MTU - MEEM - Template
Transcript of MTU - MEEM - Template
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Bo Chen, Ph.D.Dave House Associate Professor of Mechanical Engineering and
Electrical EngineeringDepartment of Mechanical Engineering - Engineering Mechanics
Department of Electrical and Computer EngineeringMichigan Technological University
July 4th, 2013
Model-Based Design and Hardware-in-the-Loop Simulation
for Clean Vehicles
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Outline of Presentation
Background and Motivation Model-Based Approach for Embedded Control
System Design Hardware-In-the-Loop (HIL) Simulation Single Shaft Parallel Hybrid Electric Vehicle (HEV)
and Electronic Control Unit (ECU) Network HIL Simulation of Parallel HEV Conclusions
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Background and MotivationVehicle Population• 750, 000, 000+ vehicles in the world• Expected 2 billions by the year of 2020
Fuel Consumption• The transportation sector in the U.S.
accounts for two-thirds of our petroleum use
Environmental Emission• Transportation produces 33% of US CO2
output
Technologies & Challenges• Hybrid, electric, fuel cell , and renewable energy
vehicles• Complex powertrain and control system
Fuel Economy& Emission Standards
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Model-Based Approach for Embedded System Design
Conventional V-model: a plan-driven process. The design process follow the defined development stages in order
Model-based Design: provide an integrated environment for design, simulation, automatic code generation, and validation.
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Salient Features of Model-Based Embedded System Design Approach
Platform for representing entire system: control strategy and plant models Graphical representation: use graphical language to
describe implementation details Time saving: minimize software development time and
maximize software re-use. No hand coding, production quality code is automatically generated Integrated development and validation cycles Communication among the team members is made easier
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Hardware-In-the-Loop (HIL) Simulation
ActuatorsSensors
Automotive Plant Model
Signal Conditioning
Output Drivers
Micro-controller
Electronic Control Unit
Real World
dSPACE HIL Simulator
MotoTronEngine ECU
MicroAutoBoxMotor ECU
Electrical Signal Interface
HIL System
• Generate an environment where ECU assumes that it is running with a real physical system.
• HIL simulator simulates the physical system that is under test. It generates plant sensor signals and capture actuator signals from ECU.
• Used to test control strategies to be implemented on ECUs.
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dSPACE HIL I/O Interface
PHS-Peripheral High Speed
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Model Development and HIL Simulation Process
Model Development Parameterization Updating
ModelAuto-code Generation
Downloading to ECUs
Online CalibrationRecording
Colors indicate the different softwares used in the steps. Blue : Simulink/Stateflow/dSPACE blocksets/Real-time Workshop
Model building, modification, and auto-code generation Yellow : dSPACE ModelDesk
Model Parameterization Red : dSPACE ControlDesk Next Generation
Real Time Calibration, Data Recording, File Export
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Single Shaft Parallel HEV PowertrainArchitecture and ECU Network
ICE PMSM
Battery
Inverter
Gearbox
Final Drive
Clutch1 Clutch2
Automatic Transmission
Motor ECU Transmission ECU
Hybrid ECU
Engine ECU
Driver Environment• Vehicle level
ECU:
Hybrid ECU
• Low level ECU:
Engine ECUMotor ECUTransmission ECU
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dSPACE Parallel HEV Model
Actu
ator
sig
nals
from
EC
U
Sens
or s
igna
ls fr
om E
CU
From RTI Blocks
To RTI Blocks
dSPACE HIL Simulator
Sensor SignalsActuator Signals
From MotoTron ECM:• Ignition angle • Injection angle and
duration• Throttle valve, EGR
valve, pressure control valve position, and PWM control signal
To MotoTron ECM:• Engine torque request• Engine speed• Engine keys• Intake manifold
pressure and temperature
• Coolant temperature• Rail pressure• ……
From MicroAutoBox II:• Three phase PWM
signals
To MicroAutoBox II:• Motor Torque
Request• Motor Speed• Three phase
current• DC bus voltage
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Parameterize HEV Model Using ModelDesk
Environment
Vehicle DynamicsDrivetrainEngine
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HIL Setup for the Parallel HEV
dSPACE HIL simulator MicroAutoBox II for motor controller MotoTron 128 pin ECM for engine
controller
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Driver Controller
Vehicle Plant
Hybrid ECU
MicroAutoBox II
Motor Controller
HIL Simulator
APP
BPP
ICE Torque Request, Key
EngineActuator Signals
SimulatedEngineSensor Signals
Vehicle Key
PWM Signals
Vehicle Reference Speed Actual Vehicle Speed
Motor Torque Request, Motor Speed, 3 phase current, DC bus voltage
PWM Signals
Motor Speed, 3 phase current, DC bus voltage
Motor Torque Request
SOC, Transmission Speed, Current Gear Level, Engine State
Transmission ECU
Gear Level, Clutch Command
Mechanical Brake Torque Request
Gear Ratio,Clutch Command
Shifting Maneuver
