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DISTRIBUTED WITH AUTOTEST MAGAZINE No. 20 / SEPTEMBER 2011 SIAR IS AFFILIATED TO INTERNATIONAL FEDERATION OF AUTOMOTIVE ENGINEERING SOCIETIES EUROPEAN AUTOMOBILE ENGINEERS COOPERATION Ingineria Automobilului Society of Automotive Engineers of Romania Romanian Automobile Register • Interview with Dr. Ir. Jan Leuridan, LMS International • Fuel Cell Powertrain Simulation • Study of Automotive Dynamics and the Acoustic dynamics of the car A Better Reliability Modeling in The Cases of Incomplete Tests • Engine Particle Filters Sytems Research

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distr ibu ted with au totest m ag a zineno. 20 / september 2011

SIAR IS AffIlIAted to

InteRnAtIonAlfedeRAtIon ofAutomotIveenGIneeRInGSocIetIeS


IngineriaAutomobilului Society of


of Romania


• Interview with Dr. Ir. Jan Leuridan, LMS International• Fuel Cell Powertrain Simulation

• Study of Automotive Dynamics and the Acoustic dynamics of the car• A Better Reliability Modeling in The Cases of Incomplete Tests

• Engine Particle Filters Sytems Research

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Author: Prof. Dr. Eng. Dan ABĂITANCEI

Abstract: This book brings to the fore over 40 types of engines ma-nufactured in Romania in almost 60 years, in international coopera-tion or national initiatives. This book accomplished a great void in the literature that reveals a road crossed by an important sector of Romanian industry, because it draws attention to the younger gene-ration working in this field that walking on a road that has traditions in Romania. From this book you can find creative and productive scale activities that took place and they carry generations of people who have worked and are still working in this area2011 ALMA Craiova, Publishing, ISBN 978-606-567-089-1Contact author: +40268 512 243


Autors: Conf. Dr. Ing. Adrian Sorin ROSCA, Conf. Dr. Ing. Ilie DUMITRUAs. Drd. Ing. Andrei Gheorghe NANU

This book is addressing mainly to students and to those who are in-volved in the field of automotive engineering. The authors are present-ing various subjects related to road vehicles (like engine, transmission and other sub-systems), using modern software (Catia, Inventor etc).The book is made up of several examples for each given subject, exam-ples covering a wide range of information that will assist the readers in their quest to improve the skills and knowledge.

Universitaria Craiova Publishing, 132 pages, ISBN 978-973-742-571-3Details about the book can be obtained at: [email protected]

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The AIAR (Association of Automotive Engineers of Romania), founded in 1988 as

part of the CNIT (National Council of Engineers and Technicians), became in 1990 SIAR (Society of Automotive Engineers of Romania), it was the result of recognizing both national and international professional prestige of the specialists from

universities, research units and production sector, all involved in the automotive industry in Romania. It was also decided to edit a journal to introduce the events of the new company and to present the most valuable of both Romanian and foreign researchers acting in the field of automotive engineering. Thus, in the summer of 1990, with the high professionalism support of the “Monitorul Oficial”, appeared the first issue of the “Journal of the Romanian Automotive Engineers” (RIA), whose chief editor was Dr. Eng. Dumitru Marincaş. The magazine was published monthly until 2000. Afterward, the appearance of the magazine ceased because of financial reasons.On the 1st of October 2006, the new journal “Ingineria Automobilului” (Automotive Engineering) has been launched (quarter issue) with the support of the Romanian Automobile Registry (RAR) and distributed together with the Auto Test magazine.During its five years of existence, the journal “Ingineria Automobilului” has been continuously modernized and adapted to the field, knowing a series of transformations.The interviews with prominent personalities at home or abroad acting in the field of automotive engineering or related to this area were highly appreciated. The interviews started to be

published with the magazine no. 6 of March 2008. Among the personalities interviewed it is worth to mention Prof. Gunter Hohl, General (r), Vice President FISITA and President EAEC; Mr. Constantin Stroe, general manager of ACAROM and vice president of Dacia Renault and RTR; Mr. Philippe Prevel and Mr. Sorin Buse (CEOs Renault Technologie Roumanie); Prof. Dr. Eng. Nicolae Vasiliu, from the University “Politehnica” of Bucharest, Department of the Hydraulics and Hydraulic Machinery; Dr. Peter Pleus, general director of Schaeffler Romania; Mr. Bernard Gauvin, president of the WP 29, CEE-UN; the rectors of universities from Bucharest, Brasov and Pitesti and more recently, Mr. Andras Siegler, director of the Directorate Transport of the Directorate General for Research and Innovation of the European Commission.New fields which have expanded the journal`s horizon of information and interest such as “Research in universities”, “University laboratories”, “Student achievements“ etc. have been introduced.The increasing interest in papers and information published by the “Ingineria Automobilului” determined its managerial team to increase the number of pages from 16 to 24 (starting from no. 10 of March 2009) and to edit it in two separate formats: one “printed“ – entirely in Romanian language and one “on-line” – entirely in English language posted on the website “ingineria-automobilului.ro”(starting from no. 19 of June 2011).Celebrating the 5 years of the “Ingineria Automobilului” journal’s life, often in adverse economic conditions, I congratulate the editorial team as well as the readers and wish them long life together!

Mircea Oprean

Summary „Ingineria Automobilului“ No. 20


3 – „INGINERIA AUTOMOBILULUI” The 5th anniversary5 – Interview with Dr. Ir. Jan Leuridan – Executive Vice-President & Chief Technical Officer LMS International 7 – Fuel Cell Powertrain Simulation 10 – The Interdependence between the Functional Dynamics and the Acoustic Dynamics of the Car12 – A Study Regarding a Better Reliability Modeling in the Cases of Incomplete Tests15 – Research on the Construction and Performances

of Particle Filters from the Depolluting Engine Systems19 – Intermediate Warehouses – Logistics Solution. A Case Study23 – Annual Session of Scientific Papers „IMT ORADEA – 2011”24 – The laboratory for performances certification of electro-hydraulic amplifiers University Politehnica of Bucharest25 – University Research26 – Challenge KART LOW COST

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Ingineria Automobilului

romAnIAn AutomobIle


General ManagerSotir STANCU

Technical ManagerFlavius CÂMPEANU

Auto test

Chief editorLorena BUHNICI

editorsRadu BUHăNIţă

Emilia VELCU

Contact:Calea Griviţei 391 A,

sector 1, cod poştal 010719, Bucureşti, România

Tel/Fax: 021/202.70.17E-mail: [email protected]


ContactFaculty of Transport

University POLITEHNICAof Bucharest

Splaiul Independenţei 313Room JC 005

Cod poştal 060032, sector 6Bucureşti, România

Tel/Fax: 021/316.96.08E-mail: [email protected]


Art grouP Int srl

Str. Vulturilor 12-14, sector 3Bucureşti

Full or partial copyingof text and pictures

can be done only withAuto Test Magazine approval,of the Romanian Automobile

Register and of SIAR

soCIetY oF AutomotIVe engIneers oF romAnIAPresident: Prof. eugen mihai negruş

Vice-president: Prof. Cristian AndreescuVice-president: Prof. Anghel ChiruVice-president: Prof. Ioan tabacu

General Secretary: Dr. Cornel Armand Vladu

redactor şef Prof. mircea oPreAn Universitatea Politehnica Bucureşti

redactori-şefi adjuncţi Prof. gheorghe-Alexandru RADu Universitatea Transilvania Braşov Prof. Dr. Ing. Ion CoPAe Academia Tehnică Militară, Bucureşti

redactori Conf. Ştefan tAbACu Universitatea din Piteşti Conf. Adrian sACHelArIe Universitatea Gh. Asachi Iaşi Conf. Dr. Ing. Ilie DumItru Universitatea din Craiova Lector Cristian ColDeA Universitatea Cluj-Napoca Lector Dr. Ing. marius bĂŢĂuŞ Universitatea Politehnica Bucureşti Dr. Ing. gheorghe DRAgomIr Universitatea din Oradea

ColegIul De reDACŢIe

sCIentIFIC AnD ADVIsorY eDItorIAl boArDProf. Dennis Assanis

University of Michigan,Michigan,

United States of America

Prof. rodica A. bărănescuUniversity of IIlinois at Chicago

College of EngineeringUnited States of America

Prof. nicolae burneteTechnical University of Cluj-Napoca


Dr. Felice e. CorcioneEngines Institute,

Naples, Italy

Prof. georges DescombesConservatoire National

des Arts et Metiers de Paris,France

Prof. Cedomir DubokaUniversity of Belgrade


Prof. Pedro estebanInstitute for Applied

Automotive ResearchTarragona, Spain

Prof. radu gaiginschiTechnical University

„Gh. Asachi”of Iaşi, Romania

Prof. berthold grünwaldTechnical University

of Darmstadt, Germany

Eng. eduard golovatai-schmidtINA-Schaffler KGHerzogenaurach, Germanz

Prof. Peter KucharUniversity for Applied Sciences,Konstanz, Germany

Prof. mircea opreanPolitehnica University of Bucharest,Romania Prof. nicolae V. orlandeaRetired Professor, University of MichiganAnn Arbor, M.I., USA

Prof. Victor oţătUniversitatea din Craiova, România

Prof. Pierre PodevinConservatoire Nationaldes Arts et Metiers de Paris, France

Prof. Andreas seeligerInstitute of Mining and Metallurgical Machine, Engineering,Aachen, Germany

Prof. ulrich spicherKalrsuhe University, Karlsruhe, Germany

Prof. Cornel stanWest Saxon University of Zwickau, Germany

Prof. Dinu tarazaWayne State University, United States of America

Serie nouă a Revistei Inginerilor de Automobile din România (RIA), 1992-2000Cod ISSN 1842 - 4074

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Interview with Dr. Ir. Jan LeuridanExecutive Vice-President & Chief Technical Officer LMS International

Ingineria Automobilului: Who is LMS International?Dr.ir. Jan leuridan: LMS, the leading partner in test and mecha-tronic simulation in the automotive, aerospace and other advanced manufacturing industries, helps customers get better products to market faster. With a unique combination of mechatronic simula-tion software, testing systems and engineering services, LMS tunes into mission critical engineering attributes, ranging from system dynamics, structural integrity and sound quality to durability, safety and power consumption. With multi-domain and mechatronic sim-ulation solutions, LMS addresses complex engineering challenges associated with intelligent system design and model-based systems engineering. LMS has become the partner of choice for over 5,000 leading discrete manufacturing companies worldwide. Ingineria Automobilului: How do you see the vehicle of the future? What is the potential of different clean automotive propulsion tech-nologies for contributing to de-carbonization objective in the short, medium and long term?Dr.ir. Jan leuridan: As polluting fossil-based energy becomes scarcer and more expensive, governments are taking measures for a balanced energy mix that combines conventional and renewable sources, and are making regulations to steer consumer’s behavior. By 2030, global energy use will be doubled, but CO2-emissions will have to be reduced by 80% to 95% by 2050. The race to reduce

greenhouse gasses and to achieve greater energy efficiency is offer-ing some of the most challenging engineering opportunities in de-cades.Manufacturers and suppliers are developing hybrid-electrical/die-sel vehicles, liquid hydrogen-fuelled hybrid propulsion systems, and electrical navigation drive systems. As a result, there is an increased demand for power electronics and high-voltage batteries. At the same time, engineers are downsizing conventional powertrains by ‘super-charging’ smaller engines, and developing advanced fuel efficiency programs. Design departments are shaping the world’s largest and smallest vehicles with composite materials to make them lighter. All of this will greatly contribute to reduce CO2. At the same time this creates great challenges on automotive development, making the field of automotive engineering at the same time very interesting. It has never been a better time to be an automotive engineer!Ingineria Automobilului: How is LMS transforming its solutions to support the automotive industry in its’ today challenges?Dr.ir. Jan leuridan: Since 1980, LMS has pioneered multi-channel computer-based testing systems. Innovative software and hardware applications cover a full set of NVH, structural, acoustic, modal, du-rability, and rotating machinery applications delivered in a modular hardware/software platform to support the integrated “LMS Test.Lab” vision.

