Five Cool Things You Can Do With Powertrain Blockset The MathWorks, Inc. 1

Similar documents
Modeling and Simulate Automotive Powertrain Systems

Building Fast and Accurate Powertrain Models for System and Control Development

Full Vehicle Simulation for Electrification and Automated Driving Applications

Simulink as a Platform for Full Vehicle Simulation

2015 The MathWorks, Inc. 1

Model Based Design: Balancing Embedded Controls Development and System Simulation

Optimizing Performance and Fuel Economy of a Dual-Clutch Transmission Powertrain with Model-Based Design

The MathWorks Crossover to Model-Based Design

Combining Optimisation with Dymola to Calibrate a 2-zone Predictive Combustion Model.

Designing for Reliability and Robustness with MATLAB

Finite Element Based, FPGA-Implemented Electric Machine Model for Hardware-in-the-Loop (HIL) Simulation

Balancing operability and fuel efficiency in the truck and bus industry

Implementation and application of Simpackmulti-attribute vehicle models at Toyota Motor Europe

MORSE: MOdel-based Real-time Systems Engineering. Reducing physical testing in the calibration of diagnostic and driveabilty features

DYNA4 Open Simulation Framework with Flexible Support for Your Work Processes and Modular Simulation Model Library

Model-Based Design and Hardware-in-the-Loop Simulation for Clean Vehicles Bo Chen, Ph.D.

SIL, HIL, and Vehicle Fuel Economy Analysis of a Pre- Transmission Parallel PHEV

DRAFT (IMECE ) Hardware-In-the-Loop Simulation for Control Development in EHPV Applications

Modelling and Simulation Specialists

Model based development of Cruise Control for Mercedes-Benz Trucks

Downsizing Powertrains NVH Implications and Solutions for Vehicle Integration

Design and evaluate vehicle architectures to reach the best trade-off between performance, range and comfort. Unrestricted.

GRPE/HDH Engine-Base Emissions Regulation using HILS for Commercial Hybrid Vehicles JASIC

Modeling the Electrically Assisted Variable Speed (EAVS) Supercharger

COUPLING HIL-SIMULATION, ENGINE TESTING AND AUTOSAR- COMPLIANT CONTROL UNITS FOR HYBRID TESTING

SESSION 2 Powertrain. Why real driving simulation facilitates the development of new propulsion systems

Real-time simulation of the 2014 Formula 1 car

Novel Chassis Concept for Omnidirectional Driving Maneuvers

Experience the Hybrid Drive

PHEV Control Strategy Optimization Using MATLAB Distributed Computing: From Pattern to Tuning

MODELING AND SIMULATION OF DUAL CLUTCH TRANSMISSION AND HYBRID ELECTRIC VEHICLES

Hybrid Vehicle Model Development using ASM- AMESim-Simscape Co-Simulation for Real-Time HIL Applications

Digital Future of Product Development and Validation- The Role of Experiments & Modelling Challenges

development of hybrid electric vehicles

ASM Gasoline Engine Simulation Package. dspace Automotive Simulation Models ASM NEW: Gasoline Engine Model and ASMParameterization

Momentu. Brake-by-Wire Gathers. HIL Test System for Developing a 12-V Brake-by-Wire System BRAKE-BY-WIRE SYSTEMS

JMAAB: supporting MBD deployment and standardization in Japan

Addressing performance balancing in fuel economy driven vehicle programs

Embedded Torque Estimator for Diesel Engine Control Application

PROJECT WORK. NAME Engine base calibration process. TUTORs Amorese Stefano. JOB POSITION Engine calibration test bench engineer

ABB June 19, Slide 1

MODEL BASED DESIGN OF HYBRID AND ELECTRIC POWERTRAINS Sandeep Sovani, Ph.D. ANSYS Inc.

