ME 6105 HW3 Elevator Final

7/27/2019 ME 6105 HW3 Elevator Final

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ME 6105 Modeling and Simulation

HW3: Energy-Based Systems Modeling in Modelica

Simulation Based Design of a High-Speed

Elevator System

Memebers:

Bo Yang

Fei Zhao

Xiayun Zhao

Sen Yang

Spring 2008

03-04-1008


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Table of Content

Task 1: Define your goals and problem domain ............................................................................... 3

Problem Domain ....................................................................................................................... 3

Simulation Scenario .................................................................................................................. 4

Task 2: System and Simulation Specification ................................................................................... 5

Systems ..................................................................................................................................... 5

Assumptions .............................................................................................................................. 6

Task 3 Create your models in Dymola .............................................................................................. 7

Sheave ....................................................................................................................................... 7

Car & Counter weight ............................................................................................................... 8

Brake System ............................................................................................................................ 9

Voltage Controllable Source ................................................................................................... 10

DC Motor ................................................................................................................................ 11

Sensor System ......................................................................................................................... 12

Motor Controller ..................................................................................................................... 12

Task 4 Verification .......................................................................................................................... 14

Sheave-car-counter weight system .......................................................................................... 14

Brake System .......................................................................................................................... 15

The Electrical System ............................................................................................................. 16

Task 5 Experimentation and Interpretation ..................................................................................... 19

Experimentation ...................................................................................................................... 19

Interpretation ........................................................................................................................... 19

Task 6 Lessons Learned .................................................................................................................. 20

References ....................................................................................................................................... 22


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Task 1: Define your goals and problem domain

Problem Domain

Elevator systems are typical examples for complex mechatronic systems. High

safety-relevant demands are special properties of these systems. Practical experiments for the

function validation of developed components (subsystems) and their interactions are

mandatory necessary. However, the opportunities for experimental system optimization are

often limited by the system size and complexity. Experiments with system versions are too

expensive or impossible because of safety requirements. Furthermore, the investigation of

relevant operating conditions is very complicated. This difficult design situation can be

improved by accompanying system simulations.

Machine

Room

Top Of

Hoistway

Inside

Elevator

Outside

Mounted On

Elevator

Elevator

Entrance/Hall

way

Elevator

Pit/Bottom of

Hoistway

-Elevator

Control Systems

-Motors

-Handset

Telephones

-Machine Room

Lighting

-Brake Limit

Switches

-Final, Normal

& Slow Down

Switches

-Access Over

Travel Limit

Switch

-Main &

Auxiliary Car

Stations

-Car Position

Indicators

-Traveling

Lanterns

-Cab Lighting

-Car Top

Inspection

Station

w/Worklight &

Receptacle

-Magna-Track

Selector System

-Car Bottom

Worklight

&Receptacle

-Retiring Cam

-Cab Ventilation

Fan

-Door Interlocks

-Hall Stations

-Multi Light

Position

Indicators

-Hall Lanterns

-Access Switch

Stations

-Final, Normal

& Slow -Down

Switches

-Pit Switch

-Pit Worklight

and GFCI

Receptacle

Table 1 Components of a Typical Elevator System

A complete commercial elevator system contains many sub-systems and componentsas shown in Table 1. Due to the size of the project, we abstracted a real elevator system into a

simple one consisting of components shown in Table 2. Instead of model an elevator that has

complete features, we focus on the motional aspects of a high-speed elevator that deliver

excellent performance in terms of travel efficiency and comfort. Therefore, we mainly model

the core parts of the mechanical system and the electrical system within an elevator that

deciding the motional performance without considering others such as the alarm, door,

lanterns, etc.


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Mechanical System Electrical System Environment Factors

Car

Counter Weight

Rope

SheaveBrake

Motor

Motor Speed Control

Sheave Friction

Wind Resistance

Table 2 Composition of the Abstracted Elevator System in our Model

Simulation Scenario

In Homework 2, we defined the design objectives as MAXIMIZE EFFICIENCY and

MAXIMIZE PASSENGER COMFORT. Based on these objectives, a set of attributes were

presented such as maximum speed, running time and maximum acceleration as to measure theperformance. Accordingly the simulation scenario will mainly focus on testing different

alternatives of the components in Table 2 to find the combinations that contribute to good

performance based on measurement of those attributes. For example, given that the elevator is

going to travel from 1st floor to 10th with certain weight in the car, we will measure the travel

time, maximum speed, maximum acceleration and other attributes in the simulation under

different configurations of the system components.