Dr. Jan Leuridan is Executive Vice-President and Chief Technical Officer of LMS International.Dr. Leuridan received the engineering degree at the Department of Mechanical Engineering of the University of Leuven in 1980. He received a M.Sc. (1981) and Ph.D (1984) from the “Department of Mechanical & Industrial Engineering of the University of Cincinnati”. In 1984, he joined LMS International as R&D Manager, to become Chief Technical Officer for LMS International. Since 1987, Dr. Leuridan is member of the Board of Directors of LMS.At LMS, he has been directing research, technology and product development programs, aiming at deli-vering breakthrough solutions for functional perfor-mance engineering in mechanical and mechatronic product development. This includes new solutions for physical prototyping, virtual prototyping, as well as innovative, web-centric solutions for technical data organization and distribution in support engineering collaboration, enabling the approach of Model Based System Engineering (MBSE) in mechanical and me-chatronic product development.

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LMS is the industry’s leading single source provider of best-in-class hardware and software for high-end testing systems.LMS Test.Lab became the market reference with more than 5.000 active systems, totaling over 150.000 channels, where extensive user benchmarks reported 50% performance gains.By 1995 it was clear that manufacturers had to shorten time-to-mar-ket drastically to stay competitive and that physical prototype test-ing was often one of their critical path bottlenecks. LMS continued to invest in dramatic, innovative improvements in physical testing but, at the same time, expanded its vision to include the addition of virtual simulation … a unique “hybrid” test and simulation solution that, for the first time, leveraged the best of both the test and simula-tion worlds.With a series of acquisitions and innovative partnerships, LMS fa-cilitated the movement to reduce back-end prototype testing, by frontloading the design process with virtual simulation. In 2000, LMS introduced the LMS Virtual.Lab platform, which has grown to simulate many multi-physics, multi-attribute applications.To accurately simulate multi-domain intelligent system behavior and predict multi-disciplinary performance long before detailed CAD geometry is available, LMS acquired Imagine in 2007 and produced the LMS Imagine.Lab suite for 1D multi-physics simulation.With the acquisition of Emmeskay in 2010, LMS is again leading a paradigm shift, this time to evolve its solutions so as to support the emerging approach of Model Based System Engineering (MBSE). In complex, mechatronic products, controls and mechanical designs can no longer proceed independently or in parallel ; they must be interlocked, MBSE creates the ideal product development architec-ture to design, calibrate and test controls and controlled systems to-gether in a simulation environment. For the first time, the dynamic interacting behavior of the growing number of controls and software can be proven before physical prototypes become available.Is LMS providing special features/opportunities for Students, BSc, MSc, doctorate students and for young engineers in terms of using their passion / hobby for vehicles in research ?Dr.ir. Jan leuridan: Since 1980, when LMS started as a spin-off from the Catholic University of Leuven, Belgium, it has developed numerous close working relationships with Universities, world-wide. Multiple instruments have been applied for this, including like in Europe, the participation in collaborative research projects with Universities in the various EC Framework programs and strategic ini-tiatives aimed at support of Automotive Industry. Examples include research projects on noise and vibration transmission path analysis in vehicles (BRITE EURAM BE-4436-90, “DIANA”), on applica-tion of smart structures, “adaptronics”, to vehicles (EC 6th FWP, NMP2-CT-2003-501084), or more recently on warning sounds for electrical vehicles (I will look up the reference still). Such projects provide excellent collaboration platforms between academia and industry for graduate students and researchers. Additionally LMS has been very supportive to the Research Mobility programs in Europe, such as the Marie-Curie and Da-Vinci programs, providing possibilities for graduate students and researchers from universities all over Europe to spend time at LMS’ R&D centers and participate to LMS’ research initiatives focused on advancing technology and methods for automotive engineering. Many of such graduate stu-

dents and researchers have later taken jobs at LMS, and developed careers through which they could apply their interest and passion for vehicles to advance LMS’ solutions portfolio for automotive en-gineering, both test and simulation applications as well as services. Ingineria Automobilului: How do you see a better communication between LMS and universities from Romania interested for hi-quality research in automotive/multi-engineering domain? Dr.ir. Jan leuridan: When LMS established its R&D center in Romania in 2005, it also took a strong commitment to actively engage with Romanian Universities in education and research for automotive engineering. This has materialized in several partner-ships, including with the Transylvania University of Brasov and the University Politehnica of Bucharest. Through such partnerships, LMS has been providing at favorable conditions its testing systems and simulation software, to be used as platform for education and research. Moreover, LMS seeks active collaboration with graduate students and researchers in research projects focused on automotive engineering, that are supported by Romanian innovation initiatives, such as the NVHLMS Project, developed with University Politehnica of Bucharest and AMCSIT. LMS’ long-standing relationship with Renault has also facilitated to create opportunities for research-oriented cooperation between LMS, Romanian Universities and Renault’s Technology Center in Romania. Strongly, we are commit-ted to foster a strong communication and network with Romanian universities, based on which they can become engaged with LMS on applied research for automotive engineering, and through which also LMS establishes its visibility within the Romanian Academic World as a world-class high-tech company, its growing R&D center in Romania, with many employment opportunities for professions focused on test and simulation solutions for automotive engineer-ing. Ingineria Automobilului: Do you think to affiliate with University Politehnica of Bucharest and to develop an interesting research center there?Dr.ir. Jan leuridan: In recent years, LMS has been expanding rapidly its application portfolio for multi-physics, mechatronic simulation, LMS Imagine.Lab AMESim. This has been driven by both organic developments, and also acquisitions, including the French company Imagine (acquired in 2007) and the US company Emmeskay (acquired in 2010). Imagine had developed a strong re-lationship with the University Politehnica of Bucharest in the field of fluid power (hydraulic) simulation, under Professor. Nicolae Vasiliu. After Imagine became part of LMS, this relationship has further grown into one where the University Politechnica of Bucharest has now a leading center of competence for multi-physics and mecha-tronic simulation, where Imagine.Lab AMESim is extensively used for education and research. This includes specific expertise for us-ing multi-physics simulation models developed within Imagine.Lab AMESim as so-called “plant” models to support model based con-trols engineering, including Real-Time application of such “plant” models to support Hardware-in-the-Loop (HIL) set-ups. Such competences are core to LMS’ forward strategy to advance its so-lutions of mechatronic simulation for automotive engineering, and are therefore a strong foundation to further expand the partnership between LMS and the University Politehnica of Bucharest.

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This paper presents a theoretical study regarding fuel cell drive systems. The hydrogen consumption and the vehicle range are determined using simula-tion for a medium class passenger car with PEM (proton exchange membrane) fuel cell as the pri-mary electric energy source. Regenerative braking and electrical energy management were implement-ed in the global model in order to have a correct de-termination of fuel consumption during a standard drive cycle. The closed loop control for PEM, which is necessary for maintaining a high efficiency level, is detailed as well.Matlab/Simulink programming environment and the power electronics library SimPowerSystems were used for modeling and simulation. The model was validated by comparison of the results with data given by manufacturer for the simulated pas-senger car.Key words: fuel cell, electric drive system, simula-tion, PEM, PMSM.IntroDuCtIonThe more stringent emissions regulations for motor vehicles make necessary the research of new technical solutions for increasing the ef-ficiency of well to wheel energy conversion, while maintaining or even increasing dynamic performance and passenger comfort. These re-quirements lead to reducing green house gas emissions quantified as CO2 equivalent/100 km. A comparison between different propulsion systems based on present technology is present-ed in figure 1 [1].Electric vehicles have a series of advantages that lead to the reduction of energy consumption and gas emissions (especially in urban environ-ment). The main disadvantages concerning the use of electric energy as the main energy source are long recharging time and a lack of electric charging infrastructure, thus limiting mobility of the electric vehicle. The implementation of fuel cell represents an efficient solution for improv-

ing the vehicle range and reducing the recharging time. Also, creation of a hydrogen charging infra-structure can be achieved much more easily due to fewer stations necessary.Honda is one of pioneers in applying fuel cell technology to automobiles, introducing the FCX model as early as 2002 in Japan and USA [2]. In 2004 the Japanese company developed a new FCX version fitted with a fuel cell capable of cold start at -200C. Increasing of the dynamic perform-ance and the capacity to work in a wide range of climate conditions made the fuel cell power train, developed on FCX models, competitive with the

internal combustion engine in terms of perform-ance, drivability, reliability and economy.Dynamic modeling with a high degree of accura-cy of the integrated vehicle-power train system is required for fuel cell power train systems synthe-sis and fast optimization of the necessary control and command system. In addition, if it is desired to follow a drive cycle it is necessary to create a control loop with a driver model.DrIVe sYstem moDelIngConsidering the state of the art in fuel cell ve-hicle development, Honda FCX Clarity 2010 model, presented in figure 2 [6], was chosen as

Faculty of Transports,University POLITEHNICA of Bucharest

Assist. Professor marius Valentin


Professor Ioan mircea


M. Eng. studentmircea nicolae


Fuel Cell Powertrain Simulation

Fig.1. energy consumption green house gas emissions for different propulsion systems

Fig.2. The main components of the drive train of Honda FCX Clarity (2010 model)

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a study case. The global model is presented in figure 3 and con-tains the following subsystems:1. The Driver subsystem is based on a PID con-troller and has the role of maintaining a small dif-ference between real and reference speed;2. The Electric Drive System is made up of the fuel cell, the Li-ion battery, the DC/DC con-verter, the inverter and the PMSM (permanent magnet synchronous motor);3. The Vehicle subsystem is based on a longitudi-nal dynamic model of the automobile;4. The H2 Consumption and Range subsystem calculates the fuel consumption and range during a drive cycle. The parameters needed for the vehicle longitudi-nal dynamics model were adopted or computed using the vehicle technical specifications pre-sented in [3].

