A 3cell =

− 1Rccc

1Rccc

0 0 0 01

Rccs−( 1

Rccs+ 1

Rucs+ 1

Rcccs) 0 1

Rcccs0 0

0 0 − 1Rccc

1Rccc

0 00 1

Ru2c f cs

+ 1Rcccs

1Rccs

−( 1Rucs

+ 1Rccs

+ 2Rcccs

) 0 1Rcccs

0 0 0 0 − 1Rccc

1Rccc

0 1R2

uc f cs(1− 1

Ruc f) 0 1

Ru2c f cs

+ 1Rcccs

1Rccc

−( 1Rccs

+ 1Rucs

+ 1Rcccs

).

(20)

Figure 11. OBSERVABILITY OF THE SAME SENSOR LOCATIONSUNDER DIFFERENT CONDITIONS

Table 3. NUMBER OF SENSOR POSITION COMBINATIONS GIVINGFULL OBSERVABILITY FOR A STRING WITH 12 CELLS AND 4 SEN-SORS

Conditions No. of combinations

giving full observability

Full interconnection 106/495

Natural convection 52/495

No cell to cell conduction 1/495

ditions under different scenarios, and the conclusion is summa-rized in Table 3. The minimum number of sensors that gives fullobservability is 4.

As shown in Table 3, among all the 495 combinations of4 sensor locations in a cell string of 12, if there is both circu-lated coolant convection and cell to cell conduction, referred toas full interconnection in Table 3, 106 combinations will givefull observability. Under natural convection, where the coolantis not flowing between cells, only 52 combinations can satisfy

full observability condition. When the cell to cell conduction ismissing, only 1 combination yields full observability. That com-bination would be placing the sensors at the 3th, 6th, 9th and12th cells. The sensors are actually evenly distributed along thecluster, which agrees with intuition.

Of the two modeled thermal interconnections between cells,namely the cell to cell heat conduction and the heat convectionthrough the coolant flow, the former tends to have larger impacton the observability of the pack model. This may be related tothe fact that the cell to cell heat conduction is a two-way inter-action, where the two adjacent cells can transfer heat betweeneach other. But the heat convection through the coolant flow issingle directional, and only the previous cells along the coolantflow direction will affect the latter ones.

Consequently, greater cell to cell heat conduction will be fa-vored by the observability of the pack model. It is noted thatgreat cell to cell heat conduction can also reduce the temperaturegradient between cells in the pack and thus help contain the im-balance between cells induced by temperature non-uniformity.However, on the negative side, in case of a single cell thermalfailure, e.g. local overheating, the great cell to cell heat conduc-tion will facilitate the spread of such failure to other cells in thepack. This is not desirable from the safety perspective.

8 ConclusionIn this paper, an online parameterization methodology for a

lumped thermal model of a cylindrical lithium ion battery cellhas been proposed, designed and verified by simulation. By us-ing online parameterization algorithm, the lumped parameters ofthe thermal model, which cannot be easily measured or calcu-lated otherwise, can be automatically identified based on the cur-rent excitation of a real drive cycle and the resultant battery sur-face temperatures. The identified parameters and the measuredcell surface temperature are adopted by an adaptive observer toestimate the unmeasurable core temperature of the cell. The esti-mated core temperature can be used as a more useful and criticalreference for the on-board thermal management system and eventhe vehicle power management system. The next step will be tovalidate the model and the methodology with experiments. Overthe battery lifetime, such online identification scheme can be re-set on a monthly or yearly basis to track varying parameters due

A 3cell =

− 1Rccc

1Rccc

0 0 0 01

Rccs−( 1

Rccs+ 1

Rucs+ 1

Rcccs) 0 1

Rcccs0 0

0 0 − 1Rccc

1Rccc

0 00 1

Ru2c f cs

+ 1Rcccs

1Rccs

−( 1Rucs

+ 1Rccs

+ 2Rcccs

) 0 1Rcccs

0 0 0 0 − 1Rccc

1Rccc

0 1R2

uc f cs(1− 1

Ruc f) 0 1

Ru2c f cs

+ 1Rcccs

1Rccc

−( 1Rccs

+ 1Rucs

+ 1Rcccs

).

(20)

Figure 11. OBSERVABILITY OF THE SAME SENSOR LOCATIONSUNDER DIFFERENT CONDITIONS

Table 3. NUMBER OF SENSOR POSITION COMBINATIONS GIVINGFULL OBSERVABILITY FOR A STRING WITH 12 CELLS AND 4 SEN-SORS

Conditions No. of combinations

giving full observability

Full interconnection 106/495

Natural convection 52/495

No cell to cell conduction 1/495

ditions under different scenarios, and the conclusion is summa-rized in Table 3. The minimum number of sensors that gives fullobservability is 4.

As shown in Table 3, among all the 495 combinations of4 sensor locations in a cell string of 12, if there is both circu-lated coolant convection and cell to cell conduction, referred toas full interconnection in Table 3, 106 combinations will givefull observability. Under natural convection, where the coolantis not flowing between cells, only 52 combinations can satisfy

full observability condition. When the cell to cell conduction ismissing, only 1 combination yields full observability. That com-bination would be placing the sensors at the 3th, 6th, 9th and12th cells. The sensors are actually evenly distributed along thecluster, which agrees with intuition.

Of the two modeled thermal interconnections between cells,namely the cell to cell heat conduction and the heat convectionthrough the coolant flow, the former tends to have larger impacton the observability of the pack model. This may be related tothe fact that the cell to cell heat conduction is a two-way inter-action, where the two adjacent cells can transfer heat betweeneach other. But the heat convection through the coolant flow issingle directional, and only the previous cells along the coolantflow direction will affect the latter ones.

Consequently, greater cell to cell heat conduction will be fa-vored by the observability of the pack model. It is noted thatgreat cell to cell heat conduction can also reduce the temperaturegradient between cells in the pack and thus help contain the im-balance between cells induced by temperature non-uniformity.However, on the negative side, in case of a single cell thermalfailure, e.g. local overheating, the great cell to cell heat conduc-tion will facilitate the spread of such failure to other cells in thepack. This is not desirable from the safety perspective.

8 ConclusionIn this paper, an online parameterization methodology for a

lumped thermal model of a cylindrical lithium ion battery cellhas been proposed, designed and verified by simulation. By us-ing online parameterization algorithm, the lumped parameters ofthe thermal model, which cannot be easily measured or calcu-lated otherwise, can be automatically identified based on the cur-rent excitation of a real drive cycle and the resultant battery sur-face temperatures. The identified parameters and the measuredcell surface temperature are adopted by an adaptive observer toestimate the unmeasurable core temperature of the cell. The esti-mated core temperature can be used as a more useful and criticalreference for the on-board thermal management system and eventhe vehicle power management system. The next step will be tovalidate the model and the methodology with experiments. Overthe battery lifetime, such online identification scheme can be re-set on a monthly or yearly basis to track varying parameters due

In accordance with Cooperative Agreement W56HZV-04-2-0001

U.S. Army Tank Automotive Research, Development and Engineering Center (TARDEC)

8:00 Welcome & IntroductionsProf. Anna Stefanopoulou, ARC DirectorDr. Stephen Forrest, VP for Research, University of Michigan

8:20 Plenary SessionIntroductions by Dr. David Gorsich, Chief Scientist, U.S. Army TARDECDistinguished Speakers

Dr. Grace Bochenek, Chief Technology Officer, U.S. Army Materiel CommandDr. Scott Fish, Chief Scientist, U.S. ArmyMr. Gary Rogers, President & CEO, FEV, Inc.Mr. Craig Savonen, Director, Engine Product Engineering, Daimler Trucks

Break

10:30 Case Study Presentations• Enabling Integrated Powertrain Experiments in Networked Labs• Reliability-Based Design Optimizations (I-RBDO) Code & Applications

12:00 Lunch

1:30 Technical Symposium 1 with parallel sessions1A: JP-8 Studies, IC Engines 1B: Thermal Dynamics & Hybrid Powertrains1C: Design/V&V/Reliability

3:30 Poster Session / Tour of Autolab experimental facilities

Day 1: Monday, May 21, 2012

8:00 WelcomeProf. Dawn Tilbury, ARC Deputy DirectorMr. David Thomas, Director, National Automotive Center

8:10 Plenary SessionIntroduction by Mr. David Thomas, Director, National Automotive CenterDistinguished Speaker

Dr. Arun Majumdar, Director ARPA-E, Department of EnergyPanel on “Diverging Future of Automotive Systems in Civilian and Military

Vehicle Applications”Dr. Peter Schihl, Senior Technology Expert (GVPM), U.S. Army TARDEC Mr. Kyle Kimel, President and CEO, AVL Test Systems Inc.Dr. Matthew Brusstar, Director, Advanced Powertrain Center, U.S. E.P.A.Dr. Emilio E. Bunel, Director, Chem. Sc. and Eng. Div., Argonne Natl. Lab.Prof. Huei Peng, U.S. Director, Clean Energy Research CenterDr. Matthew Reed, Head Biosciences Group, UMTRI

Break

10:00 Technical Symposium 2 with parallel sessions2A: Mobility/Terramechanics 2B: Electrified Powertrains: Design & Characterization2C: Survivability/Reliability

12:00 Lunch

1:30-3:30 Poster Session

Day 2: Tuesday, May 22, 2012

Organized by theAutomotive Research Center

A U.S. Army Center of Excellence for Modelingand Simulation of Ground Vehicles

College of Engineering

This event is free of charge. Register at

arc.engin.umich.eduInquiries

(734) 764-6579arc-conference-inquiries@umich.edu

Venue

Penny and Roe Stamps AuditoriumNorth Campus

The University of Michigan1226 Murfin Ave.

Ann Arbor, MI 48109

18th Automotive Research Center ConferenceMay 21-22, 2012 Powering Future Mobility

18TH ANNUAL AUTOMOTIVE RESEARCH CENTER CONFERENCE

Computer Science Engineering Building / Bob and Betty Beyster Building : CSE Herbert H. Dow Building : Dow

Walter E. Lay Automotive Engineering Laboratory : Auto Lab

POWERING FUTURE MOBILITY

MAY 21ST, DAY 1 PROGRAM

7:30 – 8:00 CHECK-IN AND BREAKFAST Stamps Auditorium

8:00 – 8:15 WELCOME & OPENING REMARKS Stamps Auditorium

Prof. Anna Stefanopoulou, Director, Automotive Research Center

Prof. Stephen Forrest, Vice President for Research, University of Michigan 8:15 – 9:50 PLENARY SESSION Stamps Auditorium

Introductions

Dr. David Gorsich, Chief Scientist, U.S. Army TARDEC

Distinguished Speakers

Dr. Grace Bochenek, Chief Technology Officer, U.S. Army Materiel Command

Dr. Scott Fish, Chief Scientist, U.S. Army

Mr. Gary Rogers, President & CEO, FEV, Inc.