Research Report. FD807 Electric Vehicle Component Sizing vs. Vehicle Structural Weight Report

Proper Modeling of Integrated Vehicle Systems

A 6-Speed Automatic Transmission Plant Dynamics Model for HIL Test Bench

LMS Imagine.Lab AMESim Ground Loads and Flight Controls

GENERIC EPS MODEL Generic Modeling and Control of an Electromechanical Power Steering System for Virtual Prototypes

Multi-ECU HiL-Systems for Virtual Characteristic Rating of Vehicle Dynamics Control Systems

Model Based Development and Calibration

Regenerative Braking System for Series Hybrid Electric City Bus

Model-Based Engine Calibration

ENERGY ANALYSIS OF A POWERTRAIN AND CHASSIS INTEGRATED SIMULATION ON A MILITARY DUTY CYCLE

Predictive Control Strategies using Simulink

ONE-PEDAL DRIVING RAPID FEATURE DEVELOPMENT WITH SIMULINK MATHWORKS AUTOMOTIVE CONFERENCE MAY

Integrated Vehicle Thermal Management in Modelica: Overview and Applications

Development of a Multibody Systems Model for Investigation of the Effects of Hybrid Electric Vehicle Powertrains on Vehicle Dynamics.

Calibration. DOE & Statistical Modeling

MBD solution covering from system design to verification by real-time simulation for automotive systems. Kosuke KONISHI, IDAJ Co., LTD.

Chip Simulation for Virtual ECUs

Vehicle Simulation for Engine Calibration to Enhance RDE Performance

Development and Deployment of Virtual Test Systems An enabler to faster and efficient vehicle development

SIMULATION AND DATA XPERIENCE

COMBUSTION CONTROLLER DEVELOPMENT AND APPLICATION USING MODEL-BASED DESIGN

Holistic 1D-Model for Cooling Management and Engine Analysis of a Heavy-Duty Truck

MoBEO: Model based Engine Development and Calibration

Dipl.-Ing. Thorsten Pendzialek Dipl.-Ing. Matthias Mrosek. Model-Based Testing of Driver Assistance Systems for Counterbalance Forklift Trucks

Virtual Testing and Simulation Environment [Micro-HiL] for Engine and Aftertreatment Calibration and Development -Part 2

Full Vehicle Durability Prediction Using Co-simulation Between Implicit & Explicit Finite Element Solvers

Modification of IPG Driver for Road Robustness Applications

Methodology for Distributed Electric Propulsion Aircraft Control Development with Simulation and Flight Demonstration

Virtual Testing of the Full Vehicle System

Incorporating Drivability Metrics into Optimal Energy Management Strategies for Hybrid Vehicles. Daniel Opila

Steady-State Engine Modeling for Calibration: A Productivity and Quality Study

ELECTRIC VEHICLES DRIVE CONTROL THEORY AND PRACTICE

Certification Procedures for Advanced Technology Heavy-Duty Vehicles. Evaluating Test Methods and Opportunities for Global Alignment

Integrated Powertrain Control with Maple and MapleSim: Optimal Engine Operating Points

INCREASING ENERGY EFFICIENCY BY MODEL BASED DESIGN

V-CAP TM A FEV VIRTUAL POWERTRAIN CALIBRATION PLATFORM

Model-Based Design of an Electric Powertrain Vehicle; Focus on Physical Modeling of Lithium-ion Batteries.

Integration of Lubrication and Cooling System GT-SUITE Models

Crankcase scavenging.

Actuator Force Using Physical Modeling Tools to Design Power Optimized Aircraft

Testing of Emissions- Relevant Driving Cycles on an Engine Testbed

Mathematical modeling of the electric drive train of the sports car

FE151 Aluminum Association Inc. Impact of Vehicle Weight Reduction on a Class 8 Truck for Fuel Economy Benefits

Simulation of Collective Load Data for Integrated Design and Testing of Vehicle Transmissions. Andreas Schmidt, Audi AG, May 22, 2014

Bonded versus Sintered Interior PM Motor for Electric and Hybrid Vehicles

Automotive and transportation. Magneti Marelli

Identification of tyre lateral force characteristic from handling data and functional suspension model

ASM Brake Hydraulics Model. dspace Automotive Simulation Models ASM Brake Hydraulics Model

Integration of complex Modelica-based physics models and discrete-time control systems: Approaches and observations of numerical performance