The electric drive system model detailed in figure 4 is made up from four main blocks and a safety module:1. Electric power management block (Power Control);2. Electric system block (Electric System);3. Electric motor controller block (PDU - Power Drive Unit);4. Permanent magnet synchronous motor and Transmission block (PMSM & Transmission);5. Safety and electrical measurements module (Watchdog & Electrical Measurements). A detailed model available in SimPowerSystems Library in Simulink [4] was used for the fuel cell. This is a generic model parameterized to repre-sent most popular types of fuel cell stacks fed with hydrogen and air. The nominal values of conver-sion for hydrogen (Uf H2) and oxygen (UfO2) are determined using the following relations:


(1) (2)

where:R - universal gas constant;T - nominal operating temperature;N - number of cells;ifc - generated electric current;z - number of moving electrons;F - Faraday constant;PH2 - absolute supply pressure of hydrogen;Vlpm(H2) - hydrogen flow rate;Pair - absolute supply pressure of air;Vlpm(air) - air flow rate;x% - percentage of hydrogen in the fuel;y%- percentage of oxygen in the air.Based on relations (1) and (2) it can be concluded that for the fuel cell stack to work at an optimum efficiency, close to nominal conversion values, a flow control system is necessary. For the purpose of solving this problem a control block was real-ized. It regulates the mass flow of hydrogen and air in function of the estimated electric current consumption of the drive system. The hydrogen mass flow is determined with the formula:


Fig.3. global model in simulink

Fig.4. electric Drive system

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where:p - hydrogen pressure;M - hydrogen molar mass (2.0158814 g/mol).A dynamic model was used for the electric mo-tor and the controller. It is based on AC6 block from SimPowerSystems Library [4]. The speed controller is based on a PI regulator. The output of this regulator is a torque set point applied to the vector controller block. These values are used in the vector controller to generate the reference sinusoidal current waves needed to command a three phase IGBT inverter.The Battery block from SimPowerSystems Li-

brary [4] was implemented for the Li-ion poly-mer battery. The Battery block implements a ge-neric dynamic model parameterized to represent most popular types of rechargeable batteries.The transmission subsystem contains a gear ratio of 9.44:1 and a constant efficiency of 96%.resultsThe instantaneous hydrogen consumption, as it can be observed in figure 5, rises to a maximum of 0.8 kg/h when accelerating and it drops to a minimum value of 0.05 kg/h while regenerative braking is in use. The high fuel cell response time is caused by

the „charge double layer“ phenomenon due to the build-up of charges at electrode/electrolyte interface and the dynamics of external equip-ments (compressor, regulator and loads) [6]. The surplus of electrical energy goes into the battery, thus maintaining the system in balance. This phenomenon can be observed in figure 6, as a high negative current at the battery termi-nals, while going from positive acceleration to steady speed.The fluctuation for effective and maximum theoretical efficiency of the fuel cell, in ECE15 cycle, can be observed in figure 7. The mean value for effective efficiency of the fuel cell stack was 63.88%. This result is very close to the mean maximum theoretical value which could be ob-tained in case of an ideal control (64.95%).ConClusIonsAn error of 0.67% was obtained using the block for acceleration and braking command (Driver- PID Controller) in regard to vehicle speed and NEDC reference speed. The efficiency of the al-gorithm implemented for the control of hydro-gen and air flows was demonstrated.An estimated hydrogen consumption of 0.832 kg/100 km and a range of 441 km are obtained for NEDC cycle. An error of 4.3% has resulted when compared to the range stated by Honda for NEDC (460 km) [5].Using only the ECE15 drive cycle a hydrogen consumption of 0.98 kg/100 km and a range of 386 km are obtained.

Fig.5. Hydrogen consumption and vehicle speed during eCe15 cycle

Fig.6. Vehicle speed and electrical power for fuel cell stack and battery during eCe15 cycle

Fig.7. Fuel cell stack efficiency during eCe15 simulation

bIblIogRAPHY: [1] Peter Froeschle, Electrification of the Drivetrain – Evolution or Revolution?, 8th International CTI Symposium & Transmission Expo, 2009[2] Souleman Njoya Motapon, A generic fuel cell model and experimental validation, M. Eng. Thesis, École de Technologie Superieure, Universite du Québec, 2008[3] http://automobiles.honda.com/fcx-clari-ty/specifications.aspx[4] Mathworks help toolbox – SymPower Systems[5] Toyohei Nakajima, Fuel Cells & Hydrogen for Sustainable Transport, Industry Update Meeting, Copenhagen, 30th November 2009[6] Minoru Matsunaga , Tatsuya Fukushima, Kuniaki Ojima, Powertrain System of Honda FCX Clarity Fuel Cell Vehicle, World Electric Vehicle Journal Vol. 3 - ISSN 2032-6653, 2009[7] Peter J. Mohr, CODATA Recommended Values of the Fundamental Physical Constants: 2006,. Rev. Mod. Phys, Vol. 80, 2008, pp. 633–730

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The Interdependence between the Functional Dynamicsand the Acoustic Dynamics of the Car

AbstRACtExperimental research has highlighted the in-terdependence between functional parameters frequently used in the study of vehicle dynam-ics (speed, acceleration and vehicle deceleration, throttle position, engine speed, fuel consumption etc.) and the sound level produced during the ve-hicle’s movement (emitted noise). To this purpose, the current paper relies on experimental data gath-ered from vehicle testing sessions, especially those vehicles that are fitted today with an electronically controlled engine thus meaning that the exist-ing data is gathered from the onboard computer. Based on this data, mathematical patterns are es-tablished, both discrete and continuous, which gives the values to the functional parameters that define vehicle dynamics depending on the sound level that accompanies their movements. In order to establish these models, calling on to system identifying algorithms and to specific procedures of information theory and extreme values theory.Also, the paper presents some aspects regarding the analysis of the acoustic field of vehicles, relying on algorithms specific to time analysis, frequency analysis and time-frequency analysis; references to correlation analysis, cepstral analysis, coherence analysis, extremal analysis, entropic and informa-tional analysis of the sound level (emitted noise). The paper highlights some aspects regarding the synthesis of vehicle’s acoustic field, which allowed for the establishment of mathematical models both discrete and continuous which offers values to the sound level depending on the other functional pa-rameters which define vehicle dynamic behavior.The moving of cars is accompanied by the appear-ance of acoustic phenomena, often called noises; further in this paper it will be used the notion of acoustic field, which is a generalization [5;6], hence the concept of acoustic dynamics of vehicle. This paper aims to address, for the first time in lit-erature, the theoretical and experimental problem

of the dynamic interdependence between functional dynamics and acoustic dynamics of the car, both in real time, taking advantage of a new theoretical treatment and of the possibility of acquiring data from transducers and elements incorporated in the manufactur-ing execution and taken from the vehicle’s onboard computer. This paper uses the instantaneous val-ues of the functional parameters and noise emitted during the vehi-cle movement and the mentioned interdependence will be found in mathematical models based on experimental data, applying algorithms to identify dynamic systems and processes [1;2;4]. The experimental research was conducted with a Daewoo Tacuma car equipped with fuel injection engine and allowed data acquiring from transduc-ers and elements incorporated in the manufactur-ing execution and taken from the vehicle’s onboard computer. For this purpose was used the SCAN-100 tester, the 1 landmark from fig.1a, that was connected with the vehicle’s onboard computer by the car diagnostic plug. Also, it was used the laptop 2 from fig.1a on which specialized data acquisition software was implemented and that was connected with the microphone 3 from fig.1b using the cable 4, so that the functional parameters and noise mea-surements flow simultaneous. A special attention was paid to the positioning of the microphone for the instantaneous sound recording. Since the main purpose of this work was to establish the interdependence between functional dynamics and acoustic dynamics of the vehicle, both in real time, the microphone was placed in the engine compartment, remaining in the same position during all the experiments. The accuracy of the mi-

crophone placing was confirmed by the analysis of the acoustic field. Also, it should be noted that the experimental researches were made after technical verifications of the car, to avoid other unexpected noises. Obviously, each experimental test has spe- Obviously, each experimental test has spe-Obviously, each experimental test has spe-cific features. For instance, fig. 2 shows the experi-mental values (top graphics) and also the calcula-ted values (bottom graphics) for the acoustic noise level for two experimental tests, T19 and T20. As it was expected, there are different variations of the dynamic series for the two tests. Also, fig.2 shows (by comparing the top graphic with the bottom graphic) the interdependence between experi-mental acoustic field and calculated noise level, the A points emphasizing the highest values and the B points emphasizing the lowest values from the bottom graphics, where it was used the 2-norm of the ∆h calculation step.Finally, the top graphics emphasize a variation in the h∈[-1;1] range for experimental data, that are specific for ”.wav” files wich on the experimental acoustics is operating. The graphics from fig. 2 show the pronounced cha-racter of variation for experimental acoustic field and for calculated noise level that accompanies the car movement. This character suggests that a car’s

Military Technical Academy, Bucharest, email: ion_copae@


Armaments Department, Bucharest, email: ruicu.

[email protected]

Eng. Dumitru ruICu

Univ. prof. eng. PhD. Ion CoPAe

a) b)Figure 1

Figure 2

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acoustic field has a nonlinear and nonstationary character; from this are arising implications in the acoustic field analysis (by using some algorithms for emphasizing the nonlinearity and bispectral analysis and time-frequency analysis) and in the acoustic field synthesis (by establishing some non-linear mathematical models and some mathemati-cal models with variable coefficients). The acous-tic field analysis appeals to methods of analysis in time, frequency and time-frequency analysis; the frequency analysis (spectral analysis) comprises the monospectral analysis based on Fourier trans-form, bispectral analysis and cepstral analysis. Also, for establishing the linear dependence, it is appeal-ing to bispectral frequency analysis and entropic and informational analysis of the data; the infor-mational analysis of the data allows determining the relevant variables, so those variables are adopt-ed like main parameters of mathematical models.

For establishing the values of the acoustic field out-lines’ we appeal to to extre-mal analysis. For instance, time-frequency analysis allows us to determine the fundamental frequencies, which concur with the first formant. Thus, fig.3d and fig.3c present how the fundamental frequencies for T18 test are established by using the flat spectro-gram. Fig.3 chart shows that fundamental rotation frequencies are equal to the νc frequencies of en-

gine crankshaft. This shows the correctness of the microphone arrangement for instantaneous sound recording, confirming that the experiments meet the main requirement imposed, which is to high-light the interdependence of functional dynamics and acoustic dynamics. The synthesis of the acous-tic field, as a complementary analysis, provides mathematical modeling for the noise level (noise), which allows the reconstruction / restoration of its analytical form, tabular or graphical. In this case it is using the specific acoustic field synthesis algo-rithms and the algorithms to identify systems and processes for establishing the mathematical mod-els which have the noise as a result; the mathemati-cal models can be discrete, continuous or extremal [4; 5].For instance, Fig.4 presents the establishment of a generalized linear mathematical model (for all the 40 tests) in continuous (a differential equation) field, which provides the noise values Z according to engine speed n and throttle position ξ.As found in Fig.4, the mathematical model has the form of a first order differential equation:


From this expression result related transfer functions:- the transfer function related to engine speed with polynomials in fig.4:


- the transfer function related to the throttle position:


both of them being written in the Laplace transform argument s. Unlike the previous case,

the mathematical model presented in Figure 5 is continuously offering the car speed values V depending on the noise level Z, the throttle position ξ and the engine speed n. Therefore, this example has three variables as input factor and the result factor is speed, which defines the vehicle dynamics. Thus, the example in Fig.4 shows the relationship between functional dynamics and acoustic dynamics; however, the example of fig.5 connects acoustic dynamics and vehicle functional dynamics. The sought mathematical model is a II order differential equation:


the modeling error having in this case also an acceptable value. In this case, three transfer func- In this case, three transfer func-tions in continuous field will be established, since there are three input parameters. For instance, the transfer function for noise Z is:


in a similar way also resulting the other two trans-fer functions. Based on what was presented above it can be concluded that it is possible to study the interdependence between functional dynamic and automotive acoustic dynamics, using functional parameters commonly used and emitted noise measured in different places. It should be noted that, unlike traditional approaches, in this paper are used the instantaneous values of noise and other variables that define the functional dynamics of cars [3; 5].Mathematical models based on experimental data highlight the mentioned interdependence and allow similar approaches on dynamic systems and functional processes accompanied by acoustic phenomena.