Mr. Craig Savonen, Director, Engine Product Engineering, Daimler Trucks NAFTA

Question & Answer session

9:50 – 10:00 Group Photo Outside

10:00 – 10:30 BREAK Stamps Auditorium

10:30 – 12:00

CASE STUDY SESSION Stamps Auditorium

1. Enabling Integrated Powertrain Experiments in Networked Distributed Laboratories

2. Reliability-Based Design Optimizations Code and Its Applications

12:00 – 1:30 LUNCH Pierpont Commons

1:30 – 3:30 TECHNICAL SYMPOSIUM 1 – Parallel Sessions (see enclosed matrix) CSE / Dow

1A: JP-8 Studies, IC Engines CSE 1670

1B: Thermal Dynamics & Hybrid Powertrains CSE 1690

1C: Design/V&V/Reliability DOW 1013

3:30 – 5:30 POSTER SESSION & LAB TOURS CSE / Auto Lab

18TH ANNUAL AUTOMOTIVE RESEARCH CENTER CONFERENCE

Computer Science Engineering Building / Bob and Betty Beyster Building : CSE Herbert H. Dow Building : Dow

Walter E. Lay Automotive Engineering Laboratory : Auto Lab

POWERING FUTURE MOBILITY MAY 22ND, DAY 2 PROGRAM

7:30 – 8:00 BREAKFAST Stamps Auditorium

8:00 – 8:05

WELCOME Stamps Auditorium

Prof. Dawn Tilbury, Deputy Director, Automotive Research Center

8:05 – 9:30 PLENARY SESSION Stamps Auditorium

Introductions & Moderator

Mr. David Thomas, Director, National Automotive Center

Distinguished Speaker

Dr. Arun Majumdar, Director ARPA-E, Department of Energy “Catalyzing Energy Breakthroughs for a Secure American Future”

Panel Discussion

“Diverging Future of Automotive Systems in Civilian and Military Vehicle Applications”

Dr. Peter Schihl, Senior Technology Expert (GVPM), U.S. Army TARDEC

Mr. Kyle Kimel, President and CEO, AVL Test Systems Inc.

Dr. Matthew Brusstar, Director, Advanced Powertrain Center, U.S. Environmental Protection Agency

Dr. Emilio Bunel, Director, Chemical Science and Engineering Division, Argonne National Laboratory

Prof. Huei Peng, US Director, US - China Clean Energy Research Center - Clean Vehicle Consortium Dr. Matthew Reed, Head Biosciences Group, University of Michigan Transportation Research Institute

Mr. Eric Hausman, Project Manager, University of Michigan Solar Car Team

9:30 – 10:00 BREAK CSE / Dow

10:00 – 12:00 TECHNICAL SYMPOSIUM 2 – Parallel Sessions (see enclosed matrix) CSE / Dow

2A: Mobility/Terramechanics CSE 1670

2B: Electrified Powertrains: Design & Characterization CSE 1690

2C: Survivability/Reliability Dow 1013

12:00 – 1:30 LUNCH CSE

1:30 – 3:30 POSTER SESSION CSE

18TH ANNUAL AUTOMOTIVE RESEARCH CENTER CONFERENCE      

 

SPEAKER  INFORMATION  

DR.   SCOTT   FISH   is   the   Chief   Scientist   of   the   U.S.   Army.     He   serves   as   the   chief   scientific  advisor  to  Senior  Army  Leadership,  and  provides  assessments  on  a  wide  range  of  scientific  and   technical   issues   affecting   the   Army  mission.     In   this   role   he   identifies   and   analyzes  technical   issues   and   brings   them   to   the   attention   of   Army   Leaders,   and   interacts   with  operational  commanders,  combatant  commands,  acquisition,  and  science  and  technology  communities   to  address   cross-­‐organizational   technical   issues  and   solutions.    He   interacts  with   other   services   and   the   Office   of   the   Secretary   of   Defense   along   with   the   Deputy  Assistant   Secretary   for   Research   and   Technology   on   issues   affecting   the   Army   in-­‐house  

technical  enterprise.    He  is  also  the  principal  science  and  technology  representative  of  the  Army  to  the  civilian  scientific  and  engineering  community  and  to  the  public  at  large.  

Dr.  Fish  is  on  leave  of  absence  from  the  University  of  Texas  at  Austin,  where  he  was  the  Director  of  the  Institute  for   Advanced   Technology,   specializing   in   hypervelocity   physics,   electrodynamics,   and   pulsed   power   systems  integration.    He  has  served  as  an  Assistant  Vice  President   for  Technology  at  Science  Applications   International  Corporation,  and   lead  programs   in   large-­‐scale   robotics  and   intelligent  systems  while  at   the  Defense  Advanced  Research   Projects   Agency.     Dr.   Fish   started   his   career   with   the   Naval   Surface   Warfare   Center   conducting  research  in  a  wide  range  of  fluid  mechanics  areas  from  torpedo  launch  to  ship  wake  signature  reduction  as  well  as  ship  system  integration  associated  with  high  power  electrical  weapons.    

DR.  GRACE  BOCHENEK   is   the   first  Chief  Technology  Officer   (CTO)   for   the  U.S.  Army  Materiel  Command  (AMC),  which  is  the  lead  agency  for  development,  delivery,  and  sustainment  of  materiel  to  ensure  a  dominant  joint  force  for  the  United  States  and  its  Allies.  A  2008  recipient  of  the  Meritorious  Executive  Presidential  Rank  Award  and  member  of  the  Senior   Executive   service,   Dr.   Bochenek   brings  more   than   25   years   of   scientific,   technical  and  managerial  experience  to  the  CTO  role.    Dr.  Bochenek  serves  as  the  senior  civilian  authority  for  science,  technology  and  engineering  with   responsibility   for   developing   and   executing   a   long-­‐term   research,   development,  

technology   and  engineering   transformation   and  organizational   realignment   and   restructuring.   In   this   role,  Dr.  Bochenek   establishes   the   technical   vision   and   leads   all   aspects   of   AMC   technology   development,   sets   the  strategic  direction  for  a  full  range  of  Army  systems  investments  and  drives  strategic  alignment  with  the  Assistant  Secretary   of   the   Army   for   Acquisition,   Logistics   and   Technology   and   the   U.S.   Army   Training   and   Doctrine  Command   to   ensure   rapid   and   responsive   delivery   of   products.   Additionally,   she   leads   the   execution   of   the  technology   strategy   for   platforms,   partnerships   and   external   relationships   and   provides   technical   advice,  guidance  and  recommendations  that  form  the  basis  for  high  level  policy  and  management  decisions.      Prior   to   this   assignment   Dr.   Bochenek   served   as   Director   of   the   U.S.   Army’s   Tank   Automotive   Research,  Development  and  Engineering  Center  (TARDEC),  the  premier  Army  laboratory  for  advanced  military  automotive  technology   for   ground   vehicle   systems   and   logistics   support   equipment.   As   Director   she   created   and   led   all  research,  development  and  engineering  strategies  for  the  Department  of  Defense’s  ground  vehicle  manned  and  unmanned  systems  with  military  impact  worldwide.  She  has  also  held  the  positions  of  Deputy  Program  Executive  Officer   for   Program  Executive  Office  Combat   Support   and  Combat   Service   Support   and  Executive  Director   for  Research  and  Technical  Director  at  TARDEC.    Bochenek   has   a   B.S.   in   electrical   engineering   from  Wayne   State   University,   an  M.S.   in   engineering   from   the  University  of  Michigan  and  a  Ph.D.  in  Industrial  Systems  Engineering  from  the  University  of  Central  Florida.      

18TH ANNUAL AUTOMOTIVE RESEARCH CENTER CONFERENCE      

   

MR.   GARY   ROGERS   is   President   and   Chief   Executive   Officer,   FEV,   Inc.,   and   Executive   Vice  President   (Geschäftsführer),   FEV   Motorentechnik,   GmbH.   Hi   s   previous   positions   have  included:  Director,  Power  Plant  Engineering  Services  Division  and  Senior  Analytical  Engineer,  Failure   Analysis   Associates,   Inc.;   Design   Development   Engineer,   Garrett   Turbine   Engine  Company;  and  Exploration  Geophysicist,  Shell  Oil  Company.  He  has  extensive  experience  in  research,  design,  and  development  of  advanced  engine  and  power   systems   including   homogeneous   and   direct   injected   gasoline   engines,   high   speed  direct   injection   (HSDI)   passenger   car   diesel   engines,   heavy-­‐duty   diesel   engines,   hybrid  

vehicle   systems,   gas   turbines,   pumps   and   compressors.   He   has   also   directed   both   research   and   production  development   of   engines   and   power   systems   utilizing   renewable   and   alternative   fuels   including   ethanol,  methanol,   biodiesel,   Fischer-­‐Tropsch-­‐derived   and   gaseous   fuels.   He   provides   corporate   leadership   for   a  multinational  research,  design  and  development  organization  specializing  in  engines  and  energy  systems.  Mr.   Rogers   is   a  member   the   American   Society   of  Mechanical   Engineers   and   a   Fellow   Grade  Member   of   the  Society   of  Automotive   Engineers   (SAE).  He   sits   on   the   Executive  Management   Committee  which   founded   the  SAE  North  American  International  Powertrain  Conference.  He  also  serves  as  a  member  of  the  Advisory  Board  to  the  College  of  Engineering  and  Computer  Science,  Oakland  University,  Rochester,  Michigan  and  is  a  member  of  the  President’s  Advisory  Board  of  Clemson  University.  He  has  served  as  a  member  of  several  committees  under  the  National  Academy  of  Sciences  including:  National  Research  Council  (NRC)  Committee  on  Program  Review  of  DOE’s  Office  of  Heavy  Vehicle  Technologies;  the  NRC  Committee   on   the   Effectiveness   and   Impact   of   Corporate   Average   Fuel   Economy   (CAFE)   Standards;   the   NRC  Panel   on   Benefits   of   DOE’s   Light-­‐Duty   Hybrid   Vehicle   R&D   Program;   the  NRC   Committee   evaluating   the   21st  Century  Truck  Partnership;  the  NRC  Fuel  Economy  of  Light  Duty  Vehicles  Committee  and  previously  supported  the   Department   of   Transportation,   National   Highway   Traffic   Safety   Administration   as   a   peer   reviewer   of   the  NHTSA  CAFE  Model.  Mr.  Rogers  currently  serves  as  a  member  of  the  National  Academies  Board  on  Energy  and  Environmental  Systems.  He   earned   a   Master   of   Engineering   (Mechanical),   University   of   Colorado;   a   B.S.M.E.   from   Northern   Arizona  University   and   received   his   Professional   Engineer   registration   in   Mechanical   Engineering   from   the   State   of  Arizona.    