Technical Reports. Idle Speed. Crank Time. Idle ramp Rate. Crank Speed. Idle Speed. Standstill Speed. Zero Speed

Contents. Figures. iii

Integration of Real-time Systems into the entire Vehicle Simulation

A First Principles-based Li-Ion Battery Performance and Life Prediction Model Based on Single Particle Model Equations

Future Propulsion Systems

Electro-mechanical Interactions

Highly dynamic control of a test bench for highspeed train pantographs

Using Physical Modeling Tools to Design Power Optimized Aircraft

Integrated Architectures Management, Behavior models, Controls and Software

Transcription:

Five Cool Things You Can Do With Powertrain Blockset Mike Sasena, PhD Automotive Product Manager 2017 The MathWorks, Inc. 1

FTP75 Simulation 2

Powertrain Blockset Value Proposition Perform fuel economy simulations at 50 100x real time Explore and customize pre-built reference applications Reuse models throughout the development cycle 3

Agenda Introduction to Powertrain Blockset Five cool things you can do with it: 1. Engine control design / calibration 2. Design optimization studies 3. Multidomain simulation via Simscape 4. Subsystem control design 5. Hardware-in-the-loop (HIL) testing Why are these cool? Reduce time on HIL, dyno, vehicle testing Explore wider search space Integrate multidomain subsystem models Validate controller design via simulation Validate controller virtually 4

Agenda Introduction to Powertrain Blockset Five cool things you can do with it: 1. Engine control design / calibration 2. Design optimization studies 3. Multidomain simulation via Simscape 4. Subsystem control design 5. Hardware-in-the-loop (HIL) testing 5

Powertrain Blockset Product released for R2016b Goals: Provide starting point for engineers to build good plant / controller models Provide open and documented models Provide very fast-running models that work with popular HIL systems 6

Powertrain Blockset Features Library of blocks Pre-built reference applications 7

Drivetrain Energy Storage Propulsion Transmission Vehicle Dynamics and Auxiliary Drive Vehicle Scenario Builder 8

Reference Applications Full vehicle models (conventional, EV, multi-mode HEV, input power-split HEV) Virtual engine dynamometers (compression ignition, spark ignition) 9

Four Use Cases. One Framework. Use Cases: 1. System design and optimization 2. Controller parameter optimization 3. System integration test Requirements Closed-loop Simulation Rapid Prototyping 4. Software-hardware integration test (HIL) UC1 Subsystem Design UC2 Unit Design Adapt and Reuse Production Code Generation UC3 Unit Test UC4 Subsystem Test System Test Vehicle Test System Test (HIL) 10

Agenda Introduction to Powertrain Blockset Five cool things you can do with it: 1. Engine control design / calibration 2. Design optimization studies 3. Multidomain simulation via Simscape 4. Subsystem control design 5. Hardware-in-the-loop (HIL) testing Reduce time on HIL, dyno, vehicle testing 11

Engine Control Design / Calibration Powertrain Blockset includes virtual engine dynamometer reference applications These can be used for a variety of engine controls development and calibration activities Includes several predefined experiments 12

Pre-defined Experiments for Automating Analyses Generate a steady state map from the current engine / controller Generate transient data for system identification / Model- Predictive Control (MPC) Automatically calibrate throttle / wastegate to match torque command Automatically scale engine and re-calibrate controller (150cc 15 L) 13

Automated Calibration Experiment 14

Executable Test Specification Describe the calibration procedure as a Stateflow chart (not a Word doc) Test the procedure virtually Validate / plan calibration procedure with test engineers Start testing on real hardware with refined procedure 15

Flexible Testing Framework Use Powertrain Blockset mapped engine blocks with your own data Create custom engine models using Powertrain Blockset library components Connect in your own engine model (e.g., 3 rd party CAE tool) 16

Controls Validation with Engine Model Co-Simulation 17

Controls-oriented Model Creation Detailed, design-oriented model Fast, but accurate controls-oriented model 18

How Accurate is the Mapped Engine Model? Auto-generated mapped engine model vs. co-simulation with design-oriented CAE model: 0.3% fuel economy difference 50x faster Mapped engine model Design-oriented engine model 19