Figure 3

Figure 4

Figure 5


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bIblIogRAPHY: [1] Copae I. Dinamica automobilelor. Teorie şi experimentări. Editura Academiei Tehnice Milita-Editura Academiei Tehnice Milita-re, Bucureşti, 2003[2] Copae I., Lespezeanu I., Cazacu C. Dinamica autovehiculelor. Editura ERICOM, Bucureşti, 2006[3] Gillespie D. T. Fundamentals of Vehicle Dynam-ics. SAE Inc., S.U.A, 1992[4] Ljung, L. From Data to Model: A Guide Tour of System Identification. Department of Electrical Engineering, Linkoping University, Sweden, 1995[5] Ruicu D. Contribuţii la studiul dinamicii auto-mobilelor pe baza câmpului acustic al acestora. Teză de doctorat, Academia Tehnică Militară, Bucureşti, 2011 [6] Ruicu D., Bivol G., Copae I. Considerations re-garding the analysis and synthesis of vehicle acoustic field. Annual symposium of the Institute of Solid Mechanics SISOM 2011, Romanian Academy, Bucharest, 2011

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A Study Regarding a Better Reliability Modelingin the Cases of Incomplete Tests

AbstRACtFor modeling the reliability, there are used spe-cifically designed computing programs, two situ-ations being possible: complete tests and incom-plete tests. However, it is found that in the cases of incomplete tests it is not made distinguish between the censored type testing (which ends when a preset number of products of consid-ered batch failed) and the truncated type testing (which ends at a predetermined time moment). In the case of the incomplete type testing, there is not taken into consideration the time interval between the moment of the last failure and the moment of the end of the experiment (the case of truncated type testing). Therefore, based on the realized study, there is proposed a computing al-gorithm for modeling the reliability in the case of the truncated type testing. The obtained theoreti-cal and practical results confirm the utility of the proposed algorithm. For any other mathematical model used in the truncated type testing, it will be built the suitable computer algorithm. Key words: reliability modeling, computing pro-gram, censored tests, truncated tests, Weibull law.Problem FormulAtIonTher are used special designed computing pro-grams to determinate the reliability indicators for different mathematical models. For example, ReliaSoft Weibull ++7 [5] is a high-performance program, which, based on the data obtained by monitoring a batch of products in the real exploi-tation or in the framework of special organized tests, achieve the following:1 – make the graphs: FS histogram, FS Pie, FS Timeline (the shape is unique, regardless of theoretical law that will be used for mathematical modeling of reliability);2 – realize experimental distribution modeling through various theoretical distribution laws: Weibull-2P, Weibull-3P, Normal, Lognormal, Exp-1P, Exp-2P, G-Gamma, Gamma, Logistic, Loglogistic, Gumbel, etc.;

3 – make for any models of reliability the graphs of the following reliability indicators: Probability, Reliability, Unreliability, Pdf, Failure rate, Contour (this one only for models Weibull-2P, Weibull-3P, Normal and Lognormal);4 – present the graph for each indicator, simulta-neously for all the laws, in order to make a com-

parison by viewing them in the same time.But working with these computing programs, it was found, however, that these have some limita-tions in terms of differentiating between different types of tests. Thus, next there are presented the following research.So, it was started from the mileages where it were

Alexandru boroIuUniversitatea din Piteşti, Facultatea Mecanică şi Tehnologie, Departamentul Autovehicule, [email protected]

Fig. 1. The graph F/s timeline for the complete test (F = 10, s = 0).

Fig. 2. The graph Probability Weibull-3P for the complete test (F = 10, s = 0).

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broken the 10 right transmission shafts of a lot of cars with the powerplant arranged transversally, in the framework of a complete test (the test stops after the failure of all components) – presented in

Table 1.The experimental data are highlighted in figure 1 (the number of failed elements is F = 10, and the number of the supervised elements that were not damaged is S = 0), and the graph Weibull-3P (the three-parametric model) which shows the values of the three parameters (β = 3.0129; η = 25157 km; γ = 14417 km) is presented in figure 2.Using the same values for the proper functioning times of the 10 transmission shafts, it was imag-ined an incomplete test in which F = 10 and S = 10, but with different scenarios for the values as-

signed to the 10 monitored elements which are not breaks during the experiment:1 – it is considered censored type test (it ends with the failure of the tenth element), so for all the 10 elements that continue to operate, there are assigned the value of the last recorded time: tS = 48203 km (figure 3 and figure 4).2 – it is considered the truncated type test (it not ends with the failure of the tenth element, but at a predetermined time, which is higher than the last recorded time), so for all the 10 elements that continue to operate, there are assigned a value of the time at which the test stops: tS = 60000 km.3 – there are imagined, also, other values for the truncation times of the experiment: tS. It is found that for all these different scenarios there are ob-tained the same values for the Weibull-3P model parameters, ie, the computing program consid-ers all these different tests as a censored type test (with the censoring time equal to the time at which breaks the tenth element).Continuing the investigations, it is imagined an-other censored test, in which F = 10, but S = 20 (total, 30 elements are tracked). It appears that this time it is really obtained different values for the three Weibull parameters, so the program has discriminatory power for censorship tests. Analyzed test data are presented in Table 2.Continuing the investigations, it is imagined an-other censored test, in which F = 10, but S = 20 (total, 30 elements are tracked). It appears that this time it is really obtained different values for the three Weibull parameters, so the program has discriminatory power for censorship tests. Analyzed test data are presented in Table 2.It concludes that the computing program identi-fies correctly the complete test and the incom-plete tests of censored type, but not the incom-plete tests of truncated type. As a result, we intend to realize a research through which we provide those theoretical elements necessary to identify an incomplete test of truncated type and for cre-ating a suitable computing program to model reli-ability based on this type of tests.reAlIZeD reseArCHesTo find the theoretical elements necessary for processing the data obtained through incomplete tests of truncated type, it can be started from the most visible reliability indicator of reliability which depends of the type of reliability test, the estimated value of mean time between failures m [2].• for complete tests:


No Failure time [km]1 247912 284273 311754 338715 353386 380337 401028 429139 4521810 48203

table 1. The values for failure times

Fig. 3. The graph F/s timeline for the censored incomplete test (F = 10, s = 10).

Fig. 4. The graph Probability Weibull-3P for the censored incomplete test (F = 10, s = 10).

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• for incomplete tests of censored type:


• for incomplete tests of truncated type:

(3)where:- tF is the time corresponding to the failure of the last element in the censored test;- ttr is the truncation time of the test.In the particular case of modeling by law Weibull-3P, the mean time between failures value m is depending of the all 3 Weibull parameters:


where Γ represents the Euler function of first rank (Gamma type), defined through the analytical relation:

(5)Since the analytic relation of this function is quite complicated, in reliability studies is more easily to work with the function values calculated and listed in tables (Andreescu, 1996).The indicator m is in relation to all the three Weibull parameters, so we are not dealing with a bi-univocal relationship, deterministic, so that will be performed an analysis to decide which of the three indicators is most appropriate to be cor-rected depending on the value of m , and thus depending on the type of test.For this, we must define the three Weibull param-

eters (O’Connor, 1991):- γ is the localization parameter or parameter posi-tion, an constant that defines the start time of the variation of reliability function R(t);- η is the scale parameter, expresses the extension distribution on the time axis; so, if (t – γ) is equal with η, R(t) becomes:

368.0ee)t(R 11 === −− β

, (6) ie, scale parameter represents the time, measured from the moment γ = 0, at which 63,2% of the elements can be failed. Therefore, this parameter expresses a characteristic operating time.- β is the shape parameter, is dimensionless and represents the parameter that determines the shape and curves of variation for the reliability indicators.The parameters γ and η are expressed in time units and can be graphically highlighted (figure 5).As the previously revealed problem express that the program does not offer the possibility of ex-tending the distribution on the time scale accord-ing to the value of truncation time (larger than the censoring time), it follows that the most suit-able to be put in a deterministic relationship with the mean time between failures m is precisely the scale parameter η. For this, there will be proc-essed the analytical relations for the mean in the case of the two types of tests – the censored test (for which the program calculates the parameters Weibull, including ηcens) and the truncated test (which is intended to determine the parameter ηtrun):


(8)It results the inegality:

, (9)By reducing the inequalities (2) and (3) to equal-ities there is obtained concrete and satisfactory values for the means, so based on the relation (9) it can be effectively realized the calculation for parameter ηtrun.


Thus, in the case of truncated test from the posi-tion 3 in Table 2, we obtain the relation (10).

a value according to what is expected for the trun-cated test: a more extended theoretical distribu-tion on the time axis, compared with the case of censored test. Therefore, the Weibull model which will be used for the truncated test from the position 3 in Table 2 will have the parameters: β = 1.6984; η = 44897 km; γ = 19871 km. ConClusIonsBased on the realized researches, it can be build a computing program for the case of incomplete tests of truncated type in the case of Weibull model, by using the additional relationship (10).In the cases of other mathematical models (in-cluding the models with one parameter, even there is no issue of the parameter choice that will be corrected) – [4], a similar analysis is required to create the computing program that will com-plement the complex software dedicated to reli-ability study.

bIblIogRAPHY:[1] Andreescu, C., a.o. (1996), Aplicaţii numerice la studiul fiabilităţii automobilelor, ISBN 973-95856-0-4, Ed. Magie, Bucureşti[2] Cordoş, N., Filip, N. (2000), – Fiabilitatea autovehiculelor, ISBN 973-99779-4-4, Ed. Todesco, Cluj-Napoca[3] O’Connor, P. (1991), Practical Reliability Engineering, ISBN 0-471-92696-5, Ed. John Wiley&Sons, New York[4] *** (1987), Automotive Electronics Reliability Handbook, SAE, ISBN 0-8988-009-5, Warrendale[5] *** www.reliasoft.com

Fig. 5. The highlighting of the parameters γ and η on the graph r(t) in the case of Weibull law.

No. Test Type F S F+S The values of the Weibull 3-P model parameters

1 completed 10 0 10 β = 3,0129; η = 25.157 km; γ = 14.417 km.

2 censored 10 10 20 β = 1,6984; η = 35.616 km; γ = 19.871 km.

3 truncated 10 10 20 identical with row 2

4 censored 10 20 30 β= 1,5497; η= 49.639 km; γ= 20.429 km.

table 2. experimental data and results obtained in the framework of reliability tests.