MR.   CRAIG   L.   SAVONEN   is   the   Director   of   Performance   and   Emissions,   Engine   Product  Engineering   at   Daimler   Trucks   NAFTA.     Savonen   began   his   career   in   1984   as   a   technology  engineer   within   the   Technology   &   Planning   Department   of   GM-­‐Detroit   Diesel   Allison,  developing   his   expertise   in   Thermodynamics,   Combustion,   and   Emissions   development.    Along  the  way,  he  led  model  enhancements  and  applications  of  analytical  tool  sets  including  cycle   simulation,   3D   fluid   flow   and   combustion   analysis   tools   within   the   industrial  environment.     In   the   late  1980’s,  he   led  a   team  to   the   first  officially   certified  alternate   fuel  

(methanol)  heavy  duty  engine.    As  technology  group  manager  within  the  Advanced  Engineering  team  of  Detroit  Diesel   (Penske  and  then  DaimlerChrysler  parent  companies),  he  was  a  key  contributor   to   the  advancement  of  engine  controls  and  fuel  economy  in  long  haul  heavy  duty  vehicles,  including  the  Series  60  engine  family.    During  this  timeframe,  Savonen  also  managed  several  US  DOD  and  DOE  sponsored  pre-­‐development  programs.    In  2001,  Savonen   transitioned   to  manager   of   final   product   development   of   fuel   injection   systems   and   engine   system  controls  for  the  new  DD13,  DD15,  and  DD16  global  engine  families  now  produced  under  the  Detroit  brand  for  Daimler  Trucks  North  America.    Since  2009,  he  has  been  director  of  the  Performance  and  Emission  Department,  which   includes   NAFTA   responsibilities   for   engine/powertrain   product   development   for   performance,   fuel  economy,   and   emissions,   and   elements   of   OBD   compliance,   as   well   as   low   and   high   pressure   fuel   system  hardware   and   software.     Multi-­‐functional   engineering   vehicle   testing   complement   this   span   of   product  validation  responsibility.    Savonen  received  his  MSME  degree  from  Michigan  Tech  in  1984.  

18TH ANNUAL AUTOMOTIVE RESEARCH CENTER CONFERENCE      

   

DR.   ARUN   MAJUMDAR     became   the   first   Director   of   the   Advanced   Research   Projects  Agency  -­‐  Energy  (ARPA-­‐E),  the  country's  only  agency  devoted  to  transformational  energy  research  and  development,  in  October  2009.    Prior  to  joining  ARPA-­‐E,  Dr.  Majumdar  was  the  Associate  Laboratory  Director  for  Energy  and   Environment   at   Lawrence   Berkeley   National   Laboratory   and   a   Professor   of  Mechanical   Engineering   and   Materials   Science   and   Engineering   at   the   University   of  California,   Berkeley.   His   highly   distinguished   research   career   includes   the   science   and  engineering   of   energy   conversion,   transport,   and   storage   ranging   from  molecular   and  nanoscale  level  to  large  energy  systems.  In  2005,  Dr.  Majumdar  was  elected  a  member  of  

the  National  Academy  of  Engineering  for  this  pioneering  work.      At  Berkeley  Labs  and  UC  Berkeley,  Dr.  Majumdar  helped  shape  several  strategic  initiatives  in  the  areas  of  energy  efficiency,   renewable  energy,  and  energy  storage.  He  also   testified  before  Congress  on  how  to   reduce  energy  consumption   in   buildings.   Dr.  Majumdar   has   also   served   on   the   advisory   committee   of   the   National   Science  Foundation's   engineering   directorate,   was   a   member   of   the   advisory   council   to   the   materials   sciences   and  engineering   division   of   the   Department   of   Energy’s   Basic   Energy   Sciences,   and   was   an   advisor   on  nanotechnology  to  the  President's  Council  of  Advisors  on  Science  and  Technology.  Additionally,  Dr.  Majumdar  has  served  as  an  advisor  to  startup  companies  and  venture  capital  firms  in  the  Silicon  Valley.  He  received  his  bachelor’s  degree   in  Mechanical  Engineering  at   the   Indian   Institute  of  Technology,  Bombay   in  1985  and  his  Ph.D.  from  the  University  of  California,  Berkeley  in  1989.  

 

PANELIST  INFORMATION  

DR.  PETER   (PETE)  SCHIHL   is   currently   the  Senior   Technical   Expert  of   the  RDECOM-­‐TARDEC  Ground  Vehicle  Propulsion  and  Mobility  Laboratory  and  has  worked  at  TARDEC  since  1991.  His   research   throughout   the   last   eighteen   years   has   concentrated   on   developing   and  experimentally   validating   simplified   combustion  and   ignition  models   for  military   relevant  diesel   engines   and   most   recently   has   focused   on   combustion   characteristic   differences  between   diesel   fuel   and   JP-­‐8,   and   other   relevant   military   heavy   fuels.   To   date,   many  articles  have  resulted  from  his  work  and  he  has  received  the  ‘Best  Paper  in  Session’  award  at  the  1996,  1998,  2000,  2004,  2006,  2008,  and  2010  Army  Science  Conferences  and  twice  

has  received  Department  of  Army  Research  and  Development  Achievement  Awards  (2005  and  2009).  Dr.  Schihl  is  a  reviewer  for  SAE,  ASME,  and  the  Journal  of  Engine  Research  in  his  subject  field  of  expertise,  and  since  1998  has   been   an   invited   reviewer   at   various   Department   of   Energy   Advanced   Compression   Ignition   Engine  Technology  National  Lab  reviews.  Dr.  Schihl  earned  a  Ph.D.  from  the  University  of  Michigan  that  was  focused  on  diesel  combustion  systems  and  has  M.S.  and  B.S.  degrees  in  Mechanical  and  Systems  Engineering  from  Oakland  University  where   he   also   received   a   four   year,   full-­‐ride   basketball   scholarship   to   play   for   Coach  Greg   Kampe.  Previous   to   the   Army,   he  worked   as   a   graduate   research   assistant   at   Oakland  University   studying   the   use   of  photo-­‐thermal  radiometry  for  assessing  thin  coating  thermal  properties  and  also  was  a  research  assistant  at  the  General  Motors  Research  Laboratory  studying  the  use  of  telemetry  for  indirectly  measuring  tappet  stress  in  a  3.1  liter  Chevrolet  engine.  He  is  currently  an  adjunct  faculty  member  at  Lawrence  Technological  University  where  he  has  taught  Heat  Transfer  and  currently  holds  a  State  of  Michigan  boy’s  high  school  state  record  for  blocked  shots  in  a  playoff  game.  

   

18TH ANNUAL AUTOMOTIVE RESEARCH CENTER CONFERENCE      

   

MR.  KYLE  KIMEL  is  the  President  of  AVL  Test  Systems  Inc.  (TSI)  and  is  responsible  for  all  North  American   sales,   operations   and   business   development   for   the   AVL   family   of   powertrain  instrumentation   and   testing   products   and   services.   He   has   over   28   years’   experience   in  engine  and  powertrain  development  and  testing.    

Kimel   joined   AVL   in   2005,   as   the   Director   of   Sales   and   assumed   his   current   position   of  President,  TSI,   in  September  2011.    Prior  to  AVL,  Kimel  held  several  engineering   leadership  positions   with   Lotus   Engineering,  MTS   Systems,   ETAS   and   Kistler   Instruments.   He   holds   a  Bachelor  of  Science  degree  in  Mechanical  Engineering  from  the  University  of  Michigan  and  is  

a  graduate  of  the  Executive  Business  Leadership  Program  at  Stanford  University.    

DR.   MATTHEW   BRUSSTAR   is   the   Director   of   the   Advanced   Powertrain   Center   at   EPA’s  National  Center  for  Advanced  Technology  in  Ann  Arbor,  where  he  is  leading  the  research,  development   and   assessment   of   new   and   emerging   automotive   technologies.    Matt   has  been   with   the   U.   S.   EPA   for   over   thirteen   years,   focusing   mainly   on   advanced   engine  research,  where  he  has  produced  several  publications,  presentations  and  patents.    Prior  to  that,  he  worked  in  the  automotive,  power  generation  and  aerospace  industries.    Matt  is  a  three-­‐time  University  of  Michigan  graduate,  most  recently  earning  his  Ph.D.  in  Mechanical  Engineering  back  in  1995.  

 

DR.  EMILIO  BUNEL  is  the  Director  of  the  Chemical  Sciences  and  Engineering  Division  at  the  U.S.  Department   of   Energy's  Argonne  National   Laboratory.   Bunel   received  his  M.S.   in   Chemical  Engineering   in   1980   from   the   University   of   Chile,   and   his   Ph.D.   in   chemistry   from   the  California   Institute   of   Technology   in   1988.   He   began   his   professional   career   at   DuPont  Central  Research  as  a  member  of  the  Catalysis  Group.  He  was  responsible  for  the  discovery  and   subsequent   development   of   new   processes   for   the   synthesis   of   Nylon   intermediates  required  in  the  manufacture  of  Nylon-­‐6,6  and  Nylon-­‐6.    

In   2001   Bunel   was   hired   by   Eli   Lilly   to   establish   the   Catalysis   Group   within   the   Discovery  Research  Organization.  In  2003  he  was  appointed  Associate  Director  at  Amgen,  Inc.,  and  subsequently  in  January  2008,  Research  Fellow  at  Pfizer,  Inc.  

After   spending   twenty   years   in   industry,   in   October   2008   Emilio   Bunel   was   named   director   of   the   Chemical  Sciences   and   Engineering   Division   at   U.S.   Department   of   Energy's   Argonne   National   Laboratory,   where   he   is  responsible  for  directing  a  science-­‐based  research,  development,  and  early-­‐stage  engineering  organization  that  conducts  both  fundamental  and  applied  research  in  chemistry  and  chemical  engineering.  

One  of   the   areas   that   he   is   responsible   for   is   Electrochemical   Energy   Storage,   internationally   recognized   as   a  world-­‐class  center   for   lithium  battery  R&D  where  the   integration  of  basic   research,  applied  R&D,  engineering,  and  battery  testing,  as  resulted  in  new  technologies  currently  being  deployed  by  industry.    