Engine Control Design / Calibration Automatically calibrate throttle / wastegate Define and simulate custom calibration procedures Generate engine maps from CAE models 20

Agenda Introduction to Powertrain Blockset Five cool things you can do with it: 1. Engine control design / calibration 2. Design optimization studies 3. Multidomain simulation via Simscape 4. Subsystem control design 5. Hardware-in-the-loop (HIL) testing Explore wider search space 21

Accessible Optimization Capabilities 50-100x Faster Than Real Time Efficient Optimization Laptop-based Analysis More drive cycles and design parameters Using fewer resources Simulink Design Optimization UI 22

Multi-Mode HEV Review EV Mode 23

Multi-Mode HEV Review SHEV Mode 24

Multi-Mode HEV Review Engine Mode 25

Requested Tractive Force [N] Design Optimization Problem Statement Maximize MPGe FTP75 and HWFET Weighted MPGe = 0.55(FTP75) + 0.45(HWFET) Optimize Parameters: 5 control parameters EV, SHEV, Engine mode boundaries 1 hardware parameter Final differential ratio Use PC Simulink Design Optimization (SDO) Parallel Computing Toolbox (PCT) 8000 7000 6000 5000 4000 3000 2000 1000 EV SHEV Engine / Power Split 0 0 50 100 150 Vehicle Speed [kph] Differential Ratio Lenovo ThinkPad T450s Dual Core i7 2.60GHz 12 GB RAM 26

Simulink Design Optimization Speed Up Best practices Accelerator mode Fast Restart Use Parallel Computing Toolbox Specify Simulation timeout 27

Optimization Results Simulink Design Optimization Response Optimization + 2% MPGe ~ 12 Hours 3.42:1 2.92:1 28

Sensitivity Analysis Determine sensitivity of the fuel economy to changes in design parameters Configure Monte Carlo simulations using Simulink Design Optimization s graphical interface Create sample sets using random & pseudo-random techniques Define behaviors of interest in the model Speed up performance using parallel computing Local: Parallel Computing Toolbox Cluster: MATLAB Distributed Computing Server 29

Sensitivity Analysis Results City Cycle High variation in fuel economy for variations in wheel radius, vehicle mass, and other parameters High sensitivity to variation in wheel radius and injector slope values Highway Cycle Low variation in fuel economy for variations in wheel radius, vehicle mass, and other parameters High sensitivity to variation in barometric pressure, but little else 30

Design optimization studies Define Design Optimization studies with minimal setup effort Enable parallel computing with a simple checkbox Perform Design Optimization studies overnight on your laptop Perform Monte Carlo studies to analyze sensitivity 31

Agenda Introduction to Powertrain Blockset Five cool things you can do with it: 1. Engine control design / calibration 2. Design optimization studies 3. Multidomain simulation via Simscape 4. Subsystem control design 5. Hardware-in-the-loop (HIL) testing Integrate multidomain subsystem models 32

Powertrain Blockset and Simscape Tools have overlap in what they can do, but they have a different emphasis Analysis Powertrain Blockset Equation-based Data-driven Simscape Design 33

Custom Drivetrain or Transmission Replace portions of reference application with custom models assembled from Simscape libraries Use Variant Subsystems to shift back and forth based on current simulation task Pre-Built Drivetrain Custom Drivetrain Custom Transmission 34

Engine Cooling System Take customization one step further Start with Custom Driveline variant Add Engine Cooling subsystem adapted from sscfluids_engine_cooling_system 35

Conventional Vehicle with Simscape Engine Cooling 1. Heat rejection calculation 1 2. Heat distributed between oil and coolant 2 3. Temperature of cylinder used to validate cooling system performance 1 2 3 36

Multidomain simulation via Simscape Create detailed, multi-domain subsystem models with Simscape Incorporate them into system level vehicle models from Powertrain Blockset Validate subsystem performance with closed loop simulation 37

Agenda Introduction to Powertrain Blockset Five cool things you can do with it: 1. Engine control design / calibration 2. Design optimization studies 3. Multidomain simulation via Simscape 4. Subsystem control design 5. Hardware-in-the-loop (HIL) testing Validate controller design via simulation 38