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AbstRACtThe paper presents an analysis of the construc-tive solutions of diesel particle filters (DPF) which make up a depolluting system specific to middle class cars. There are also mentions regarding the formation of mechanic particles (MP), from the exhaust gases, highlighting the necessity to reduce their concentration and the specific ways to fulfill this objective. An analysis of the DPF regeneration methods is also pre-sented and of the implementation solutions on the car. The paper also presents the results of the research concerning the pressure drops value limits in the case of a new DPF and another one subjected to repeated regenerations.tHe neeD to Post-treAt tHeeXHAust gAses oF CAr engInesThe fitting of the cars equipped with compres-sion ignition engines (c.i.e) and spark ignition engines (s.i.e) with direct fuel injection within EURO 5 and EURO 6 standards supposes spe-cial depollution measures by using the post-treatment exhaust gases systems. The strict lim-its of these standards are presented in table 1. In this context experience has shown that the par-ticle filter (DPF -diesel particle filter) is an indis-pensable element within the depollution system structure. Therefore, extended researches are taking place both as to the mechanism of the particle formation as well as to the constructive optimization of the PAF. These researches are also connected to way of regeneration of these filters and the implementation architecture of the DPF on a car.

Research on the Construction and Performances of Particle Filters from the Depolluting Engine Systems

Prof. univ. dr. ing. Florian IVAnCatedra AutomobileFacultatea de Mecanică şi TehnologieUniversity of Piteş[email protected] [email protected]

University of Piteşti

drd. ing. Daniel lIŢĂ

drd. ing. Andrei buŞoI

table 1 euro standards evolution

Pollutants CO [g/km]HC


[g/km]NOx [g/km] Particles [g/km]


Gas GasDiesel Diesel

GasDiesel Gas




Euro 3

(2000/2001)0,64 2,3 0,2 0,56 0,5 0,15 0,05 -

Euro 4

(2005/2006)0,5 1 0,1 0,3 0,25 0,08 0,025 -

Euro 5a

(2009/2011)0,5 1 0,1 0,23 0,18 0,06 0,005 0,005

Euro 5b (2011/2014)

0,5 1 0,1 0,23 0,18 0,06 0,0045 0,0045

Euro 6b

(2014/2016)0,5 1 0,1 0,17 0,08 0,06 0,0045 0,0045

DI – direct injection IDI – indirect injection

Figure 1. The escapes absorbed bythe respiratory tract

Figure 2. structure of the mechanic particle

Figure 3. The mechanic particles formation mechanism

a) a) Ceramic monolith DPF b) b) metallic fibers DPFFigure 4. longitudinal section of a DPF

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ConstruCtIVe AnD WorKIngDPF DAtAThe particle filter is a filtration system used to retain fine particles, having a cancerigenic effect, contained in the exhaust gases. These soot parti-cles are essentially made up of carbon and they have typical dimensions varying between 10 nm and 1 μm. Finer particles (nanoparticles) cannot be fully retained by the constructive solutions of the FAP. Experimental studies have shown that the hid-rocarbs at high temperatures (more than 1500 °C) and with little oxygen (rich mixture, the excess air coefficient, λ<0,6), conditions met inside the fuel flow, simultaneously taking place the dehydrogenation phenomenon. Therefore, the carbon gathers in six-angled structures (mineral carbon) and it forms layers which give birth to spheres having a diameter of 400 Ǻ. The spheres are known as turbostratic structures and after they reach such dimensions they become very unstable and begin to gather in irregular structures and shapes, most of them measur-ing between 0.01 and 0.1 µm. These structures

mostly made up of carbon, contain almost 1% hydrogen and are known as soot. The soot parti-cles that reach the exhaust system meet unburnt hydrocarbons due to the heavy escapes of fuel or oil. When temperatures goes below 500°C, these heavy hydrocarbons firm on the surface of the soot particles giving birth to mechanic particles. Mechanic particles represent a real threat to human health. Their effects on the respiratory system are well known, as well as their canceri-genic ones when inspired. If nowadays the ac-tual standards impose limits regarding the mass of the particles, in the future these standards will have to mention also their dimensions, as well as their numbers, because it is well known that the smallest MP are also the most dangerous. Figure 1 shows the relation between absorbed particle percentage by the respiratory system and their dimensions. One can notice that the highest absorption percentage belongs to 0.1 MP (the circles area in figure 1).The formation mechanism of these particles is rendered schematically in figure 3, and their structure in figure 2. The composition of a MP depends on the per-fecting of the burning process (the organized movement in the combustion chamber, over-feeding, the air/fuel relation), the Diesel oil quality (sulphur content, cetane number), the post treatment temperatures of the system cata-lyst case- particle filter.When making the particle filters (DPF) one uses porous ceramic materials such as silicon carbide or cordierite, and more recently metal-lic fibers.Ceramic monoliths are permeable to gas and they have a porosity (the total volume of the pores as related to the total volume of the body) of 52% (less than 9-10 μm). Generally, in the case of a 52% porosity, the monoliths have the following densities:

For the cordierite ceramic: 490g/l;For the silicon carbide :720g/l.The major difference between the two types of monoliths is made by the melting temperature of almost 1355°C in the case of the ceramic cordierite, and in the case of the silicon carbide this one exceeds 2000°C. Figure 4a renders schematically the interior structure of a mono-lith used to make the DPF.The metallic fiber particle filter is made up of a packet of porous, unfretted metallic sheets, ren-dered schematically in figure 4b. For a good functioning these filters require the use of fuels with a sulpher concentration of less than 500 ppm. On these conditions the DPF manages to retain over 90% of the released me-chanic particles. Unlike ceramic monoliths, the metallic fiber filters are not brittle and they have the melting temperature characteristic to nickel or titanium, constituent metals. A special prob-lem is represented by the DPF regeneration. Regeneration supposes making it able to retain particles and to ensure their exhaust. In order to have an effective regeneration two basic condi-tions must be fulfilled:• the initial temperature when entering the DPF should be between 550°C and 650°C;• the O2 percentage of the gas that crosses the filter should be between 5% and 10%.In a first phase the filter retains the particles, and when a certain degree of loading is reached regeneration starts. This phenomenon takes 20 minutes at every 300-500 km, depending on the harshness of the working conditions.The efficiency of a particle filter, as well as its good functioning is established after specific experimental investigations. Therefore, the au-thors have highlighted, comparatively, the pres-sure drops curves in a reference DPF and a new one, subjected to repeated regenerations /3/, /4/. One had in view that in both cases – new PAF and regenerated DPF – the curves be with-

Figure 5. The pressure drop curvethrough the DPF

1- engine; 2- combustion chamber; 3- common type injection; 4- fuel tank; 5- injector + regulator; 6- low pressure pump; 7- additive; 8- engine computer; 9- gauges; 10- resonator;

11- pre-catalyst case; 12- PAF; 13- post combustion; 14- regeneration; 15- filtered gases.

Figure 6. Cerina adding PAF

Figure 7.Injection ways

Figure 8. Fuel injection technologies

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in the admitted limits by curves 1 and 2 (figure 5). The inferior and superior limit curves are es-tablished on some similar vehicles ensuring the fitting within the EURO 5 standards. The refer-ence pressure drop curve represents the middle area of the range. One has in view that DPF have a pressure drop as close as the reference curve 3. One notices that after the regeneration the pres-sure drop curve through the DPF undergoes a change from curve 4 to curve 5. This applies to all new particle filters, which need a stabilization period to obtain the expected results. tHe AnAlYsIs oF tHe DPFregeneRAtIon metHoDsTwo basic conditions must be fulfilled in order to have an efficient regeneration: The initial temper-ature when entering the DPF should be between 550°C and 650 °C and the oxygen gas percentage crossing the filter between 5% and 10%.

Generally, two ways of regenerating the DPF are known, namely:- Passive (natural) regeneration, occurring when the running engine has high rotation and charge (regeneration is the consequence of high tem-peratures reached by the gases in the exhaust section);- Active regeneration, which supposes either fuel injection in the DPF upstream or late injection (post injection) in the combustion chamber, electronically controlled. Post injection adjusts with the temperature increase given by the cata-lytic reactions of oxidation and with the oxygen quantity controlled with the help of a shutter.The main problems occurring when implement-ing the DPF on a vehicle are related to the old DPF recycling, limited lifetime and the con-straints related to the vehicle architecture. There are several active regeneration methods:

Regeneration by Diesel oil cerina (Ca) e) ad-ditionExperience has shown that by Diesel oil cerina addition (only during the regeneration period), the particles formed and collected by the DPF can be oxidized by burning at a lower tempera-ture. The solution has been developed on some Peugeot - Citroën engines, figure 6. Though, it has a series of disadvantages: high recycling and maintenance cost, limited lifetime, implement-ing difficulties.

Active regeneration with cylinder post in-b) jectionFigure 7 presents schematically the differences between the standard injection way and the regeneration one. In the green circled area the main injection and the post injection are meant to make up couple.The red area, late post injection is used to in-crease the DPF entering temperature due to the exothermic reaction within the catalyst case. Experience has shown that late post injection has a strong impact on oil dilution, with unwant-ed effects concerning the HC concentration.

Late post injection active regeneration up-c) stream the DPFTwo technologies of injection are used upstream the particle filter, presented in figure 8.In figure 8, variant a, one injects the fuel up-stream the catalyst with the help of an injector, and in variant b, the Diesel oil is vaporized with the help of a preheated spark plug, resembling a tube with a wasteful resistance. This regenera-tion method is costly enough, and the injector or the spark plug have to work under severe thermal and chemical conditions, which leads to low reliability.

Mixed active regeneration (with post injec-d) tion upstream the DPF and cylinder post injec-tion)This method consists in combining the late post injection with the fuel injection in the exhaust section. Thus, one tries to reduce the oil dilu-tion effect due to the increasing release burning and the supplementing of the thermal neces-sary for an optimal regeneration with the help of the exhaust injector. The major disadvantage of this method consists in introducing a new ac-tor which has to be controlled and introduced in the injection computer system, as well as a fuel increase consumption.Due to making technology and used materials, metallic fiber filters can be regenerated by the same methods as the particle filters made up of ceramic monoliths. Moreover, these have as

Figure 11. nox -tRAP + PAF + exhaust injector

Figure 9. DPF under the floor

Figure 10. DPF under turbo

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advantage the regeneration possibility through electric heating of the fibers.tHe AnAlYsIs oF tHe DPF ImPle-mentAtIon solutIons WItHIn tHe eXHAust gAses sYstem In tHe InternAl burnIng engInes Regarding the chosen regeneration way, a cer-tain architecture solution of the post treatment exhaust gases system has to be implemented on the car. The main implementation solutions on the car are:

DPF placed under the floor downstream a) DOCIn the case of this solution the necessary regen-eration DPF temperature is obtained by using the cylinder post injection. Due to the func-tioning of the compression burning engines with poor mixtures, the catalyst case C1, called DOC–Diesel Oxidation Catalyst fulfills two main functions: on the one hand it ensures the classic depollution (it changes by oxidation CO into CO2 and HC into H2O and CO2), and on the other hand it ensures the thermal necessary for the regeneration (due to exothermal oxidation reactions within the catalyst case). On the other hand, due to the great distance between the vor-tex wheel and the DPF, the second catalyst case, C2, should bring back the gas temperature to re-generation values. Regeneration control is done with the help of the injection computer based on the information received from the temperature and pressure gauges. The closed buckle control system ensures the DPF entering temperature varying between 550 - 650°C to start regenera-tion and it limits the maximum temperature at 670°C to avoid the DPF destruction.In figure 9 one used the following abbreviations: TC – measuring temperature gauge in the catalyst case; Sλ – lambda well; TDPF – temperature meas-uring gauge in the PAF; PPAF- pressure gauge be-fore and after the DPF.The information received from these gauges are used to control and manage regeneration, as well as to verify the working state of the post treatment system.This solution has as advantages the DOC quick kicking-off (130 – 150°C). As to the important disadvantages one mentions: the necessary re-generation temperature is reached difficultly (which makes regeneration to be difficult and the increase of the oil dilution), a high cost due to using two catalyst cases.The solution can be met on applications of Fiat, Saab and Opel constructors.