   

18TH ANNUAL AUTOMOTIVE RESEARCH CENTER CONFERENCE      

   

PROF.  HUEI  PENG  US  Director,  US-­‐China  Clean  Energy  Research  Center-­‐Clean  Vehicle  Consortium  Professor,  Department  of  Mechanical  Engineering,  The  University  of  Michigan  Huei   Peng   received   his   Ph.D.   from   the   University   of   California,   Berkeley   in   1992.     He   is  currently   a   Professor   at   the   Department   of  Mechanical   Engineering   at   the  University   of  Michigan.     His   research   interests   include   adaptive   control   and   optimal   control,   with  emphasis   on   their   applications   to   vehicular   and   transportation   systems.     His   current  

research  focuses  include  design  and  control  of  hybrid  vehicles  and  vehicle  active  safety  systems.      In  the  last  10  years,  he  was  involved  in  the  design  of  several  military  and  civilian  concept  vehicles,  including  FTTS,  FMTV,  and  Super-­‐HUMMWV—for  both  electric  and  hydraulic  hybrid  vehicle  concept  designs.    He  is  currently  the  US   Director   of   the   Clean   Energy   Research   Center—Clean   Vehicle   Consortium,   which   supports   29   research  projects  related  to  the  development  and  analysis  of  clean  vehicles  in  US  and  China.    He  also  leads  an  education  project  funded  by  DOE  to  develop  10  undergraduate  and  graduate  courses  including  three  laboratories  courses  focusing  on  transportation  electrification.    He  has  more  than  200  technical  publications,  including  80  in  referred  journals  and  transactions.      Huei   Peng  has   been   an   active  member   of   the   Society   of  Automotive   Engineers   (SAE)   and   the  ASME  Dynamic  System  and  Control  Division  (DSCD).    He  served  as  the  chair  of  the  ASME  DSCD  Transportation  Panel  from  1995  to  1997,  and  is  a  member  of  the  Executive  Committee  of  ASME  DSCD.    He  served  as  an  Associate  Editor  for  the  IEEE/ASME   Transactions   on   Mechatronics   from   1998-­‐2004   and   for   the   ASME   Journal   of   Dynamic   Systems,  Measurement  and  Control  from  2004-­‐2009.    He  received  the  National  Science  Foundation  (NSF)  Career  award  in  1998.    He  is  an  ASME  Fellow.      

DR.  MATTHEW  REED  is  a  Research  Associate  Professor  and  Head  of  the  Biosciences  Division  of  the   University   of   Michigan   Transportation   Research   Institute.   Dr.   Reed   also   serves   as   the  Director   of   the   Human  Motion   Simulation   Laboratory   at   the   Center   for   Ergonomics   in   the  University  of  Michigan  Industrial  and  Operations  Engineering  Department.  Dr.  Reed’s  research  interests   focus   on   physical   ergonomics,   engineering   anthropometry,   and   vehicle   safety.   He  has   conducted   research  on  occupant   restraint   systems,  emphasizing   investigation  of  airbag-­‐induced   injuries,   crash   dummy   positioning   procedures,   belt   restraints,   and   child   passenger  

safety.     He   has   developed   tools   for   the   ergonomic   design   of   vehicle   interiors,   including  widely   used   posture  prediction  and  motion  simulation  algorithms  for  use  with  digital  human  figure  models.  Dr.  Reed   is  a  Fellow   in  SAE   International   and   a   member   of   the   SAE   Human   Accommodation   and   Design   Devices   Committee,   Driver  Vision   Standards   Committee,   and   Truck   and   Bus   Human   Factors   Committee.   Dr.   Reed   has   received   the   SAE  Award   for   Excellence   in   Oral   Presentation   nine   times,   as  well   as   the   Lloyd   L.  Withrow  Distinguished   Speaker  Award   in   1997,   2004,   and   2010.    He   has   received  outstanding   paper   awards   from   the   Society   of   Automotive  Engineers:  the  Arch  T.  Colwell  Merit  Award  in  2005,  the  Myers  Award  in  2000,  and  the  Isbrandt  Award  for  crash  safety  research  in  1996  and  2004.    (mreed@umich.edu,  http://mreed.umtri.umich.edu)  

 MR.  ERIC  HAUSMAN  is  the  2013  Project  Manager  for  the  University  of  Michigan  Solar  Car.    He  is  currently  a  Junior  majoring  in  Industrial  and  Operations  Engineering.    He  has  been  a  life  long  Michigan  fan  and  has  been  following  the  solar  car  team  since  elementary  school.    In  his  role  as  Project  Manager,  Eric  oversees  the  entire  project  and  helps  to  keep  all  divisions  coordinated  and  on  schedule.  

 

18TH ANNUAL AUTOMOTIVE RESEARCH CENTER CONFERENCE

CASE STUDY ABSTRACTS

CASE STUDY 1

Enabling Integrated Powertrain Experiments across Networked Distributed Laboratories The hardware-in-the-loop (HIL) simulation concept is a critical engineering tool that merges the cost-

effectiveness of computer simulation with the higher fidelity of a physical experiment. In a HIL framework, the system components whose mathematical representations cannot satisfactorily deliver the high accuracies needed are represented with physical prototypes, whereas the rest of the system is simulated virtually. System performance with actual hardware can be validated, since low order models used for design may not provide sufficient accuracy, and system development time, effort, and cost can be reduced.

This case study highlights our basic research to enable the integration of multiple HIL laboratories even if the laboratories are geographically distributed. The aim is to achieve this integration over the Internet to avoid the cost of physically co-locating the hardware components. This technology is referred to as Internet-distributed hardware-in-the-loop (ID-HIL) simulation and is a key enabler for global concurrent engineering.

Specifically, the case study presents the ID-HIL simulation of a hybrid electric vehicle, in which the battery and the engine are the hardware components and the rest of the vehicle is simulated. To this end, the battery-in-the-loop and engine-in-the-loop testing laboratories at the University of Michigan are connected over the network, where a high power battery is physically tested in a laboratory with a specialized cycler and environmental chamber, and a medium-duty diesel engine is physically connected in another facility with a dynamic transient dynamometer. This ID-HIL setup is used to experimentally validate a novel power split algorithm, as well as a technique to improve the fidelity of the ID-HIL simulation when network delays are high.

CASE STUDY 2

Reliability-Based Design Optimizations Code and Its Applications This case study provides a demonstration of technology transfer of ARC research. Ford (industry), Univ.

of Michigan (academia), and TARDEC (government) came together and integrated the Iowa-RBDO (I-RBDO) code with their application-specific M&S codes to perform reliability analysis and reliability-based design optimization (RBDO) for several designs.

The Iowa team has carried out basic research in reliability analysis and RBDO methods, which have been integrated into the I-RBDO code. These include a method to model input marginal and joint distributions from given data using a Bayesian method and copulas, and a performance measure approach by carrying out inverse reliability analysis using the dimension reduction method (DRM) to search for an accurate most probable point. The DRM-based method performs a FORM-based inverse reliability analysis or a SORM-like inverse reliability analysis as per the user’s command. The capability of this RBDO method was successfully demonstrated in the past to obtain reliable optimum designs of Army ground vehicle components for durability.

More recently, for expansion to broader applications, the Iowa team has developed a new sampling-based RBDO method using dynamic Kriging (D-Kriging) surrogate models on local windows. For the D-Kriging method, accurate surrogate models are obtained by using a genetic algorithm for selection of optimum basis functions, the pattern search algorithm for selection of optimum correlation parameter, and a sequential sampling method for an efficient optimal experimental design. For the sampling-based RBDO, the sensitivity analysis is carried out using the score functions that are derived from marginals and copulas. Thus, the new sampling-based RBDO does not require sensitivity analysis from the user’s M&S codes, and it can be very easily integrated with any M&S codes as black-boxes via a very simple ASCII interface file. The sampling-based RBDO method is integrated in the I-RBDO code. The user interface of I-RBDO is very easy to use. The I-RBDO code also allows users to use their own surrogate models for deterministic design optimization and RBDO. In this case, the sampling-based RBDO does not require sensitivity from the user's surrogate model.

18TH ANNUAL AUTOMOTIVE RESEARCH CENTER CONFERENCE

The Ford team is carrying out multidisciplinary RBDO of a vehicle structure to minimize the weight and

satisfying safety and NVH requirements. This vehicle model contains about 1,060,000 elements with a total mass of 1644kg. The crashworthiness analyses are carried out by using LS-DYNA and the NVH by MSC/NASTRAN. The optimization problem consists of 44 gauge design variables which are all random variables with normal distributions. The objective of the optimization problem is to minimize the vehicle weight while satisfying the baseline targets. The design constraints, with 90% reliability, are toe-board intrusion, chest G and crush distance for safety attribute and natural frequencies for NVH.

The Univ. of Michigan team has developed advanced M&S tools for the evaluation of vehicle structural dynamic response under component damage scenarios and/or design changes. These tools are integrated in the parametric reduced order modeling (PROM) code. As a demonstration, the PROM code has been stitched to the I-RBDO code. The focus of the analysis is the frame of an HMMWV. The structure is optimally designed to limit the maximum stresses in the structure (i.e., the design constraints) while minimizing vibrations. The thicknesses of several components of the frame (i.e., the design parameters) are optimally designed such that the vibration energy input into the frame from the road and the engine (i.e., the cost function) is minimized.

18TH ANNUAL AUTOMOTIVE RESEARCH CENTER CONFERENCE

TECHNICAL SYMPOSIUM DAY 1

May 21 A: JP-8 Studies & IC Engines Session Co-Chairs: Peter Schihl, Nicholas Johnson Room: CSE 1670

B: Thermal Dynamics & Hybrid Powertrains Session Co-Chairs: Yi Ding, Sonya Zanardelli Room: CSE 1690

C: Design/V&V/Reliability Session Co-Chairs: Mark Brudnak, Amandeep Singh Room: DOW 1013

13:30 Autoignition Characteristics of JP8, ULSD, Synthetic and Biodiesel Fuels, PI: Naeim Henein

Control and System Integration of an SOFC/GT-based APU with Extended Dynamic Capabilities for Military Vehicle, PIs: Jing Sun, Soryeok Oh

Validation of Simulation Models of Dynamic Systems, PIs: Michael Kokkolaras, Greg Hulbert

13:55 Development of Comprehensive JP-8 Surrogate for Heavy Duty Compression Ignition Engine, PI: Angela Violi, Jason Martz

Computationally-Efficient 3D Finite-Element-Based Thermal Models of Electric Machines, PI: Heath Hofmann

HEV Powertrain Architecture Exploration Using Bond Graphs, PIs: Panos Papalambros, Michael Kokkolaras

14:20 Cold Start Testing of a Production High Power Truck Engine with Different Alternative Fuels, PI: Dinu Taraza

Automotive Thermal Management – A Combined Numerical and Experimental Study of Battery Pack Cooling in Hybrid Vehicles, PIs: John Wagner, Lin Ma

Accelerated Testing for Vehicle Systems using Time-Dependent Reliability Principles, PI: Zissimos Mourelatos

14:45 – 15:10

Intricate Dynamics and Frictional Losses of the Piston-Assembly in IC Engines, PI: Nabil Chalhoub

Bilevel Multiobjective Optimization for the Battery Thermal Packaging Design, PIs: Margaret Wiecek, Geoges Fadel

Reconfigurable Control for Failure Prevention and Recovery, PIs: Dawn Tilbury, Ella Atkins

TECHNICAL SYMPOSIUM DAY 2

May 22 A: Mobility/Terramechanics Session Co-Chairs: Al Reid, Paramsothy Jayakumar Room: CSE 1670

B: Electrified Powertrains: Design and Characterization Session Co-Chairs: Yi Ding, Sonya Zanardelli, Wes Zanardelli Room: CSE 1690