Specific questions to ask during simulation include:

- When integrating different components which work properly as individuals, will the

whole system perform as expected?

- What is the best configuration of the sub-systems given the two design objectives?

- Among the different sub-systems and components, which have the biggest influence on

the travel performances in terms of the efficiency and comfort?

- What are the inter-relationships among sub-systems that must be considered when

selecting alternatives?

- In terms of achieving basic performance of the elevator, whats the minimum complexity

required for the motor control mechanism?

- How well the design objectives could be realized in our model compared to real systems

in the market?

In answering those questions, we employ a bottom-up approach by developing the

components individually with alternatives included, integrating them and then testing the

system performance under different configurations.

In the context of design problem defined in HW2, the design objectives will all be

considered in the simulation the influence diagram is well followed. But the original plan on

design alternatives was modified in the simulation to reduce the complexity.


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Task 2: System and Simulation Specification

Systems

Based on the major components in Table 2 we selected to model, an overall system

structure is shown in Figure 1 indicating how the major components are integrated as an

elevator system. Basically the whole system is modeled by integrating three sub-systems: the

electrical system, the mechanical system and environment factors.

Figure 1 System Structure of our Elevator Model

As shown in Figure 1, the electrical system mainly refers to the motor circuits, a

circuit controlling its voltage input, and the sensors that provides input to the control system

by monitoring the status of the mechanical system. We use a DC motor in our model. And the

control is made by changing the voltage input to the motor. The mechanical system includes a

car, a counter-weight, a rope connecting the two, a sheave that drive the rope to roll from the

car side to counterweight or vice versa, and a brake system that helps to stop the car. The

environment factors modeled in our model are two wind resistances imposed on the car and

the counterweight respectively. There are other environment factors such as the travel

distance input and the passenger weight which are taken as input not shown in Figure 1.

Motor

Motor Control Circuit

CarCounter

Weight

Wind

Resistance

Brake

System

Sensors

Rope

Sheave

Wind

Resistance

Roll

Control

Voltage Input

- Travel Distance

- Weight Carried

Rotation

Speed

Counter-act Counter-act

Connec

Counter-actDrive

Monitor

Electrical System Mechanical System


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Assumptions

Phenomena already included in our model:

- Variable passenger weight

- Variable traveling distances

- Wind Resistance on the Car and the Counter-weight

- Friction within the Sheave

Phenomena abstracted away in our model:

- Routing algorithm and passenger detection: As our focus is on the travel efficiency and

comfort, instead of modeling random customer arrival, we take both the passenger

weight and travel distance as deterministic input in each experiment.

-The friction on the moving car and the counter-weight

- Complexity in the motor control system: in real elevator systems, the mechanisms in

motor control are usually much more complicated than ours incurred by AC input,

variable voltage and frequency, etc. In our model we use a DC power and a DC motor

controlled by adjusting its voltage input.

Phenomena to be included:

- Stiffness of the rope


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Task 3 Create your models in Dymola

In this section we are going to introduce the Dymola models of the key components in

our model and their verification accordingly. In Figure 2 is an overview of the elevator systemmodel in Dymola corresponding to the system structure in Figure 1. In this section we are

going to introduce the major component one by one.

sheave=0.2

fixedfixed1=0

fixed2=0

W...

W...

counterWeight

I

Tau

S

M...

MC...

S

speed...S...

I0

S

P1

damper_Brake

d=0.15

10

Desired_Distance

Approac...

Volt...

car

Figure 2 Overall Elevator Model in Dymola

Sheave

The sheave model is modified from the Winch model Chris provided in class. We

added two more ports in the model. Flange_damper is set to transfer rotational friction from a

damper, and also works as a brake to the whole system (see details in Brake component).Flange_CWeight is a port to carry the counter weight, in addition to another port Flange_Car.

Related equations for the movement are shown in Figure 3.


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Figure 3 Our Sheave Model in Dymola

Stiffness has not been considered in the current model. Due to the similarity of system

control, the total length of rope is set as constant.