DPF placed under the overfeeding aggregateb) This solution has been accepted by Mercedes and BMW and has as advantages minimal ther-mal losses between the overfeeding aggregate and the catalyst case. Therefore, regeneration is easy. It has the disadvantage of setting difficul-ties.

DPF placed afterc) NOx -TRAP + exhaust injector The solution used by Renault and Toyota is presented in figure 11. In order to reduce the dilution effect caused by the damage of the post injection burning, this solution proposes adding fuel injection in the exhaust section. A reduced post injection is also maintained so that the exhaust gases temperature remain at a value to allow vaporization of the injected Diesel oil in the exhaust section. The depollution chain also comprises a catalyst case stocking NOx, called NOX-TRAP. This fulfills the functions of a DOC ensuring the regeneration temperature and, moreover, fulfilling the NOx reduction func-tion. Its construction resembles classic catalyst cases, the major difference being made by the fact that the active material contains besides the noble metals used (platinum, rhodium) also barium or zirconium. The NOX-TRAP function-ing supposes two phases:-the absorption phase, takes place during the normal functioning engine period; during this phase, after the platinum reaction NO changes into NO2, and the barium oxide connects the NO2 molecules, resulting a compound, barium nitrate, Ba (NO3)2, retained on the monolith surface covered with active material.-the reduction phase, is characterized by an engine functioning close to λ=1, that is to a minimal air quantity in order to have a complete Diesel oil burning. At the end of this phase the release as N2 occurs into the atmosphere. The chemical element responsible with NOX reduction and their release is rhodium.The two functioning phases are shown in figure 12.

This solution offers as advantage a good vaporiza-tion of the Diesel oil in the exhaust section. It has as disadvantage the fact that a regeneration at re-peated periods is required (around 100 km), and the Diesel oil injection into the exhaust section leads to a fuel increase; on the whole, a high cost.5. ConclusionsThe fitting within the strict pollution standards of EURO 5 and EURO 6 (c.i.e. and s.i.e. with direct injection) requires that cars be equipped with very complex depollution systems. Within these systems the particle filter (PAF) is indis-pensable. The depollution performances are connected on the one hand to the way in which the PAF works with the other elements in the depollution system structure (DOC, NOX-TRAP, EGR, etc.) and on the other hand to its placement way along the exhaust section. In this context the constructive solutions for a PAF im-pose extended research which have in view the minimization of the pressure drops (counter pressure) and the regeneration way. The optimal solution has to be selected taking into account the production and maintenance costs.

Figure 12. The noX-tRAP functioning phases


[1] Plint, J., Martyr, T., Engine testing , Theory & Practice, SAE, Casebound, 2007.[2] Khair, M., Majewski, A., Diesel emissions and their control, SAE, Hardbound,2006[3] Busoi, A., Ivan Fl., Dumitru, C., Experi-mental research concerning the validation of a PAF constructive variant for a C.I.E. meant for light drive, Scientific buletin, Faculty of Mechanics and Technology Automotive, 2010.[4] Busoi, A., Ivan Fl., Dumitru, C. Research on the exhaust gases backpressure effect regarding the filling and the dynamic performances of the spark ignition engines, CONAT 2010 – Braşov.[5] www.dcl-inc.com[6] www.avl.com

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KeYWorDs –logistics, distribution network, logistic platform, warehouses location, cost op-timization AbstRACtThe main focus of the paper is the use of region-al warehouses in the architecture of distribution networks. It proposes an algorithm for optimal warehouses location and it discusses in what conditions it is a better logistic solution than direct distribution.In the first section, the paper reviews the notion of regional warehouses, the role they play in a distribution network and the structure of dis-tribution architectures using them. The second section tackles the problem of optimal location for the intermediate warehouses by proposing a way of modeling this logistic problem and an algorithm to solve it.The operational nature of the findings is tested in the following section of the paper in an em-pirical study on a Romanian food company with a country wide distribution network, a Just in Time organization of flows and whose produc-tion plant is located in the suburbs of Bucharest.

The algorithm proposed in the second section helps finding the optimal location for the in-termediate warehouses in each distribution area: Muntenia, Transilvania, Moldovia, Dobrogea and South Region (with Bucharest). The conclu-sions outline the benefits of using regional platforms in the case of this company instead of direct distribution.The paper concludes explain-ing in what conditions using intermediate platforms is bet-ter that direct distribution.IntroDuCtIonRomanian companies face today the new logis-tics challenges in order to cope with interna-tional competition. This study discusses a logis-tic solution concerning distribution, and more specifically transport, which has been more and more implemented recently, namely the use of regional distribution warehouses. IntermeDIAte WAreHouses solutIonIn Romania road transport is the most common-ly used means of transport for merchandise. The classical choice for transporting goods is to di-rectly delivery them from the production plant to each final retailer. An alternative option is the use of intermediate warehouses (fig1). From a transportation point of view, they facilitate the grouped transport of the merchandise going to different locations up to a place near these loca-tions by big capacity trucks, and thus at a low unit1 price per kilometer, which may signifi-cantly reduce the transportation cost. From the regional platform to the retailers the transport is operated by small capacity trucks which may offer more flexibility.Nowadays, more and more companies choose to manage their production flows in Just in Time. In this kind of systems the production man-

1. By „unit” we mean unit of transport which is the standard box of 1m3 (with the standard dimen-sions 0,850m x 1,240m x 0,970m) placed on a pal-let. From now on we will call it „eurobox”. The goods are wrapped in this type of boxes.

agement is highly integrated and it has as one of primary priorities the reduction of stocks. Therefore, this system demands a rapid flow of goods in order to reduce as much as possible the level of stocks and thus the classical function of storage of the logistic platforms (which were ini-tially warehouses) became far more complex.There are today millions of logistic platforms all over the world which are passed in transit by merchandise going to different locations, switching means of transport or even getting as-sembled from pieces coming from several loca-tions. In this study we are going to narrow our analysis to the storage function of the intermediate lo-gistic platforms. Therefore, from now on we are going to refer to intermediate logistic platforms as regional warehouses. One of the key issues to be solved when it comes to distribution architectures using regional warehouses is the choice of their optimal loca-tion. There are several strategic objectives to be taken into consideration when tackling this issue such as minimization of costs and of du-ration, proximity to key clients, flexibility and security of transport.Today there are various specific software which can indicate the right location depending on the parameters taken into consideration ranging from specialized ones to more integrated ones such as APS (Advanced Planning System) or ERP (Enterprise Resource Planning). The aim of the next section is to tackle this is-sue of warehouse location by proposing a way of

Intermediate Warehouses – Logistics Solution.A Case Study

Cristina mAneACatholic University of Louvain, Belgia

Polyvalent factory

Regional platform

Distribution to retailers with own company’s vehicles

Regional platform

Regional platform

Fig 1. exclusively using intermediateplatforms distribution

Fig.2: transportation cost components from the production plant to the retailers

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modeling this logistic problem and an algorithm to solve it.oPtImAl WAreHouse loCAtIonHYPOTHESISOn suppose that the whole production is done in a single factory from which the goods have to be transported to several retailers. The retailers can be found in different sectors (sector can mean a country, a city or a geo-graphic region where there is a concentration of demand). The algorithm is run using history data of sales by supposing that the variation of future sales respects the same repartition between retailers within a sector. OBJECTIVEFind the proper location of the regional (or in-termediate) warehouse in each sector in order to optimize the distribution flows. Optimizing the distribution flows can be understood here as minimizing the cost of transport. The same algo-rithm will be run separately for each sector. GENERAL ALGORITHMThe cost of transportation that we aim to mini-mize is the sum of:

the cost of transportation of the total mer-a) chandise of the sector from the production plant to the regional warehouse and

the cost of transportation of the merchan-b) dise from the intermediate warehouse to each retailer from the sectorThe transportation to the regional warehouse is operated by big capacity trucks, whereas the one from the regional warehouses to each retailer by small capacity trucks. Total Cost of Transportation = Cost (Production

plant Intermediate Warehouse) + Cost (Intermediate Warehouse Each Retailer)

The cost of transportation from the production plant to the intermediate warehouse is a func-tion of the number of kilometers between them, of the number of big trucks2 needed to transport the total quantity of merchandise of the sector and of the cost per kilometer for a big truck. Cost of Transportation Prod.Plant Intermed. Warehouse = (Nb. km3 Prod.Plant Intermed. Warehouse) X

2. By „big truck” we mean a truck with a high load capacity (often between 80 and 120 m3).3. Some abbreviations will be used in this section such as Nb. for «Number», Km for “Kilometer”, Intermed. for “Intermediate”, Prod. for “Produc-tion”, Ret. for “Retailer”, Transp. for “Transpor-tation”

(Nb. of necessary Big Trucks for total quantity of merchandise of the sector) X (Cost of transport per

km Big Truck) The cost of transportation from the intermedi-ate warehouse to each retailer of the sector it is the sum of costs of transportation of the quan-tity needed by each retailer from the regional warehouse. Each of these costs depend as well on the distance between the warehouse and the retailer, on the number of small trucks4 needed to transport the merchandise needed by that very retailer and on the cost per kilometer for a small truck.

Cost of Transportation=

]/ost)Re.[( ckKmSmallTruCcksNbSmallTrutailerWarehouseedNbKmInterm i ••→∑]/ost)Re.[( ckKmSmallTruCcksNbSmallTrutailerWarehouseedNbKmInterm i ••→∑

Intermed.Warehouse Retaileri

We can now write the minimization problem (equation 1) we have to solve as in Figure A.We can now find the city (among those where the retailers can be found) where, by locating the regional warehouse, the cost of transport would be minimal. Intuitively, the proper loca-tion will be the right compromise between dis-tances and quantities. Finding the city that by locating here the region-al platform we minimize the transportation cost means finding the city for which the above sum

4. By „small truck” we mean a truck with a low load capacity (often less than 40 m3)

is minimal.In order to facilitate the analysis, spreadsheets (Excel) will be used. We are going to propose an original design for the tables that will ease manipulation of data and will facilitate visuali-zation of results. We will start by building a square table like the one in figure3 with the cities (where the retailers of the region can be found) as header column and header row. Next, for each column, we will introduce the distances (fig.4) between each two cities. For instance, for the first column, where City1 and City2 (from the second row) meets we intro-duce the distance [km] between them. On the principle diagonal where Cityi meets Cityi, we will introduce instead of zero (which would be normally the distance between Cityi

and Cityi) the distance between the production site and Cityi. Now, for each column, adding the number of kilometers (in an additional row) we will obtain the total distance that would have to be traveled should the regional platform been located in the city staying in the column header. This can be easily understood (have a look to fig2 while read-ing the explanation). For instance, for the first col-umn (fig.4) with the header “City”1 we analyze the case in which City one is the location for the regional warehouse: in the first cell (which be-longs to the principal diagonal) we have the dis-

Fig.3 spreadsheet design


City 1 City 2 City 3 City 4

City 1

City 2

City 3

City 4


The cities where the retailers of the sector can be found. The proper lo-cation of the intermediate warehouse will be chosen among them.