C: Survivability/Reliability Session Co-Chairs: David Lamb, Harry Zywiol Room: DOW 1013

10:00 Advancements in TerrainSim: Terrain Characterization, Modeling, Analysis, and Synthesis Software, PI: John Ferris

Electrified Propulsion Systems: Integration of e-Motors and Sizing Based on Thermal Load Consideration, PI: Zoran Filipi

A Blast Event Simulation Process for Multi-Scale Modeling of Composite Armor for Light Weight Vehicles, PI: Nick Vlahopoulos

10:25 Off-Road Soft Soil Tire Model Development, Validation, and Interface to Commercial Multibody Dynamics Software PI: Corina Sandu

Optimal Charging of Ultracapacitors During Regenerative Braking, PI: Ardalan Vahidi

Sampling-based RBDO using Stochastic Sensitivity Analysis and Virtual Support Vector Machine, PI: K.K. Choi

10:50 Integrated Power Systems for Improved Mobility of Ground Robotics, PI: Huei Peng

Neutron Imaging of Lithium Ion Batteries: Toward Parameterization of High Fidelity Lithium Ion Battery Models for High Power Applications, PI: Anna Stefanopoulou, Jason Siegel

Parametric Reduced Order Models for Fatigue Life Predictions of Hybrid Electric Vehicle Batteries, PI: Bogdan Epureanu

11:15 – 11:40

UGV System Reliability Modeling & Improvement, PI: Judy Jin, A. Galip Ulsoy

High Energy Density Asymmetric Capacitors, PI: Levi Thompson

Soldier-Centered Vehicle Seating Design Tools based on Measurement and Modeling of Soldiers, PI: Matthew Reed

18TH ANNUAL AUTOMOTIVE RESEARCH CENTER CONFERENCE

TECHNICAL SYMPOSIA ABSTRACTS

Day 1 Technical Session A – JP-8 Studies, IC Engines & Thermal Management Session Co-Chairs: Dr. Peter Schihl, Mr. Nicholas Johnson

1A1: Autoignition Characteristics of JP8, ULSD, Synthetic and Biodiesel Fuels; C. Jayakumar, U Joshi, Z. Zheng, PI: Naeim A. Henein (Wayne State U.)

The investigations on the autoignition characteristics of JP8, ULSD, synthetic S-8 fuels included experimental, detailed analysis of the rate of heat release (RHR) and diesel cycle computer simulations. Two types of JP-8 are investigated. The first is JP-8 with a high cetane number (CN=44). The second has CN of 31 which has been reported to cause serious problem to military engines in the field. The experiments were conducted on a single-cylinder high speed research diesel engine equipped with a common rail injection system. The inlet air temperature was varied to calculate the global activation energy of different fuels based once on the total ignition delay (ID) and another time on the chemical part of I.D. The difference in the activation energies is found to be the inclusion of the physical delay in the total dely. Detailed analysis of experimental results of the rate of heat release (RHR) for the different fuels indicated the presence of the LTHR (low temperature heat release or “cool flame”) and the NTC (negative temperature coefficient) regimes in the autoignition of JP-8(31). These regimes slow down the autoignition process and increase the ID to a point where the engine misfires. Diesel cycle computer simulations showed the role of aldehydes in slowing the autoignition exothermic reactions and agreed with the experimental results on the effect of the increase in charge temperature and pressure on reducing the LTHR and HTHR of the low-CN JP-8.

1A2: Development of Comprehensive JP-8 Surrogate for Heavy Duty Compression Ignition Engine; Doohyun Kim, Paolo Elvati, Angela Violi (PI), Jason Martz (U. of Michigan);Peter Schihl, Laura Hoogterp, Nick Johnson (TARDEC); Craig Savonen, Justin Kollien, Kevin Sisken (DDC)

The use of JP-8 on ground vehicles with compression ignition engine is mandated by Army’s single battlefield fuel policy. Expected cetane number variation of petroleum/coal/natural gas based JP-8 is wide enough (30s ~ 60s) to cause significant changes in combustion phasing, mode, and rate, which may lead to serious durability and fuel economy problems. In this work, a comprehensive JP-8 surrogate is developed for CFD engine simulation which is a fundamental tool to analyze the effect of different physical and chemical properties of JP-8, including cetane number, on its combustion characteristics. 4-component and 5-component mixtures are formulated by optimization process to represent hydrocarbon class distribution and to match target properties of real JP-8. Blending ratios of these surrogates for low, mid, and high cetane number JP-8 is also proposed. Furthermore, available chemical mechanisms which enable simulation of proposed surrogate are tested and selected.

1A3: Cold Start Testing of a Production High Power Truck Engine with Different Alternative Fuels; Florin Mocanu, Amrinder Singh, Madhu Palanisamy, PIs: Dinu Taraza (presenter), Marcis Jansons, Naeim Henein (Wayne State U.)

A major concern for military vehicles is the prompt and sure engine starting in very cold environments. In this project, a six cylinder commercial truck diesel engine: Mercedes Series 900 (250 HP @ 2200 rpm- 800 lb.ft 1300 – 1600 rpm) has been fully instrumented with pressure transducers on each cylinder and tested in the cold room facility at Wayne State University. Cold starting with two different fuels: ULSD and JP8 were conducted at temperatures ranging from 700F to 00F. The engine fully started with ULSD down to 200F and with JP8 down to 160F. At lower temperatures the engine fueled with JP8 reached Idling speed, but failed to start due to inadequate fuel injection strategy. The fuel injection was reduced, even completely cut, or desynchronized with the pressure pulse in the injector high pressure line. These preliminary results point out the necessity to improve fueling strategy for cold starting in the electronic controls of the engine. Further investigations will concentrate on the development of better fuel injection strategies.

18TH ANNUAL AUTOMOTIVE RESEARCH CENTER CONFERENCE

1A4: Intricate Dynamics and Frictional Losses of the Piston-Assembly in IC Engines; Mohannad Hakeem, PI: Nabil G. Chalhoub, Naeim A. Henein (Wayne State U.); Pete Schihl (TARDEC)

The intricate dynamics of the piston-assembly directly affect the performance of IC engines by influencing their fuel efficiency through frictional losses, thermal efficiency through blow-by, emissions through oil consumption, durability through wear, and engine noise through piston-slap. In this work, a dynamic model for the crank-slider mechanism of a single cylinder engine has been developed to predict the intricate dynamics and the lubrication regimes of the piston-assembly under various engine operating conditions. The formulation considers the interconnected motions of the crankshaft, connecting-rod, piston (including piston-slap and piston-tilting), and ring-pack using a multi-body dynamic approach. Each ring is considered to have three rigid body degrees of freedom in addition to its longitudinal and in-plane transverse deformations. The structural flexibility terms are approximated by using curved beam finite elements derived based on the Timoshenko beam theory. Moreover, the model has a variable structure whose number of degrees of freedom depends on the liner-piston-ring interactions. Furthermore, the solid-fluid interaction between the lubricating oil film and the piston-assembly is considered for determining the friction losses induced by the hydrodynamic lubrication regime of the piston-skirt and the elasto-hydrodynamic lubrication regime of the rings.

Day 1 Technical Session B – Thermal Dynamics & Hybrid Powertrains Session Chair: Dr. Yi Ding

1B1: Control and System Integration of an SOFC/GT-based APU with Extended Dynamic Capabilities for Military Vehicle; Zhenzhong Jia, PIs: Jing Sun, Soryeok Oh (U. of Michigan); Herb Dobbs, Joel King (TARDEC); Owen Taylor (Pittsburgh Electrical Engine Inc.)

Integrating high temperature solid oxide fuel cells (SOFC, 600-800degC) with a gas turbine (GT) is an effective strategy to develop highly efficient and clean power generation solutions. While the concept of SOFC/GT is very appealing for mobile applications (such as for military vehicles) from the energy conversion efficiency point of view, its feasibility depends critically on the dynamic characteristics of the combined cycle system. This project is aimed at addressing the control and system integration challenges of SOFC/GT to achieve safe, efficient and fast load following under different operating conditions and various constraints. This presentation will focus on the dynamic analysis of the SOFC/GT system with battery and dual mode generator/motor (G/M). The relative merits of different system integration strategies are explored to extend the dynamic capabilities and improve the load following performance of the SOFC/GT system. In particular, the study shows that by taking full advantage of the bi-directional operation of G/M, one can better manage the trade-offs between power tracking and thermal management, thereby further reducing battery power and energy requirements for the integrated system.

1B2: Computationally-Efficient 3D Finite-Element-Based Thermal Models of Electric Machines; Kan Zhou, Jason Pries, PI: Heath Hofmann (U of Michigan); Denise Kramer (TARDEC); Lei Hao (GM.

Knowledge of the internal temperatures of an electric machine under real-time operating conditions would be extremely useful in order to determine its torque capabilities. This knowledge is also useful for full-scale electric vehicle simulation and optimization. In this work, we present a technique for developing computationally-efficient thermal models for electric machines that can be used for real-time thermal observers and vehicle-level simulation and optimization.

The technique is based upon simulating the eigenmodes of the thermal dynamics as determined by 3D finite element analysis. The order of the model is then dramatically reduced in two ways. First, the dynamic system is decomposed into two parts by using the orthogonal property of the eigenvectors. The extent of excitation of each eigenmode is calculated, and only eigenmodes that are significantly excited are included in the dynamic model; other eigenmodes are treated as static modes. Second, only a few “hot spots” in various regions are chosen.

The result is a thermal model that can accurately model internal temperatures of the machine while requiring the modeling of only a handful of states. Such a model can be used in vehicle simulations, or for real-time observers in actual vehicles. The computation time of the computationally-efficient reduced-order model presented in this work is reduced by more than 5 orders of magnitude compared with a typical full–order finite

18TH ANNUAL AUTOMOTIVE RESEARCH CENTER CONFERENCE

element model. Experimental validation on a 145kW liquid cooling permanent magnetic surface mount machine is being undertaken to validate the presented thermal model.

1B3: Automotive Thermal Management – A Combined Numerical and Experimental Study of Battery Pack Cooling in Hybrid Vehicles; Joshua Finn, William Tao, John Wagner (Clemson U.); Lin Ma (Virginia Tech)

The operation of military vehicles in extreme temperature environments requires robust thermal management systems to effectively remove heat from the passenger compartment and powertrain components. The increasing need for heat rejection may be partially attributed to a greater emphasis on vehicle electronic content and alternative energy sources. This presentation describes a collaborative effort combing simulations and experiments to investigate advanced automotive thermal management concepts. First, a concluding ARC study will be presented in which thermoelectric devices have been applied using the concept of cooling zones to offer localized temperature regulation for electronic equipment and compartment occupants. Second, a new project is described which integrates numerical simulations (Clemson University) and experimental tests (Virginia Tech) to investigate hybrid vehicle battery pack cooling.