Car & Counter weight

Car and Counter Weight are modified from sliding mass component. All the mass of

Car and Counter Weight are suspended by the tope on sheave. According to literature, typical

mass of a car is 1600 kg, and standard max load is 2000kg. The mass of counter weight is

usually designed as the sum of Car and half of max load, which is 1600+2000/2=2600kg.

Therefore, in the simulations in Task 5, such weight setting is regarded as standard.

During the traveling period, wind in the elevator shaft provides resistance, which is a

function of car velocity. Based on the homework one and literature review, the wind

resistance function has been defined aswind_resistance= -k*air_density*vel_ms^2*sign(vel_ms), where k is set to be 0.05 as

the default condition.


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f

force

v

speedSensor

product

k=-0.05

w indConstant

sign1

si...

product1k=1.29

AirDensity

flange_a1

Figure 4: Dymola Model of Wind Resistance

Brake System

Although the motor is controlled to decelerate before arriving, a brake system is stillnecessary to assist a timely brake. We design a brake system by ourselves. The principle of

the brake system is to increase rotational friction at the sheave shaft when elevator car is

approaching its destination, so that its velocity will decrease very fast to a full stop.

The brake system consists of two components: Is_Approaching and

Damper_Brake.

(1) Is_Approaching

This component checks whether the elevator car is approaching a customer-specified

travel distance (S0).

Components Name Description

RealInput Car_s real-time position of elevator car

RealInput S0 desired distance specified by passenger

BooleanOutput Is_Approaching True: if the car is close enough to its destination

Figure 5 Dymola Model of the Component Is_Approaching


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Note: we define approaching as the remaining travel is ErrorCoefficient * Desired

Distance. Here, the ErrorCoefficient is a small number (i.e., 1e-4)

(2) Damper_Brake

This component is based on Modelica.Mechanics.Rotational.Damper in Dymola

Library.

Graphically, we add an input connector Is_Stopping to signal the damper that it is

time to increase tau.

We specify a sufficiently large damper coefficient (i.e., 5e3) for the output torque (tau)

at flange_b; hence the rotational resistance increases significantly to brake. The graph and

Modelica language of the component - Damper_Brake is shown as below in Figure 6.

Figure 6Dymola Model of the Component Damper_Brake

Voltage Controllable Source

The voltage output of this component has a range from -120V to 120 V, which is

controlled by two inputs: variable resistance and a switch signal.


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ground

constantVolta

ge=120

+

-

controlledIdealInter...

cVariableResis

t...

powerSensor

P

integrator

I

k=1

p1

n1

RS

Figure 7 Dymola Model of the Voltage Controllable Source

DC Motor

DC Motor is composed of resistor, inductor, eMF, inertia and damper, which also has

power and energy output.

L=0.01

inductor

eMF

k=3 inertia

J=0.2

fixed=0

dam

per

d=

0.3

powerSensor

P

R=0.05

resistor

addadd+

inte...

Ik=1

abs2

flange_b1

n1

p1

power

work

Figure 8 Dymola Model of the DC Motor


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Sensor System

The sensor system gets the weight of car and counterweight to calculate the inertia of

them and the torque exerted to the shave because of their gravity. Also the current position of

the car is outputted.

add

+1

+1

add

+

+1

+1

product

R

k=0.2

product1

add1

+1

+1

add1

+

+1

+1

product2

k

k=-1

product3

g

k=9.81

product4

s

positionSensor

m_Car

m_CW

I

Tau

s

Car_s

Figure 9 Dymola Model of the Sensor System

Motor Controller

An elevator has a desired running curve as following: first accelerate at a constant rate,

then run at a constant speed, after that decelerate at the same rate as in the first step, finally

adjust the position of the car. The maximum acceleration is limited by the comfort

requirement of the elevator. The maximum speed is defined by the design of mechanical

system and energy consumption. Also the final position of the car and the jerk because of start

and stop needs to be carefully controlled. To achieve this requirement, the torque of the DC

Motor is computed in the entire process.

ma x

ma x

accelarate

0 constantspeed

decelarate

a

a

a

=

car car T aI T =

The resistance in the system should be (Modelica codes shown in Figure 11):

V LB K R K

T J B

=

+ +

&

&


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0 1 2 3 4 5 6 7 8 9 10-2

-1

0

1

2

3

4

5

6

7

8

9

10

car1.s [m] car1.v [m/s] car1.a [m/s2]

Figure 10 Typical Running Curves in Simulation

Figure 11 Modelica Codes of the Resistance in the Motor Controller

amax

- amax

Vmax

astart astop


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Task 4 Verification

Sheave-car-counter weight system

Taking off the power and control system, Figure 12 shows the major structure of the

traveling sub-system.

sheave=0.2

fixedfixed1=0

fixed2=0

W...