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tance from the production plant to City 1 (the distance between the production site and the purported regional platform) and then in the second one the distance between city 1 and city 2 (i.e between the purported regional platform and the retailers in city 2) and then between city 1 and 3 and so on. By adding these distances, we obtain the total number of kilometers that have to be traveled in the sector should the regional warehouse be located in City 1. Then, we make the same calculation for each column (i.e. we calculate the total distance in each possible case of regional warehouse location). In the end, by comparing the total number of kilometers for each case, we can already see which the location of the platform is which minimizes the total dis-tance that has to be traveled.

As we can see, the analysis is done on column, that is, in each column we make a simulation by supposing the regional platform is located in the city which stays in the header of the column. The comparison is made below each column and the result can be easily visualized. However, as we have already shown (fig.1), the cost of transportation depends as well on the quantities that have to be transported. By divid-ing the quantities by the specific capacity of the truck that is going to carry them (i.e. big capacity trucks up to the regional warehouse, and smaller ones from the warehouse up to local retailers) we can get the number of trucks needed. According to the sum to be minimized presented in the beginning of this section (equation 1 and figure 1), we can calculate the cost of transportation as

showed in figure 5 by multiplying the number of kilometers with the number of trucks and the appropriate cost by kilometer. In order to do that, we are going to insert near each column in the table we used for calculat-ing the distances (fig.4), an additional column where we are now going to calculate not the costs of transport. It has to be kept in mind, on one hand, that the analysis is made by column (the same logic we used to compute the dis-tances) and, on the other hand, that in the cells near the principal diagonal the cost of transpor-tation from the production plant to the city in column/row header has to be introduced (there is an example in figure 6 for City 1).It is obvious that the cost per kilometer for a big and a small truck have to be previously calcu-lated as they enter the analysis as constants. As for the number of trucks needed it is advisable to previously build a table as the one in figure 6 and to link it to the table in figure5. Name of the city = Title (Column Min Total Cost)As we can see, the algorithm is easy to implement and its structure offers as well the possibility of computing the cost of distribution. By having the cost of distribution for an optimal distri-bution architecture with regional warehouses, a comparison with the cost of direct distribu-tion can be done and the choice concerning the proper distribution network can be made.tHe CAse oF A romAnIAn ComPAnY WItH A CountrY-WIDe DIstrIbutIon netWorKS* Foods5 is a Romanian company which devel-ops a production activity in the food branch. Its production plant is situated in Bucharest and it distributes its products all over Romania.The company has an internalized distribution function and its distribution network is divided in five sectors (demand concentration areas): Banat, Transylvania, Moldavia, Dobrogea and South Region with Bucharest.At present, the company has an intermediate-platform distribution network with a warehouse in every sector, except for the South Region (with Bucharest) where it went for a direct distribution. The actual platforms can be find in Timisoara (for Banat region), in Cluj (pour Transylvania region), in Bacau (for Moldavia re-gion) and in Constanta (for Dobrogea region).

5. The real name of the company as well as the brands of the products are not revealed because of issues of confidentiality. However, the data used for the analysis is real, coming from the account-ing management records of the company.

City 1 Cost City 1 [lei] City 2 City 3 City 4

City 1 NbKm Prod.Plant-> City 1

nbKm Prod.Plant -> City 1 Xnb big trucks needed to trans-port the entire quantity of goods demanded in the sectorX Cost/Km bigtruck

City 2 Nb Km City 1-> City 2 Nb Km City 1- City 2 xNb Small Trucks needed to trans-port the quantity needed in City 2X Cost /Km Small Truck

City 3 Nb Km City 1-> City 3 Nb Km City 1- City 3 XNb Small Trucks needed to trans-port the quantity needed in City 3X Cost /Km Small Truck

City 4 Nb Km City 1-> City 4 Nb Km City 1- City 4 XNb Small Trucks needed to trans-port the quantity needed in City 4X Cost /Km Small Truck

totAl Nb Total Km = total cost of transport if the regional platforme were placed in City 1

Fig.4 Introducing the variable of distance between destinations

Fig. 5 Computation of annual cost of transport for each possibility of regional platform location

total distance of transport [km] if the regional plateforme were placed in City 1

City 1 City 2 City 3 City 4

City 1 nb Km Prod.plant -> City 1

City 2 nb Km City 1->2

City 3 nb Km City 1->3

City 4 nb Km City 1->4

totAl =Total nb Km production plant-> retailers

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Keeping the actual repartition of the selling points in the five sectors yet defined by the company, the aim of this study is primarily to determine the optimal location for the inter-mediate warehouse in each region in order to minimize the distribution cost by using the algorithm proposed in section three. Secondly, by comparing the costs in the case of using intermediate warehouses and in the case of di-rect distribution a choice for the proper distri-bution network can be made. In the end some observations will be made regarding the dif-ferences between the actual and the proposed distribution architecture.The products are transported with standard boxes placed on europallets. A standard box is the count unit for the quantity to be trans-ported. Its standard dimensions (Eurobox) are 0,850m x 1,240m x 0,970m, that is 1m3. The big trucks that have been chosen have a capacity of 84m3 and the small ones of 42m3 or of 20m3.The algorithm is run using quantities sold in 2008 by the company in each city of the five sectors. As this company works in Just in Time ( JIT), the reduction of stocks comes as a pri-ority. Therefore, a new constraint will be in-

troduced in the general algorithm presented in section three, that is the need for daily distribu-tion to each selling point. This means that the quantities which are going to be introduced in the algorithm will be daily quantities instead of annual quantities. After running the data, the algorithm indicates the following locations for the warehouses(table 1). The analysis that was made pointed out that by further dividing the South Region (which is comparatively bigger than the others) and by placing in each new division an intermediate warehouse instead of using direct distribution (as the company does today) the cost of trans-port can be further lowered. An important observation would be that the appropriateness of the location of the plat-forms is kept in time as long as the repartition of sales within each sector stays the same. This hypothesis is weak and verifiable as the repar-tition of sales between selling points within a sector is directly influenced by population characteristics (such as for instance the popu-lation number or the purchasing power of the inhabitants) which are inelastic in short and medium run.

unDerstAnDIng WHen IntermeDIAte WAreHouses Are A beTTer solutIon tHAn DIreCt DIstrIbutIonThe results obtained in this case study have pointed out the relative efficiency of a distri-bution architecture using intermediate ware-houses compared to direct distribution so as to minimize the transportation costs. By analyzing the results, we can observe that the efficiency of using intermediate warehouses is high as long as the individual quantity which has to be distributed to each city of a geo-graphic sector does not allow its direct trans-port by big capacity trucks at a high loading rate. By contrast, if the merchandise that has to be transported to a specific city is large enough so as to be transported by large trucks at full capacity (or there is the possibility to wait until this happens), direct transport be-comes the optimal choice. ConClusIonToday companies have to optimize their re-source planning and use in order to gain com-petitiveness on global markets. Against this background, optimizing transport of goods is a must. The algorithm proposed in this paper al-lows for taking a decision between a direct and a distribution network using regional warehouses in order to minimize the costs of transporta-tion. Romanian companies have to keep up with the transformations of the logistic chain in the con-text of globalization and to start to conduct more accurate management accounting and feasibility studies in order to search for ways of optimizing the use of their resources. The European integra-tion offers great opportunities but it means as well stronger competition and thus the impera-tive need for optimization the use of resources.

sector location of intermediate warehouse (algorithm)

location of the real location of the intermediate warehouse

1 BANAT Caraş-Severin Timişoara



Direct distributionRegion Z1 Ploieşti

Region Z2 Slobozia

Region Z3 Buzău

4 MOLDAVIE Bacău Bacău

5 DOBROGEA Constanţa Constanţa


[1] MANEA C., Variables stratégiques dans l’emplacement des plateformes intermédiaires lo-gistiques, Bachelor’s Degree Thesis, Economics Studies Bucharest, 2009[2] MANEA A. T., MANEA L.C., Utilaje de transport rutier în zona portuară, Editura MatrixRom Bucureşti, 2004, ISBN 973-685-704-2. [3] SERRE, G., L’entrepôt dans la chaîne logis-tique d’un industriel de grande consommation, CGPC presentation, 2002.

Local warehouseQuantity to be transported to each

destination [number of standard boxes placed on pallets]

nb de camions nécessaires par destination

City 1 Quantity to be transported in city 1 Nb. SmallTrucks needed to transport the quantity demanded in city 1

City 2 Quantity to be transported in city 2 Nb. SmallTrucks needed to transport the quantity demanded in city 2

City 3 Quantity to be transported in city 3 Nb. SmallTrucks needed to transport the quantity demanded in city 3

City 4 Quantity to be transported in city 4 Nb. SmallTrucks needed to transport the quantity demanded in city 4

total Quantity of the secteur =total quantity to be transported in

the sector

nb. bigtrucks needed to transport the total quantity demanded in the sector

Fig. 6 table of repartition of the quantities between cities (retailers) within a sector

table 1 location of regional warehouses in each sector (algorithm)

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This scientific event has an international charac-ter and is addressed to all engineers and specia-lists interested in automotive, mechanical engine-ering, industrial engineering, mechatronics and economic engineering. Website of the event is: http://imtuoradea.ro/conf/Journal “Annals of Oradea THE UNIVERSITY. BEAM OF MANAGEMENT AND ENGINE-ERING Technological “, ISSN 1583 - 0691, pu-blishes the papers presented at this conference and is an engineering scientific publication of the Faculty for Managerial and Technological Engi-neering of the University from Oradea. Its first number appeared in 1991 and this year celebra-ted 20 years. Between the years 2004-2007, was accredited CNCSIS magazine in the “Class B” and from 2007 to the present is accredited CN-CSIS “Class B +”. In 2011, the event was held under the patrona-ge of: (SIAR), Society of Automotive Engineers of Romania, General Association of Romanian Engineers - Branch Bihor (AGIR) (ENCS) - Na-tional Authority for Scientific Research - Grant 2011, Reasearch Center “Production IMT-Ora-dea “, Reasearch Center in Mechanical Enginee-ring and Automotive” IMA “Oradea, Romanian Association for Non-Conventional Technologies - Branch Bihor (ARTN)mAIn tHemes engIneerIng oF AutomotIVe AnD tRAnsPorts: New solutions for automoti-

ve engines, automotive and the environment, transport systems and advanced traffic, advanced manufacturing methods for automotive, new ma-terials, logistics and manufacturing technologies for automotive meCHAnICs: Mechanics, Strength of Materi-als, Mechanical Vibrations, Numerical Methods, Applied Mathematics, machinery and equip-ments meCHAtronICs: Industrial robots, Mecha-nisms, Machine, Fine Mechanics, Tribology, sen-sors, AI, pneumatic and hydraulic systems mAnuFACturIng engIneerIng: Te-chniques CAD / CAM, flexible and integrated systems, materials, unconventional technologies, CNC Technologies mAnAgement AnD eConomIC engI-neerIng: Management of production syste-ms, human resources, marketing, quality engine-ering, industrial logistics and material planning, risk management, knowledge management total number of scientific papers published: 245 PLENARY SESSION 1. Matúš Duňa, Marek Miško, High preci-sion gearboxes by SPINEA, SPINEA s.r.o. COMPANY, Prešov, Slovakia. 2. Ciolofan Constantin, Integrated CAD / CAM / CAE / PLM Last Generation Program System, INAS SA Romania 3. Gheorghe Florea, VERSAROLL system - applied to the assembly lines of au-tomotive body, COMAU Romania. 4. John

Lucaciu Mircea Burca, RESEARCH ON THE DEVELOPMENT OF HETERO GE NEOUS MATERIALS WELDING TECHNO LOGY, University of Oradea. 5.Florin Blaga, Julian Stănăşel, Calin Baban, Marius Baban - Developing the skills of concurrent engineering, University of Oradea.Of the over 330 authors and co-authors of papers accepted for publication, the thermal resort hotel Felix Bale attended 117 participants from Romania and 22 from abroad, most from Hungary, but also from Spain, Slovakia and Serbia. In terms of edu-cational institutions at the event were represented 14 universities from Romania and 6 from abroad. Economic media were less represented than in previous years, being present only eight compa-nies from Romania and one from abroad.At the end of the two days one could say that this annual meeting had a high scientific level, the lar-ge number of participants showing real interest for this event. The purpose was achieved, gene-rating and ensuring the conditions for the dis-semination and information transmission of the research results in areas that were the subject of the five sections.Next year, during May 31st-June 15t, 2012 will take place the event „IMT-Oradea 2012“, editi-on 21, under the coordination of the Faculty for Managerial and Technological Engineering in Spa Felix, Hotel. The conference will include the same sections as the previous edition.