1B4: Bilevel Multiobjective Optimization for the Battery Thermal Packaging Design; Brian Dandurand, Paolo Guarneri, PIs: Georges Fadel, Margaret M. Wiecek (Clemson U.)

The battery thermal packaging design requires the optimization of the battery position in the vehicle to improve vehicle dynamics, component accessibility and passenger survivability subject to geometric constraints such as collision between the components in the vehicle, and the simultaneous optimization of cell layout inside the battery pack while considering thermal aspects. Since each optimization is driven by multiple performance criteria, the battery design motivates new research in mathematical optimization. Approaches are being developed to generating the Pareto set of the all-in-one (AiO) bilevel multiobjective problem by computing subproblem-specific approximations of the AiO Pareto set.

An adaptation of the block coordinate descent technique is proposed that makes use of decomposition in the objective and design space. This approach to decomposing a multiobjective problem suitably addresses the needs of the battery design problem. Each subproblem-specific approximation of the AiO Pareto set is iteratively updated based on previous subproblem updates so that the subsequent approximations converge to the AiO Pareto set. Convergence is claimed based on existing or newly proved results. Examples are provided and the relevance to the battery design is shown.

Day 1 Technical Session C – Design/V&V/Reliability Session Co-Chairs: Dr. Mark Brudnak, Dr. Amandeep Singh

1C1: Validation of Simulation Models of Dynamic Systems; Hao Pan, PIs: Michael Kokkolaras, Greg Hulbert (U. of Michigan)

Simulation models of dynamic system models typically generate time-dependent and correlated output with high dimensionality, uncertainty and noise. From the many model validation methods reported in the literature, most are not directly applicable to validating models of dynamic systems. Our research aims at addressing this issue by means of a particular framework that utilizes feature extraction techniques and Bayesian interval-based hypothesis testing. Although this framework addresses the validation problem uniquely by providing quantitative assessment of the goodness of the model by means of a confidence metric, it is based on several limiting assumptions. Moreover, its results can be sensitive to the determination of the integration limits in the Bayes factor calculation. We investigate assumptions and report improvements to model confidence quantification. The advantages of the presented framework are demonstrated using a benchmark validation problem derived specifically for a validation workshop organized by Sandia National Laboratories. Results are compared to those of other validation techniques and subject matter expert opinions. We also report on the contributions of our research to providing guidelines and tools for validating models in a tri-force power/energy community of interest with a particular application of an electro-thermal battery model developed by ARC researchers for electrified powertrains of military ground vehicles.

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1C2: HEV Powertrain Architecture Exploration Using Bond Graphs; Alparslan Emrah Bayrak, Yi Ren, PI: Panos Papalambros (U. of Michigan)

The introduction of mechatronic devices (e.g., motors and generators) to powertrain systems has largely enriched design possibilities, with various efficient powertrain architectures being proposed and realized. While existing research has covered all spectra from powertrain sizing and packaging to optimal control in driving cycles, there is no systematic way of exploring possible powertrain architectures. As an exploratory study to create "clean-sheet" design, we introduce a framework to enumerate and filter architectures by means of bond graphs. The automated procedure outputs system properties, e.g., degree of freedom, state space equations, etc. for architectures with different complexity, e.g., number of planetary gears in the system. We then search for the optimal graph with optimal control as a nested problem.

1C3: Accelerated Testing for Vehicle Systems using Time-Dependent Reliability Principles; Igor Baseski (TARDEC/OU), Jing Li, PI: Zissimos P. Mourelatos (Oakland U.); Amandeep Singh (TARDEC)

Reliability usually degrades with time increasing the product lifecycle cost. It expresses the probability that the product will perform its intended function successfully for a specified time. It is desirable to use accelerated testing to predict vehicle reliability using a few tests of short duration. Considering that certain vehicle parameters and the vehicle excitation are random, many vehicles must be tested which is impractical. To address this challenge, we are developing an accelerated testing approach based on both experiments and analysis. Because it is practically difficult to develop and use a detailed analytical (math) model of a vehicle which closely represents reality, our approach uses available tests to calibrate an approximate simulation model which is then used to determine the failure rate of the vehicle fleet. The failure rates are estimated using a subset simulation technique with Markov Chain Monte Carlo (MCMC) considering the terrain random process and different random variables representing vehicle to vehicle variability. The methodology will be institutionalized at the TARDEC Physical simulation lab. We will provide details including progress to-date, our test rig at TARDEC and future plans.

1C4: Reconfigurable Control for Failure Prevention and Recovery; John Broderick, PIs: Dawn Tilbury, Ella Atkins (U. of Michigan)

The objective of this research is to develop models, algorithms and methods both to prevent failures from occurring and to recover from or adapt to failures after they occur. Prior work within this project has considered failures in the robot’s manipulator arm (frozen joints) and thermal overload. Recent work considers the impact of limited battery power when exploring an area. A novel cost function can be used in an optimal control scenario to trade off power used and area covered. Two different coverage planners have been considered; the planned paths are converted into trajectories using the optimal control strategy. Simulation results highlight the differences between the two planners. Experimental results with the PackBot indicate that the battery power does not follow the simple relationship with motor torque that was assumed in the simulation model; research is ongoing to better understand the actual power usage as a function of vehicle speed. Near-term future work includes extending the work to mobility failure cases such as loss of traction. Longer-term, we plan to integrate the results into a reconfigurable control strategy that can both prevent failures (e.g., thermal overload and battery empty) and adapt to failures (e.g., frozen manipulator joints, loss of traction).

Day 2 Technical Session A – Mobility/Terramechanics Session Co-Chairs: Dr. Al Reid, Dr. Paramsothy Jayakumar

2A1: Advancements in TerrainSim: Terrain Characterization, Modeling, Analysis, and Synthesis Software; Philip Chin, Jacob Lambeth, Ma Rui, John Ferris (PI, Virginia Tech)

Terrain is the main vehicle excitation and is particularly challenging to model since it is a richly complex signal with significant physical characteristics over a wide range of wavelengths. TerrainSim software has been successfully developed to study terrain characteristics by providing multiple modeling and synthesis techniques and a comprehensive set of statistical analyses to determine the model quality. In addition to several enhancements to the Markov Chain modeling technique, TerrainSim’s abilities are being expanded to include:

18TH ANNUAL AUTOMOTIVE RESEARCH CENTER CONFERENCE

modeling a terrain surface, rather than only individual longitudinal profiles and modeling deformable off-road terrain, rather than being limited to non-deformable terrain. Recent results indicate that TerrainSim is now applicable to full surfaces, profiles, and their decompositions, as well as preliminary indications that it will be possible to model deformable terrain as part of a holistic approach to tire/terrain interaction.

2A2: Off-Road Soft Soil Tire Model Development and Experimental Testing; Eduardo Pinto, Scott Naranjo, Shahyar Taheri, PIs: Corina Sandu, Saied Taheri (Virginia Tech); Paramsothy Jayakumar (TARDEC); Brant Ross (MotionPort)

Accurate and efficient tire models for soft soil operations are needed for army mobility simulations. The tire model is essential in a vehicle model; the accuracy of the predicted forces and moments has a large impact on assessing the vehicle performance, reducing the number of stuck vehicles, avoiding rollovers, and developing advanced control strategies. While FEM lead to the most detailed tire-soil interaction models, their complexity and extensive computational effort make them less than ideal for the applications envisioned. Models such as the F-tire were developed for on-road applications. The semi-analytical soft-soil tire model developed employed a similar construction and added an advanced tire-soil contact model. Testing is performed on a single tire on silty sand in the terramechanics rig at Virginia Tech. The influence of tire and vehicle parameters and soil characteristics on the tire dynamics is studied. The silty sand has been tested in a commercial lab to extract its properties. The test tire has been instrumented with sensors for measuring the rolling tire deflection in real time. The goal of the project in the second year is to refine the tire model by incorporating accurate tire and soil parameters, enhancing traction and steering model capabilities, and conducting laboratory and field tire testing for validation.

2A3: Integrated Power Systems for Improved Mobility of Ground Robotics; William Smith, Tianyou Guo, PI: Huei Peng (U. of Michigan);

Small unmanned ground vehicles (SUGVs) play an important role in many industries, from planetary exploration to military defense. SUGVs are limited by their mobility, whether they become immobilized from traversing difficult terrain or from early energy depletion. Improved design and control of SUGV propulsion systems can limit these forms of immobilization, but this requires an improved understanding of the interaction between running gear and terrain. We present different approaches of modeling vehicle-terrain interaction for wheeled and tracked vehicles. Using numerical simulation techniques, we model dynamic wheel-soil interaction conditions to better characterize how rough terrain can influence vehicle performance and mobility. Better understanding of the influence that dynamic effects can have on performance may lead to improved vehicle design and online control. For tracked vehicles, we explore the importance of initial value selection when solving a steady-state Bekker skid steering model. We also evaluate an approximation method of the Bekker equations that results in a closed-form analytical solution, which is particularly useful for online control.

2A4: UGV System Reliability Modeling & Improvement; Amir Sadrpour, W. Rob Brown, PIs: Judy Jin, A. Galip Ulsoy (U. of Michigan); Greg Hudas (TARDEC); Rainer Gasche and Jason Suchman (iRobot)

The goal of this project is to develop methods to analyze and improve the reliability of unmanned ground vehicles (UGVs).

A new design method, to improve reliability and efficiency of a UGV manipulator arm, has been developed using passive elements (i.e., torsional springs) in parallel with joint motors for typical arm trajectories and loads. For a simple single-link arm the method has been shown experimentally to reduce maximum torques by about 50% and improve energy efficiency by up to 25%. Currently robust design methods are being explored to extend the design method to families of loads and trajectories and to multi-link arms.

A unified approach to UGV system reliability assessment that includes simulation-based acceptance testing, on-line monitoring combined with prior knowledge for predicting mission reliability, and the effects on reliability of the environment and the operator is presented. UGV mission battery end-of-life estimation under varying terrain conditions uses a vehicle model and a Bayesian framework to combine real-time estimation with prior knowledge (e.g., grade, road conditions, driver style) for adaptively updating the knowledge and assessing alternative decisions during the mission execution. Theory and simulations are completed, and experiments are planned for spring/summer 2012.