W...

car1

counterWeight

damper

d=0.5

Figure 12 Structure of the Travling Sub-system

Condition 1: No wind resistance and damper friction

In this condition, the mass of car and counter weight have been set as different values

(parameters of two cases are shown in the following table), and there is no power supply to

the sheave. So the counter falls because of bigger mass. Two case studies have been done, and

have been compared to the theoretic results for system verification.

Case No. CW/kg Car/kg t/s s/m

1 100 0 1.56412 12

2 100 50 2.70914 12

Figure 13 Traveling Distances of the Counter Weight/ Car within the Two Cases

In Case 1, the counter weight drops as a falling object, therefore the theoretic travel

time for 12m is:

Case 1

Case 2


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In Case 2, the tension of rope T=200g/3, therefore the acceleration of the car is

So the theoretic travel time for 12 m is:

All the simulation results in both cases perfectly match the theoretic results; therefore

the transmission of sheave, car and counter weight has been verified.

Condition 2: Wind resistance

Based on the wind resistance definition equation shown below,

wind_resistance= -k*air_density*vel_ms^2*sign(vel_ms)

A parameter study on the wind resistance coefficient k has been done. (Simulation

results shown as in Figure 14)

0 1 2 3 4 5

0

4

8

12

[m]

car1.s car1.s

0 1 2 3 4 5

0

4

8

12

[m]

car1.s car1.s

Figure 14 Traveling Distances in Simulation under Different Parameters

Observations on parameter study:

(1) With growth of k value, the increasing slope of car velocity decreased.

(2) When the abstract value of k is large enough, acceleration of the car maintainsconstant after a short time.

All these observations match the real wind resistance, but it is also necessary at the

same time to find the real data based on literature.

Brake System

In our 4th version model EleCableCar_M4, we have two test examples for

verification of the brake system. One is CableCarSystem_Brake, and the other is

CableCarSystem_NoBrake.

K=-0.5

K=-5

K=-10

K=-20


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As we can see from the following two examples, the car will stop at a point very close

to the customer specified distance (8m). But it is only 7.99938 m, not exactly 8m. Fortunately,

this problem has been addressed by imposing a motor control to brake. (For details, see the

part of verification of whole system) In Figure 15, we can verify that the brake system do

assist to brake significantly.

a) Without Brake b) With Brake

Figure 15 Traveling Distance Curve without/with Brake

Figure 15 Adding Brake into the Whole Elevator System(Shown in the red circle)

The Electrical System

Because the electrical should be designed with regards to the mechanical system

respond, it is verified using a mechanical system without friction first then some

compensation are added to the controller to account in the effect of friction. The system is


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tested at full load (car mass is 3600kg) and the car will be pull up for 10 meters.

Test: 1.Motor drive. 2. Rotational damper at sheave

sheave=0.2

fixedfixed1=0

fixed2=0

W...

W...

coun

terW

e

ight

I

Tau

S

M...

MC...

S

speed...S...

I0

S

P1

damper_Brake

d=0.15

10

Desired_Distance

Approac...