ANNUAL SESSION OF SCIENTIFIC PAPERS „IMT ORADEA – 2011”Oradea, Felix Spa, May 26-28th, 2011

Images of the place and the manner of operation of scientific session

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The laboratory for performances certification of electro-hydraulic amplifiersUniversity Politehnica of Bucharest

Laboratory accredited by RENAR LI 821/2009; SR EN ISO 9001:2008b Certificated

Destination: Certification of static and dynamic of electro-hydraulic servoval-ves performances, propor-tional distribuitors, pro-portional valves; static and dynamic testing for high

speed electro-hydraulic servomechanisms of dy-namic stress simulators, adaptive servo-steering for road vehicles, hydraulic shock-absorbers, ABS, ESP systems, electromagnetic and piezoke-ramic injectors etc.Permanent collaborations:- Platform of Road Vehicles in UPB;- Renault Technologie Roumanie;- INOE hydraulic and pneumatic Institute;- Hidroelectrica SA, Termoelectrica SA, Rompetrol;- Parker Hannifin Romania, CEROB, Hidraulica Brasov, HESPER SA, BOSCH-REXROTH RO ;- National Instruments, LMS International, Filiala BV- ICPE-ACTEL SA, AEROTECH SA, ROMET BUZAU.Director : Prof.dr.eng. Nicolae Vasiliu

[email protected]://www.fluid-power.pub.ro/

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University Research

Project HURO/0901/258/2.2.2, Project title: Research on engines in a single regime running

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Calderon Branch, Account RO38BRDE410SV18417414100 (SWIFT BIC: BRDEROBU).

lead Partner: University of OradeaProject manager: Conf. Dr. Ing. CHIOREANU Nicolae, University of Oradea expert’s team: Conf. dr. ing. Chioreanu Nicolae, Prof. dr. ing. Antal Cornel, Prof. dr. ing. Băban Călin, Prof. dr. ing. Pop Mircea, Prof. dr. ing. Rus Alexandru, Conf. dr. ing. Mitran Tudor, Conf. dr. ing. Nemţanu Marius, Conf. dr. ing. Vesselenyi Tiberiu, Ş.l. dr. ing. Beleş Horia, Ş.l. dr. ing. Dragomir George, Ş.l. dr. ing. Fântână Nicolae, Ş.l. Dr. ing. Spoială Viorica, Ş.l. dr. ing. Şchiop Adrian, ing. Crăciun Dan, Prep. Ardelean FelicianPartner. Szent Istvan University, Gödöllõ, Ungariageneral objective: Knowledge and skills on design and manufacture of en-gines (thermal and electrical) running in a single regime. The study of the

possibility to use these engines for cars propulsion systems.General presentation: Overall objective of the project is to implement the economic cycle of new types of engines. The new engines represent an ab-solute novelty and are characterized by the following features: running in a single regime (monoregim); without moment’s idle running. The following advantages are estimated :(compared to the nowadays internal combustion engine or electric motors): less fuel or electrical energy consumption and lower polluting emissions (it is much easier to optimize a single regime to an infinite as current production engines), simple construction, and good viability. Also, the monoregim engine can assume, totally or partially.Contact: E-mail: [email protected].

Electronic counter set is the result of collaboration between Technical University of Cluj-Napoca and Cerberus Company Soft.It is intended to carry out surveys of traffic activity that so far, in the coun-try, has been made only manually by operators, thus requiring a large num-ber of people engaged in this activity. The presented equipment is patented and registered under OSIM no. 019017/26.02.2010. technical specs: Dimensions: 220x120x65 mm, - weight: 640g; Power source: 4 AA of 2500mA battery, charger fit to national power grid; Internal memory: 1Gb; Range of working temperature: - 10 - 80 °C (no condensa-tion); number of recorded moving directions: 12; number of vehicle cat-egories: 8; connectivity: USB; autonomy: 36 de ore.

Working conditions: Electronic traffic counter is portable electronic equipment, dedicated exclusively to carrying out traffic surveys. In order to simplify the text and speech, it will be mentioned throughout this document and the software under the generic name „Palm”. In terms of the degree of mechanical and electrical safety, traffic counter is within the standard IP52. For prolonged use, the device will be protected from mechanical shock and exposure to damp and will not be allowed subject to direct solar radiation for a long time. Electronic traffic counter is portable electronic equipment, dedicated exclusively to carrying out traffic surveys. Powering with electric energy of the traffic counter is achieved through Ni-MH of 2500mAh, User interface, data transfer and other information’s on exploitation of rte electronic counter: Contact Nicolae Filip.utcluj.ro

Authors: Prof. univ. dr.eng. Gheorghe Amza, Lecturer Eng. Zoia ApostolescuThe work includes technology to achieve optimal intelligent taillights and smart bars used in construction vehicles using near-field ultrasonic welding. It makes a comparative analysis quality / price of several welding proce-

dures to be applied resulting in the possible optimal method - ultrasonic welding. Welding operation is performed with an ultrasonic welding torch original design.Contact: Prof. Univ. dr. eng. Gheorghe Amza, [email protected]

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Ingineria Automobilului

CHAllenge Kart loW-Cost. WHAt Does It meAn?Developing of a kart over one academic year, whose cost is not to exceed 2000 €, aiming to participating in May to a motor-sport academic competition.This project underlines the basic competences of an engineer, such as:

Teamwork/organization of a team in such way that deadlines are to be re-spected,Capability to select engineering solu-tions, having constraints of budget and time,Ingeniousness, etc.

Therefore, it’s not just a simple go-karting race. Equally, it’s a technological, educational and hu-man challenge and the winner is not necessarily the fastest!CHAllenge Kart loW-Cost. For WHom?This competition, whose aim is to develop a so-called “low-cost” by multidisciplinary student teams, is opened to anyone concerned by the automotive engineeringThe students are gathered in teams and over one academic year, they follow the development stages of a product, so that in the end the motor-sport competition to be possible.In 2011, the competition took place on a track of the many presented on the former site of France’s F1 Grand Prix at Magny-Cours (F-58) and the competitors were: Institut supérieur de l’Automobile et des transports de Nevers from the University of Bourgogne (one team) and University of Pitesti (two teams) - http://www.upitmedia.ro/index.php/unctr/universitatea-din-piteti-la-kart-low-cost-challenge.htmlCHAllenge Kart loW-Cost. goAls

Learning/exercising of all stages of a product’s development (design, manu-facturing, etc)

Understanding the problems that occur from the need to obtain an optimal oper-ational product, as a result of a coherent compromise, corresponding to precise technical specifications,Encouraging the innovation by impos-ing of a permissive technical regulation, leaving a great freedom of design, thus allowing students the development and application of their ideas,Development of a product, respecting the constraints of budget and time,Development of competing spirit amongst students,Encouraging students to seek out for complementary competences, allowing them to open their minds, which is indis-pensable for the future professional life,Introduction of students in a frame which encourages reflection toward what

the automotive engineering really means and which allows opinions exchanges with people from different nationalities aiming also to create a cultural exchange.

Briefly, the goal of this competition is to prepare future engineers for project management by de-veloping the teamwork spirit, sharing responsi-bilities, respecting deadlines and allocated bud-get; finally, it aims to develop the synthesis and compromise capabilities in respect to the initial imposed constrains.CHAllenge Kart loW-Cost. ProJeCt eVAluAtIon

Analysis of the expenses (≤ 2000 €),Analysis of the kart’s body design,Dynamic tests, allowing to evaluate the kart’s dynamics as well as its accelera-tion,Endurance test (60 laps) in order to ana-lyze the kart’s reliability.

Challenge Kart low-Cost. 2012 editionFollowing an agreement in progress of be-ing validated, between Renault Romania and University of Pitesti, the next edition will be or-ganized on test tracks of Renault – Dacia from Merisani Arges.In 2012, taking into account the current orienta-tion of the automotive industry, ISAT de Nevers, the author of this competition, decided to intro-duce another challenge, the electric propulsion; thus, there will be two competitions: one with thermal powered karts and another one with electrical powered karts.Therefore, Romanian universities having Automotive Engineering specialization are in-vited to be part of.

Participation of students from University of Piteşti at Challenge KART LOW COST,a result of a good collaboration with University of Bourgogne,

ISAT of Nevers, France

Adrian ClenCIUniversitatea din PiteştiDepartamentul Automobile ernest gAlInDoUniversité de BourgogneInstitut Supérieur de l’Automobile et des Transp.


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Series of Lectures at theUniversity of Bra ovUniversity of Bra ov

Beginning with May 2011 the University Transylvania organizes, at regular intervals,a series of technical lectures together with Schaeffler Technologies GmbH & Co. KGand with other renowned partners from the automotive community.

Leaders Leaders ofof the automotive the automotive science and industry presentscience and industry present

Leaders Leaders ofof the automotive the automotive science and industry presentscience and industry present

The series of technical lectures will be continued in the academic yearof 2011/2012. The conferences for 2011 are scheduled at the beginning of October, November and December respectively.


y py py py p

Our speakers are:

Dr.-Ing. Kurt Kirsten,Vicepresident of Schaeffler Group Automotive, Herzogenaurach / GermanyPartners

Prof. Dr.-Ing Adrian Rienäcker and Prof. em. Dr.-Ing. Günter KnollUnversity of Kassel / Germany

Prof. Dr.-Ing. Giovanni CipollaUniversity of Torino / Italy, former head of engine development at Ferrari in Maranello

The speakers will present new concepts for the development of future mobility, as well as possibilities for tribological improvements in the

propulsion systems of road vehicles.

The lectures will be video transmitted in real-time to the Technical University of Cluj Napoca and theTechnical University of Cluj-Napoca and the

Technical University "Gheorghe Asachi" of Ia i.

Conference dates and subjects will be announced two weeksprior to each event.

We are looking forward to meeting you!WestsächsischeHochschule Zwickau

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auto test 3