18TH ANNUAL AUTOMOTIVE RESEARCH CENTER CONFERENCE

Day 2 Technical Session B – Electrified Powertrains: Design & Characterization Session Co-Chairs: Dr. Yi Ding, Dr. Wesley Zanardelli

2B1: Electrified Propulsion Systems: Integration of e-Motors and Sizing Based on Thermal Load Consideration; Xueyu Zhang, Andrej Ivanco, PI: Zoran Filipi (Clemson U.) Youngki Kim (U. of Michigan)

Improving the fuel economy of military trucks is a critical element in the US DoD’s effort to limit the increase of energy consumption in the battlefield, reduce the logistics burden and curb the ballooning expenses for fuel. Electrification and hybridization show great potential for improving fuel economy, and providing part of the solution. The fuel efficiency can be improved while preserving or improving other key vehicle attributes, e.g. performance and mobility. In particular, a series configuration with in-hub motors enables development of independent suspension with increased wheel travel for high cross-country speeds. However, significant cost, integration and control challenges have to be addressed before the technology is ready for applications to large military fleets. Our previous effort focused on applications of reduced order electro-chemical battery model for characterizing dynamic load schedules, critical surface concentration of ions, and utilization of the information for battery power management. This year’s effort is focused on a similar approach to e-Motor design and integration. We aim to utilize the new predictive capability enabled with scalable, reduced-order models of e-Motors developed by Prof. H. Hofmann’s complementary project for system level studies. A computationally efficient dynamic thermal model is created, that considers power losses and heat fluxes to estimate inner, otherwise immeasurable, temperatures of the electric machine. Consequently, HEV system analysis includes dynamic behavior of e-motors under aggressive duty cycles in the Mine Resistant Ambush Protected All-Terrain Vehicle (M-ATV), and considers motor size and cooling system parameters based on predictions of thermal load. This removes the uncertainty related to conventional approach that relies on a “continuous power” line vs. peak power line, and opens the door for studies of accessory power losses. The on-going work is focused on development of the dynamic programming framework that will enable a pioneering investigation of optimal power management of a series HEV with in-hub motors, while considering both propulsion power and accessory losses.

2B2: Optimal Charging of Ultracapacitors During Regenerative Braking; Yasha Parvini, PI: Ardalan Vahidi (Clemson U.)

Finding the optimal charging profile of an ultracapacitor energy storage system during a regenerative braking event is the focus of this paper. After showing that resistive losses can be high during a high power regeneration event, we formulate the charging problem in an optimal control framework with the objective of maximizing the energy recuperated into the ultracapacitor bank while satisfying braking power demands. We employ Pontryagin’s maximum principle to understand the necessary conditions the solution should satisfy and use numerical techniques to find such optimal solution(s).The result should provide more insight into the maximum achievable regeneration efficiency with ultracapacitors under different braking conditions and can also aid in sizing an ultracapacitor energy storage system and the associated power electronics device.

2B3: Neutron Imaging of Lithium Ion Batteries: Toward Parameterization of High Fidelity Lithium Ion Battery Models for High Power Applications; Jason Siegel, PI: Anna Stefanopoulou (U. of Michigan)

Lithium ion battery models based on porous electrode theory (by Fuller, Doyle, and Newman) have been developed and used by many researchers since the early 1990’s. However validation of these models by means other than input-output (current-voltage) behavior remains elusive. This project seeks to validate the spatial and temporal lithium concentration profiles across the electrodes and electrolyte during battery operation using in situ measurements from neutron imaging.

We first show parameterizations that match the terminal voltage of a Lithium Iron Phosphate (LFP) battery under various discharge rates and drive-cycle current profiles. The 1+1D model framework uses partial differential equations to describe the Lithium concentration across the battery electrolyte and electrodes. The Lithium intercalation in the solid material is coupled with the electrolyte lithium concentration through the Butler-Volmer reaction rate which varies across the electrode. The model contains 25 “tunable” parameters. Several of these

18TH ANNUAL AUTOMOTIVE RESEARCH CENTER CONFERENCE

parameters can be determined via ex-situ methods, such as scanning electron microscopy or half-cell experiments. The remaining parameters need to be identified and can impact the lithium distribution and hence electrode utilization and measured terminal voltage. A comparison of the model predicted lithium distributions with the measurements from neutron imaging will identify gaps in the well-established modeling approach of the porous electrode theory, especially during high power (pulsed) operation of batteries.

Strong collaborations allowed us to surpass many technical limitations, namely design of experiment and material selection with Yi Ding from TARDEC, battery fabrication with Patrick Hagans and Danny King from A123, instrumentation with Dan Hussey and David Jacobson from NIST, signal statistics with David Gorsich from TARDEC, battery simulation software with Matt Castanier from TARDEC, model reduction and verification with Dyche Anderson and Yonghua Li from Ford, and fundamental battery transport phenomena with Charles Monroe from UMICH and Steve Harris from GM.

2B4: High Energy Density Asymmetric Capacitors; Priyanka Pande, PI: Levi Thompson, Paul Rasmussen (U. of Michigan); Yi Ding (TARDEC); Stefan Heinemann (Fraunhofer USA)

Batteries are the principal devices used for military and commercial energy storage applications. While these devices can have energy densities exceeding 100 Wh/kg, this energy is difficult to fully access in pulsed and high power applications due to the relatively slow kinetics associated with their redox processes. Supercapacitors offer much higher power densities and could complement batteries in pulsed power applications, however, their low energy densities are only sufficient for relatively short pulses (a few seconds). Our research is exploring the feasibility the using asymmetric cell designs and new, high capacity materials to produce asymmetric supercapacitors with energy densities that out-perform currently available devices and enable applications with longer pulses. This paper will describe our progress including a summary of performance characteristics for the materials and prototype cells, as well as the charge storage mechanisms for the early transition metal nitrides and carbides.

Day 2 Technical Session C – Survivability/Reliability Session Co-Chairs: Dr. David Lamb, Mr. Harry Zywiol

2C1: A Blast Event Simulation Process for Multi-Scale Modeling of Composite Armor for Light Weight Vehicles; John Kim, PI: Nickolas Vlahopoulos (U. of Michigan)

Lighter weight military vehicles facilitate faster transport, higher mobility, fuel conservation, and a reduced ground footprint of supporting forces. Composite materials provide some of the most viable options for manufacturing composite armor that can increase survivability without significant weight penalty. A multi-scale simulation process using the coupled MAC/GMC and ABAQUS explicit codes for computing the response of a structure subjected to a load from an explosion has been established during earlier stages of this project. The most recent efforts in incorporating micro-constitutive material behavior at high strain rate loading in the simulation process, formulating an inverse mapping capability for linking desired material properties with the composition of their micro structure in MAC/GMC, and conducting an optimization analysis for identifying the desirable material properties for increasing the blast resistant characteristics will be discussed.

2C2: Sampling-based RBDO using Stochastic Sensitivity Analysis and Virtual Support Vector Machine; Hyeongjin Song. PI: K.K. Choi (U. of Iowa); David Gorsich, David Lamb (TARDEC)

In this research, a sampling-based RBDO method using a classification method is proposed. The stochastic sensitivity analysis is used to compute sensitivities of probabilistic constraints with respect to random variables. Since the stochastic sensitivity analysis requires only the limit state function, and not the response surface or its sensitivity, it is desirable to develop an efficient classification method that can be used for a sampling-based RBDO. The proposed virtual support vector machine (VSVM), which is a classification method, is a support vector machine (SVM) with virtual samples. By introducing virtual samples, VSVM overcomes the deficiency in existing SVM that uses only classification information as their input. In this research, the universal Kriging method is used to obtain locations of virtual samples to improve the accuracy of the limit state function for highly nonlinear problems. A new sequential sampling strategy effectively inserts additional samples near the

18TH ANNUAL AUTOMOTIVE RESEARCH CENTER CONFERENCE

limit state function. In the sampling-based RBDO, Monte Carlo simulation (MCS) is used for the reliability analysis and stochastic sensitivity analysis. Since SVM has simpler formulation than implicit methods such as Kriging, computational cost for evaluating a large number of MCS samples can be significantly reduced. Several efficiency strategies, such as the hyper-spherical local window for generation of the limit state function and the Transformations/Gibbs sampling method to generate uniform samples in the hyper-sphere, are also applied. Examples show that the proposed sampling-based RBDO with VSVM yields better efficiency in terms of the number of required samples and the computational cost for evaluating MCS samples while maintaining accuracy similar to that of sampling-based RBDO using the dynamic Kriging (D-Kriging) method.

2C3: Parametric Reduced Order Models for Fatigue Life Predictions of Hybrid Electric Vehicle Batteries; Sung Kwon Hong, PI: Bogdan I. Epureanu (U. of Michigan); Matt Castanier (TARDEC)

The goal of this work is to develop an efficient numerical modeling technology for fatigue life predictions of hybrid electric vehicle (HEV) batteries. Typically 100 or 200 (nominally) identical battery cells are stacked in a HEV battery pack. Since these cells are nominally identical, their dynamics suffers from very high modal density. The high modal density causes small structural variations from cell to cell to have very large consequences on the dynamics of the entire pack (in the range of frequencies where the modes are dense). Therefore, the fatigue life of a pack should be predicted by statistical dynamic response calculations. Such statistical calculations are hard to perform using sensitivity-based methods because the mode shapes of a pack depend in a nonlinear fashion on the parameters of each cell. The alternative is to use sample based statistical analyses, where many thousands of samples are required. However, typical finite element models of single packs have many millions of degrees of freedom. Thus, the computational time for just a single sample can be of the order of a day. One approach to overcome this challenge is to create parametric reduced-order models (PROMs). Herein, such new PROMs are developed. They able to predict the dynamics of battery packs 1,000 to 10,000 times faster than full order models while maintaining accuracy. The novel approach is based on two key assumptions. First, the mode shapes of a pack (with parametric variations) can be represented by a linear combination of the nominal pack (no parametric variations). This assumption is ensured by the high modal density. Second, the frame holding each cell moves. The variability in parameters in the corresponding cell is captured by mode shapes of the nominal cell with its boundary displaced the same amount as the frame. Numerical results to demonstrate the new method have been obtained. The PROM predictions agree very well with predictions of full-order models, with maximum errors between 1.18% and 1.64%. The analysis time required by the PROM for each variation by is about 9,000 times shorter than that of the full-order models. This computational gain is expected to be even larger for more refined models. That is because PROMs are able to capture the low-dimensional physics. Thus, and the size of the PROM is not expected to increase when the size of the full order model increases (e.g., by mesh refinement).

2C4: Soldier-Centered Vehicle Seating Design Tools based on Measurement and Modeling of Soldiers; PI: Matthew P. Reed (U. of Michigan, UMTRI)

The design of tactical vehicles to maximize crew performance and survivability is hampered by a lack of detailed data on the postures and positions of soldiers. Civilian design tools cannot be readily applied because military populations differ in body dimensions from civilians, the task conditions do not match typical civilian situations, and soldiers frequently wear personal protective equipment that affects body shape, posture, and position. To address this need, detailed posture and body shape data were measured from 300 soldiers with a wide range of body size at four levels of encumbrance: minimally clad, uniform, body armor with helmet, and fully encumbered as a rifleman or SAW gunner. Posture data were gathered in driver and crew mockups and a whole-body laser scanner was used to gather body shape data in a range of standing and seated postures. The data are being analyzed for application to a wide range of vehicle design and analysis problems, including the development of accurately dimensioned manikins for vehicle ergonomic assessment and space claim, the provision of detailed anthropometry for the development of an advanced blast dummy, and revision of current standards for military vehicle interior layout.