Volt...

car

Figure 16 System Overview with the Electrical System

0 1 2 3 4 5 6 7 8 9 10

0.00

0.04

0.08

0.12

0.16

0.20

0.24

0.28

0.32

0.36

0.40

0.44

controller1.R [Ohm] controller1.switch

Figure 17 Change of the Resistance in the Controller in Simulation


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0 1 2 3 4 5 6 7 8 9 10-1100

-1000

-900

-800

-700

-600

-500

-400

-300

-200

-100

0

100

voltage_controllable_Source.p1.v [V] voltage_controllable_Source.p1.i [A]

Figure 18 Voltage Controllable Source

0 1 2 3 4 5 6 7 8 9 10

-3200

-3000

-2800

-2600

-2400

-2200

-2000

-1800

-1600

-1400

-1200

-1000

-800

-600

-400

-200

0

[N.m

]

dC_motor.flange_b1.tau

Figure 19 Torque Output of the DC Motor in Simulation

Observations:

From Figure 17~19, we can see that by adjusting the variable resistor in the control

circuit (Figure 17), the current input to the motor and thus the torque output are changed

accordingly to represent the accelerating, constant speed and decelerating processes in a

traveling process.


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Task 5 Experimentation and Interpretation

Experimentation

In simulating the whole elevator system, we use a set of parameters of a typical

elevator design and the controller is optimized based on them. We assume the elevator lift the

maximum load up for a typical distance. All the parameters are shown in Table 3. Building on

the base configuration, in each experiment, we changed one of the alternative components to

identify the relationships between the design alternatives, chance event and the design

objectives (Table 4).

Base Configuration

Parameters K L V_max A_max Brake H M

Values 3 0.01 2 1 5000 10 3600

Performance

Attributes E[J] a_start[m/s2] a_brake[m/s2] T[s]

Values 102004 -1.58098 -0.89457 7.72

Table 3 Base Configuration and Performance

Parameters Alternative

Values

E[J] a_start[m/s2] a_brake[m/s2] T[s]

K 5 99274.4 -1.58098 -1.30259 8.28

L 0.005 100191 -1.58098 -1.38203 9.04

V_max 1 103415 -1.58098 0.893013 13.96

A_max 0.5 100546 -1.58098 -1.6803 9.16

Brake 2500 102006 -1.58098 -0.451355 7.88

H -10 1139.48 -1.58098 -0.92734 8.08

-5 1138.1 -1.58098 -.927361 5.44

5 52850.5 -1.58098 -.902585 5.88

M 1600 940.352 2.33294 -1.37104 7.25

Table 4 Experiments by Varying from Base Configuration

Interpretation

First, For the same load and running distance, since the controller is optimized for the

base configuration. So the running time is the shortest in this case.

Increase K and reduce L will decrease the hysteresis of the system, so the energy

consumption is smaller. When then the controller is optimized, the time and energy

consumption will both be smaller, the system has a better performance than currentconfiguration. However they are limited by motor design.


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We expect the energy consumption will decrease as the maximum speed decrease since

the kinetic energy will be smaller also friction loss will be smaller, we observed this

phenomenon when the weight of the car is equal to the counterweight. While in this case, the

energy consumption is little higher, I think, first the kinetic energy only counts for 1% of the

total energy consumption, so this effect is not significant. Second, The controller is working

worse than the base case, more energy is dissipated.

Smaller maximum acceleration will lead to smaller energy consumption confirms with

physical law, Since the average speed is smaller then friction loss is smaller. Also average

current is smaller since the drive torque is smaller, so dissipation is smaller

Smaller brake force will lead to smaller final acceleration but longer running time and

larger position error.

In this configuration the mass of car is much larger than that of the counterweight. So

when the car is going down, there is no energy consumption in ideal case. The small values in

this model is because of transient effect.

Half the lifting distance will not lead to half time and energy consumption, a little bit

more.

Smaller mass will reduce hysteresis of the system and lead to smaller running time.

But will also have larger acceleration at start and stop.

Task 6 Lessons Learned

Bo Yang

Now I can understand Modelica is a programming language like C++. It also hasvariable declaration If then, Do while and so on. Also the modeling style is just like write

code and debug. However the difference is also significant. First is the use of =, I need

always remember it is equal no assign value as in other programming language. So one

variable can only be define once, also there should not be any unused variable, otherwise

singularity will always accompany you. Second is unit. Most of the variables have unit, you

need to define it, and make sure the connector has the same type when connecting two blocks.

So I really like real input and output.

I designed the control scheme and the control system. There are so many exceptions

need to be considered. Whether maximum speed can be reached, how to handle a negative

driving torque, there is always new problem when you think you have finished it. Then

another line needs to be added to handle it. As time going on, the controller is getting longer

and longer, but also better and better. Hysteresis is another problem. I am trying to add

compensation to handle it. But it change with many parameters and very hard to predict, so

the large range result is not very good.