Challenges for the Motor Control Engineer How do I know if my motor controller will produce the desired performance? What will the interactions be between my motor and the rest of the vehicle systems? How will my motor operate under more extreme load cases? 39

Different Motor Models for Different Needs System Optimization Goal: Estimate fuel economy Requirements: fast simulation speed, simple parameterization Model choice: empirical model Subsystem Control Design Goal: Study controller interactions Requirements: higher accuracy, inclusion of effects like saturation Model choice: nonlinear saturation Detailed model = inverter controller + nonlinear motor model 40

High Fidelity Detailed Motor Model in Simscape FEA simulations or dynamometer data used to obtain non-linear flux table Flux-based PMSM model created to capture this effect 0.05 d Data Map id d [V.S] 0 vd λd -0.05 500 0 I q [A] -500-600 -400-200 I d [A] 0 vq λq 0.2 0.1 q Data Map q [V.S] 0-0.1-0.2 500 0 I q [A] -500-600 -200-400 I d [A] 0 iq Mechanical Eqn. 41

Including Detailed Subsystem Variants Add your own subsystem variants to the existing vehicle models Simulink-based Simscape-based S-function 42

Detailed Model Variant Simulation Cycle Final SOC (%) MPGe Name Mapped Detailed Mapped Detailed HWFET 42 44 50.5 51.8 FTP75 41.4 42.8 59.6 66.4 Detailed variant gives comparable response Supervisory controller handles both motor variants Motor controller requires further verification 43

Torque Control Performance Actual Torque Commanded Torque FTP75 Drive Cycle Motor torque response accurately follows the commanded torque at different speeds Motor Speed 44

Torque Control Performance Actual Torque Commanded Torque Motor Speed US06 Drive Cycle Much higher power demand reveals a problem Motor controller becomes unstable under certain operating conditions 45

Controller Enhancements Controller robustness was improved via dynamic gain scheduling Trq_cmd Speed Flux-Weakening Controller id_cmd iq_cmd Current Controller vd_ref vq_ref Modulation 46

Torque Control Performance Actual Torque Commanded Torque US06 Drive Cycle Even in more extreme maneuvers, improved motor controller is able to provide the commanded torque Motor Speed 47

Subsystem control design Easily integrate detailed motor and controller model in system simulation model Test interactions between motor and controller with the rest of the vehicle Verify subsystem controller meets system level requirements 48

Agenda Introduction to Powertrain Blockset Five cool things you can do with it: 1. Engine control design / calibration 2. Design optimization studies 3. Multidomain simulation via Simscape 4. Subsystem control design 5. Hardware-in-the-loop (HIL) testing Validate controller virtually 49

HIL Testing with Powertrain Blockset HEV Model Speedgoat Rapid Control Prototyping System Speedgoat Hardware in-the-loop System CAN Cable Embedded Controller Hardware Target Computer Hardware 50

Powertrain Blockset HIL Testing Physical Setup 51

Easily Tune Parameters in Real Time and Save Calibrations Calibrate parameters at run time in Simulink Real-Time Explorer Use Simulink Real-Time API to save and compare calibrations directly from MATLAB 52

Hardware-in-the-loop (HIL) testing Validate control algorithm before physical prototypes are available Reuse the same vehicle models across the V-cycle Tune parameters in real time Setup a HIL test in a few hours 53

Summary With Powertrain Blockset, you can perform Model-Based Design on your automotive systems with a single, seamlessly integrated environment Engine control design / calibration Design optimization studies Subsystem controller design Multidomain simulation via Simscape Hardware-in-the-loop (HIL) testing 54

Powertrain Blockset Value Proposition Perform fuel economy simulations at 50 100x real time Explore and customize pre-built reference applications Reuse models throughout the development cycle 55

Additional Resources Customer Service Email: service@mathworks.com Phone: 508.647.7000, option 1 Product Manager mike.sasena@mathworks.com Technical Support Email: support@mathworks.com Phone: 508.647.7000, option 2 Product Specialist Application Engineer brad.hieb@mathworks.com 56