18TH ANNUAL AUTOMOTIVE RESEARCH CENTER CONFERENCE

Lift

CSE  1670Session  A

CSE  1690Session  B

Dow  1013Session  C

Refreshments

CSE  Building  South  Entrance

Posters

Exhibitor

Session  C

Reliability/Survivability

Vehicle  Control  &Terramechanics

JP-­‐8  Studies  &  IC  Engines

Human  Modeling

Thermal  Dynamics/Management  

&  Electrical

Energy  Storage

Design,  Optimization,  VV&A

1.71.91.21.151.121.132.4

4.3  4.6(1)4.6(2)4.11A.94.16

1.6A.74.151.104.84.9

4.134.124.14 Hybrid

Powertrains

1.8(1)1.8(2)4.4A.11

3.1,  3.2,  3.4,  3.5

5.1,  5.2(1)(2),  A.19,  5.3,  A.14,  5.5,  5.6(1)(2)

2.5A.13

POSTER SESSION Vehicle Control and Terramechanics 1.2 Internet-Distributed Hardware-in-the-Loop Simulation, Ersal 1.7 Advancements in TerrainSim: Terrain Characterization, Modeling,

Analysis, and Synthesis Software, Ferris 1.9 Off-Road Soft Soil Tire Model Development, Validation, and Interface to

Commercial Multibody Dynamics Software, Sandu 1.12 Vehicle-Terrain Interaction Modeling for Design and Control, Peng 1.13 Reconfigurable Control for Failure Prevention and Recovery,

Tilbury/Atkins 1.15 Vehicle-Dynamics-Conscious Real-Time Hazard Avoidance in

Autonomous Ground Vehicles, Stein 2.4 Evaluation and Performance Modeling of User Interfaces for UGVS,

Tilbury Human Modeling 2.5 Creating Encumbered Human Figure Models for Ergonomic Design and

Assessment of Tactical Vehicles, Reed A.13 Soldier-Centered Vehicle Seating Design Tools based on Measurement

and Modeling of Soldiers, Reed Reliability/Survivability 3.1 Technology Transfer of I-RBDO and DRAW/LS-DYNA Codes, Choi 3.2 Confidence-based RBDO and Sampling-based RBDO using Virtual Support Vector Machine, Choi 3.4 Structural Dynamic Modeling and Analysis of Damaged Vehicles, Epureanu 3.5 Multi-Scale Design of Light Weight, Blast Resistant Structures, Vlahopoulos JP-8 Studies & IC Engines 4.3 Piston-Assembly Dynamics and Frictional Losses in High Power Density Diesel Engines, Chalhoub 4.6(1) Combustion Behavior and Fuel Economy of Modern Heavy-Duty Diesel Engine Using JP-8 and Alternative Fuels, Violi/Martz 4.6(2) Fuel Property Sensitive Spray Modeling of Compression Ignition Engine Using Alternative Fuels, Borgnakke 4.11 Auto-ignition Characteristics of Military Fuels (ULSD, JP-8 (50), JP-8 (31), S-8): Effect of Charge Temperature and Pressure, Henein 4.16 Cold Start Testing of a Production High Power Truck Engine with Different Alternative Fuels, Taraza/Janson A.9 Autoignition Characteristics of Military Fuels IQT™ (Ignition Quality Tester), Henein Hybrid Powertrain 1.8(1) Control and System Integration of an SOFC/GT-based APU Systems, Sun/Oh 1.8(2) Hardware Simulation of 5kW-Class SOFC/Gas Turbine Hybrid Power System, Sun/Oh 4.4 Electrified Propulsion Systems - Integration of e-Motors and Sizing Based on Thermal Load, Filipi A.11 Fault Tolerant Hydraulic Hybrid Systems, Filipi

18TH ANNUAL AUTOMOTIVE RESEARCH CENTER CONFERENCE

Lift

CSE  1670Session  A

CSE  1690Session  B

Dow  1013Session  C

Refreshments

CSE  Building  South  Entrance

Posters

Exhibitor

Session  C

Reliability/Survivability

Vehicle  Control  &Terramechanics

JP-­‐8  Studies  &  IC  Engines

Human  Modeling

Thermal  Dynamics/Management  

&  Electrical

Energy  Storage

Design,  Optimization,  VV&A

1.71.91.21.151.121.132.4

4.3  4.6(1)4.6(2)4.11A.94.16

1.6A.74.151.104.84.9

4.134.124.14 Hybrid

Powertrains

1.8(1)1.8(2)4.4A.11

3.1,  3.2,  3.4,  3.5

5.1,  5.2(1)(2),  A.19,  5.3,  A.14,  5.5,  5.6(1)(2)

2.5A.13

Thermal Dynamics/Management & Electrical Energy Storage 1.6 Neutron Imaging of Lithium Ion Batteries, Stefanopoulou/Siefel 1.10 Ultracapacitor Energy Storage for Improving Fuel Economy and Extending

Battery Life in Heavy Vehicles, Vahidi 4.8 High Energy Density Asymmetric Capacitors, Thompson 4.9 Thermoelectric and Vapor Compression Cooling for Hybrid Electric

Vehicles, Wagner 4.12 Computationally-Efficient Finite-Element-Based Thermal Models of

Electric Machines, Hofmann 4.13 Powertrain Thermal Management – Experimental Study of Battery Cooling

in Hybrid Electric Vehicles, Ma 4.14 Improved Density and Temperature Range of In-vehicle Power

Converters: High Frequency Power Supplies for High Temperature Environments, Rivas

4.15 Stability of Electro-Thermal Planar Dynamics in Large-format Prismatic Li-ion Battery Cells, Monroe

A.7 Parameterization and Validation of an Integrated Electro-Thermal Model for a Cylindrical LFP Battery, Stefanopoulou

Design, Optimization, VV&A 5.1 Validation of Models with Multivariate Functional Output,

Kokkolaras/Hulbert 5.2(1) Vehicle Structure and Seating Design for Minimizing Casualties,

Papalambros/Kokkolaras 5.2(2) HEV Powertrain Architecture Exploration Using Bond Graphs, Papalambros/Kokkolaras 5.3 Development and Laboratory Implementation of an Accelerated Testing Method for Vehicle Systems using Time-Dependent Reliability / Durability Principles, Mourelatos 5.5 Battery Thermal Packaging Design, Fadel/Wiecek 5.6(1) UGV System Reliability Modeling & Improvement: Mission Energy Prediction for UGVs by Real-time Measurements and Prior Knowledge, Ulsoy/Jin 5.6(2) UGV System Reliability Modeling & Improvement: Passive-Assist Device Optimization for Enhanced Joint Performance, Ulsoy/Jin A.14 Reliability Assessment and Optimization of a Smart Charging Microgrid, Mourelatos A.19 Crowdsourcing for Optimal Vehicle Design, Papalambros/Gonzales/Kokkolaras

UM Autolab Tour, May 21, 2012 at 3:15

ACCESS engine; transient

Quantitative Laser Diagnostics Lab

Hybrid Powertrain Laboratory

Low temperature partially premixed

diesel engine

Hydraulic valvetrain HCCI/SACI engine

EGR Heat Exchanger Deposits

ARC Heavy Duty Engine Laboratory: Fuels and Controls

Research

Scalable Battery Systems Lab

ARC Internet Distributed

Powertrain Controls

ACCESS engine; steady-state

GMCRL boosted HCCI engine

Gasoline DI Advanced

Combustion Engine

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UM Autolab Tour, May 21, 2012

•  Hybrid Powertrain Laboratory; 1070 Autolab •  Prof. Huei Peng •  An education lab developed to support two courses: modeling and control

of hybrid electric vehicles, and internal combustion engines. The lab was designed to test small engines and electric machines and study their integration into hybrid powertrains through simulations

•  Scalable Battery Systems lab; 1082 Autolab

•  Prof. Anna Stefanopoulou, Dr. Jason Siegel •  Electrothermal Battery Diagnostics, Dynamics and Management •  Observability of Cell-to-Cell Imbalance in Battery Packs •  Neutron Imaging for In-Situ Validation of Electrochemical Cell models

•  ACCESS (Advanced Combustion Controls – Enabling Systems and Solutions) for

High Efficiency Light-Duty Vehicles, 1114 Autolab •  Dr. Stani Bohac, Dr. Erik Hellstrom, Prof. Anna Stefanopoulou

Development of highly capable and flexible advanced combustion modes and control concepts to achieve at least 30% fuel economy improvement while meeting SULEV emissions in a commercially viable light-duty vehicle without compromising performance.

•  Hydraulic valvetrain HCCI/SACI engine; 1122 Autolab

•  Prof. Margaret Wooldridge, Dr. George Lavoie, Dr. Jason Martz •  Investigate HCCI and SACI advanced combustion modes •  Explore fuel effects on HCCI

•  GMCRL boosted HCCI engine,1122 Autolab •  Prof. Volker Sick, Dr. George Lavoie •  Investigate HCCI under boosted conditions

•  ACCESS (Advanced Combustion Controls – Enabling Systems and Solutions) for High Efficiency Light-Duty Vehicles, 1089/1095 (steady-state)

•  Dr. Stani Bohac, Dr. Erik Hellstrom, Prof. Anna Stefanopoulou •  Modeling and Control of Multi-Mode Combustion •  Characterizing and Controlling High Cycle-to-Cycle Combustion Variability

•  EGR Heat Exchanger Deposits, 1103 Autolab •  Dr. John Hoard •  Engine and visualization test stand for study of diesel EGR cooler fouling.

•  ARC Heavy Duty Diesel Engine 1111/1105 Autolab

•  Angela Violi, Jason Martz, Claus Borgnakke, John Hoard, Dohoy Jung •  Combined simulation and experiments, focused on understanding the

chemical/physical causes of cetane number variation in JP-8, development of an improved JP-8 kinetic mechanism and chemical surrogate(s).

•  DDC Onboard Diagnostics and Controls •  Anna Stefanopoulou, Jeff Cook, Jason Martz •  Real time controls for fuel variability with advanced sensing •  Diagnostics and On-board Calibration of EGR Recirculation

•  ARC Internet Distributed Powertrain Controls, 1103/1105 Autolab •  Dr. Tulga Ersal •  Internet-enabled framework to integrate geographically distributed

hardware-in-the-loop setups in real-time for concurrent, high-fidelity, systems-level engineering with application to powertrain controls

•  Quantitative Laser Diagnostics Laboratory, 1123 Autolab

•  Prof. Volker Sick, Dr. David Reuss •  High-speed imaging for turbulence, misfire, and boundary layer studies,

Large-Eddy Simulation Working Group

18TH ANNUAL AUTOMOTIVE RESEARCH CENTER CONFERENCE

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North Campus Map

Technical Symposia & Poster Session

Lift

CSE  1670Session  A

CSE  1690Session  B

Dow  1013Session  C

Refre

shmen

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CSE  Building  South  Entrance

Posters

Exhibitor