Simulation Models
Engine Controller
MotoTron
Measurable Engine Signals
CapturedEngineActuator Signals
Signals between Engine Controller and Vehicle Plant
Sensor signals:• AFM through throttle• engine speed• intake manifold
pressure and temperature
• EGR valve position• coolant temperature• injection pressure…
Actuator signals:• Ignition angle and
duration• injection angle and
duration• throttle valve, EGR
valve, and pressure control valve position PWM control signal
Signal for the Parallel HEV
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Hybrid ECU
Electric Only
Engine Only
BatteryCharging
Hybrid
Reg
ener
ativ
e B
raki
ngBPP>0
APP>0
SOC>Max_SOC and T_Bat<Max and TrqRequest<MaxMotorTrq
SOC<Min_SOC or T_Bat>Maxor TrqRequest>MaxMotorTrq
SOC>Max_SOC
T_Bat>Max
T_Bat<Max
SOC<Min_SOC
• Vehicle operating mode control• Split powertrain torque between engine and electric machine to achieve
maximum fuel economy• Control regenerative braking to recover as much energy as possible
and ensure braking performance at the same time
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Vehicle Mode and Energy Flow
(a) Electric only mode
(b) Battery charging mode
(c) Engine only model
(d) Hybrid mode. (e) Regenerative
braking mode
(a) (b)
(c)
(d) (e)
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Overview of Engine ECU
Homogenous Mode
Stratified Mode
Engine Operation
Starter switch
Ignition switch
Engine Speed
Relative Airmass
Intake Pressure
Intake Temperature
Engine Torque Setpoint
Engine State
Coolant Temperature
Engine State
Relative Airmass
Engine Torque setpoint
Engine Torque
Combustion Mode Switch Airpath
Rail Pressure Control
Angular Processing
Unit
RailPressure
λ setpoint
ṁthrottle
Rail Pressure
ṁthrottle
Injection Signals
Spark Signal
Throttle position
Spark Signal
Throttle position
Intake PressureAmbient Pressure
EGR %
Turbocharger Control Signal
EGR Control Signal
Rail PressureMean Injection
quantity setpoint
Fuel Metering Unit
Pressure Control Valve
Cylinder wiseCrank angle
ENGINE ECU SUBSYSTEMS
Injection Signals
• Injection signals
• Ignition signals
• Throttle position
• Turbocharger control signal
• EGR control signal
• Rail pressure control signals
• Engine position
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Motor Controller
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dSPACE Experiment Software - ControlDesk
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# Vehicle Mode0 Battery charging1 Engine only2 Hybrid mode3 Motor only4 Regenerative breaking
Simulation Results: Vehicle Mode Control• Hybrid ECU control logic is
modified to avoid frequent mode change.
• Improved vehicle performance is shown in enlarged subfigures.
Vehicle operation modes in UDDS drive cycle
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Simulation Results: Power and Energy Distribution
Wind drag
∑ −−−== GfWdrollTx FFFFmaF
rroll fmgF θcos= 2
21 AvcF dWd ρ= θsinmgFGf =
vFFFmavFP GfWdrollTreq ⋅+++=⋅= )(
Rolling resistance
Gravitational force
Vehicle power request, rolling resistance power, and wind drag power over a UDDS drive cycle
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Simulation Results: Regenerative Breaking
• Designed to recover as much as possible
• Disabled when v < 0.1 km/h or SOC reached charging limit
• Limited by maximum motor power
• 81% braking energy was recovered, total 0.4638 kWh
0 100 200 300 400 500-45
-40
-35
-30
-25
-20
-15
-10
-5
0
Time(s)
Pow
er(k
W)
Total Braking PowerRegenerative Braking Power
Braking power in US06 drive cycle
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Simulation Results: Engine StatesState value 1 2 3 4
Engine state Idling Engine Traction only
Traction &charging Battery
Traction withmotor
Engine On
30.8%
Engine idling
53.3%
0 200 400 600 800 1000 1200 14000
20
40
60
80
100
Veh
icle
Spe
ed (k
m/h
)
0 200 400 600 800 1000 1200 14000
1
2
3
4
5
Engi
ne S
tate
Time(s)
Engine states in UDDS drive cycle
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Simulation Results: Engine Operating Region
• Engine operating points: HEV (left), conventional vehicle (right)
• Motor provides traction when torque demand below 100 Nm.
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261
280
299
318
356
394432
Engine speed (rpm)
Tor
que
(Nm
)
BSFC Speed Torque Map
1000 1500 2000 2500 3000 3500 4000 4500 5000 55000
50
100
150
200
250
300
300
400
500
600
700
800
900
idlingmotor
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Engine speed (rpm)
Torq
ue (
Nm
)
BSFC Speed Torque Map
1000 1500 2000 2500 3000 3500 4000 4500 5000 55000
50
100
150
200
250
300
300
400
500
600
700
800
900
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Conclusions
Model-based design allows ECU development with vehicle plant models in the same environment.
Hardware-in-the-loop simulation enable very short development times with parallel control system validation.
• Model-based design HIL simulation are suitable for the development of complex control systems for the clean vehicles.
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Acknowledgements
This research is supported by the National Science Foundation under Grant NO. OISE-1157647.
Laboratory of Intelligent Mechatronics and Embedded SystemsMichigan Technological University
http://me.sites.mtu.edu/chen/
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