I can see my progress in grasping the Modelica and Dymola. In a new model, most of

the problems can be avoided,

Fei Zhao

In this assignment, my work focuses on the mechanical system, including sheave, car& counterweight, and all resistance and sensor components. Firstly, some literature review


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helps me gain some fundamental theory and general structure of an elevator, i.e. how the car

is carried up by a motor, how counterweight works to balance the system and reduce the

torque, how the controller makes decision on acceleration and stop, etc. This knowledge and

experience also works in architecture field, for instance the Building Automatic System

(BAS).

Besides, I have more sense on DAE and equation singularity after manipulating the

existing Modelica code of components. Finally I found the advantage of adding code in

Dymola models, and do not prefer to use many components to build an expression as before. I

also learnt that using global variables is a bad idea in Dymola modeling, instead we can use

sensors to transfer variable, and set parameters at the top level.

Also, according to our team regulation, I played the team leader role this time. I

scheduled and organized all the group meetings and set deadline for every step of work. We

tried to be proactive but still did not finish all the proposals raised in brainstorming session,

due to poor time management. In the next homework, we will try to add stiffness and other

features which may also cause uncertainty to the system.

Last but not least, I am learning English and trying to enhance my academic writing

skills.

Xiayun Zhao

In homework#3, I mainly worked on the cable-car system design, including the design

of sheave system and brake system. After converting

Modelica.Mechanics.Rotational.IdealGearR2T to a sheave in elevator system, I was excited to

see the variability and feasibility of Modelica.

Many problems came out when I used Dymola. Most were "singularity" problems. For

example, I added a Flange_a named "flange_damper" in the "sheave" component. Initially, I

only defined an equation of flange_damper.tau in Modelica language. Error came up with

singularity! I was frustrated because I couldn't think out another equation at that time. After

checking the info of Flange_a, I made a good guess that flange_damper.phi should also been

defined, although it is equal to flange_motor.phi.

Thanks to the substantial Dymola practice, I become more familiar with Modelica

language. Besides, I have a further understanding about DAE in Dymola.

I am content with my endeavor in the homework. However, I know well that my

modeling skills need to be improved. Take the brake system design for example. Next time, I

would like to explore "Modelica.Mechanics.Translational.Stop" and/or"Modelica.Mechanics.Rotational.Brake", instead of modifying damper. I think it could be

better to make full use of professional brake components in Dymola library.

Finally, I really enjoyed our groupwork. It is nice to work together and learn from each

other.

Sen Yang

In Homework 3 I became more familiar with the operations under the environment

Dymola and Modelica including how to program customized component by adapting standard

component in the library and how to interpret the result to identify the problems in the model.


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I learnt the overall process of modeling and simulation using Dymola and Modelica. It

was great that we develop the initial model of the system and refine it to a level with many

details. I learnt that a scaffolded plan of actions is a good way to start modeling from scratch.

By starting from the simplest system and adding uncertainty and complexity gradually, we

handle the complexity successfully although we need to do more.

I also learnt how to decompose a system into sub-systems and then integrate them into

a whole. The top-down and bottom-up approaches are extremely helpful in a team project.

References

[1] W.D. Zhua, L.J. Teppob. Design and analysis of a scaled model of a high-rise, high-speed

elevator. Journal of Sound and Vibration 264 (2003) 707731

[2] Yuliang Leon Zhou. Modeling and Simulation of Hybrid Electric Vehicles. 2005

[3] Peter Schneider, Erich Huck, Peter Schwarz. A Modeling Approach for Mechatronic

Systems - Modeling and Simulation of an Elevator System. XI. Intern. Symposium in

Theoretical Electrical Engeneering, Linz, Aug. 19. - 22, 2001

[4] Yan Chen and Weidong Zhu. Dynamics and Control of Elevator Systems. Poster in

Dynamic Systems and Vibrations Laboratory, University of Maryland Baltimore County.

[5] Daniel Castellanos, Rainer Domer. System-Level Modeling and Simulation of an

Elevator Control System. Technical Report CECS-07-04 June 25, 2007.

Documents

ME 6105 HW3 Elevator Final