Using a Model Based Design Approach to Accelerate Electric Drive Introduction

“This presentation does not contain any proprietary or confidential information”

HTUF 2010September 29, 2010

Larry MichaelsArgonne National Laboratory

Better Complexity Management=> Models have a higher abstraction level than C code (compare C to assembly)

Shortened Development Times=> Higher abstraction allows more software to be developed in the same time=> Fast iterations from changes in requirements or specification to implementation=> Find errors early through simulation (cheaper and faster to fix)

Improved Quality=> Better specifications through simulation=> Significantly less coding errors through automatic code generation=> Consistency between model, code, and documentation

Why Model Based Design?

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High-quality models: modeling guidelines High-quality code: efficient, readable, configurable Efficient data management Sheer volume of data, increasingMulti-user environments and multi-variant projects

Verification and validation Mature MBD process, early simulation Best-in class verification and validation tools

Support of automotive standards, for instance: More and more safety-related vehicle functions: development acc. to. ISO 26262 Adoption of AUTOSAR: easy migration, comprehensive feature support

Key Model Based Design Successes

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AUTONOMIE –

Taking it to the Next Level

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The objective is to accelerate the development and introduction of advanced technologies through a

Plug&Play architecture that will be adopted by the entire industry and research community.

Plug&Play

Reduces Cost & Time to

Production

Enterprise Wide

Solution

Key Benefits

■ Common Methods to sort technologies quickly to reduce hardware build iterations■ Reduces/eliminates duplicate modeling and analysis work■ Delivers designs that balance Fuel Economy, Emissions and Drivability (FEED) requirements

■ Flexibility & Reusability■ Customizable architectures■ Common Nomenclature■ Code Neutral

■ Database Management■ Provides common methods and tools for comparing/evaluating technologies

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Autonomie in the Controls Development Process

System Requirements

System Design

Software Design

Coding

SoftwareIntegration

Hardware/SoftwareIntegration

System Integration & Calibration

Sim

RP

OTRP SIL

PIL

HIL

Sim:RP:OTRP:PCG:SIL:PIL:HIL:

SimulationRapid PrototypingOn-Target Rapid PrototypingProduction Code GenerationSoftware-In-the-LoopProcessor-In-the LoopHardware-In-the Loop

PCG

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Evaluating Fuel Consumption of Advanced Technologies (MIL)

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0

5

10

15

Perce

ntage

Impro

veme

nt fro

m hig

h to l

ow C

d

Comparison of Aerodynamic Fuel Savings for Drive Cycles vs Steady States

HTUF Class 6/21 mph SS

UDDS Truck/26 mph SS

HHDDT Cruise/42 mph SS

HHDDT High Speed/53 mph SS

Drive CyclesSteady States

Impact of Aerodynamics for Different Line Haul Applications

16.0

13.716.3

24.022.4

15.513.1

15.6

21.319.2

15.112.5

15.0 14.015.5

0.0

5.0

10.0

15.0

20.0

25.0

30.0

HHDDT65 HHDDT Cruise HHDDT High Speed

HHDDT Transient

udds_truck

Fuel

Con

sum

ptio

n (g

al/1

00m

i) CONV MILD-HEV FULL-HEV

Impact of Mild and Full HEV for Line Haul Applications

50% load

14.9% 15.9%

1.4% 1.4%

3.0% 3.8%1.2%

1.6%1.7%1.4%

8.6%8.9%

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

14.0%

16.0%

18.0%

20.0%

Each technology

(Conv)

Combination(Conv)

Each technology

(Hybrid)

Combination(Hybrid)

Perc

ent F

uel S

aved

Impact of All Technologies on Fuel Consumption

Engine

Transmission

RR

Cd

Weight

Hybrid improvementsBaseline improvements

The Sum of the Combined Technologies < The Sum of Each Technology

Class 2B Pickup

Work performed for the NAS HD Committee

Virtual Algorithm Development Perform Algorithm design in the virtual environment

Add Simulink algorithm model to the simulation– Design the algorithm in the context of the system, including SIL

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Algorithm Model

SIL block

Testing and Validation (SIL) Integrate production code into the Autonomie vehicle model (SIL)

Test in the virtual environment

Use to represent control functionality that’s not modeled

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Evaluate Non Modeled Phenomena With HardwareComponent-in-the-Loop

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Example #2: Impact of emission and engine cold start on PHEVs Fuel Consumption

Example#1: Impact of battery cold start on PHEVs Fuel Consumption

Engine behaves as if in vehicle

Rest of the Vehicle Modeled

Sensors Battery behaves as if in vehicle

Example #3: Engine and Battery are Coupled

Autonomie Designed to Be Used For All Steps in the Development Process

Ensure simulation traceability, model compatibilities

Analyze and compare test and simulation data

Generic Processes

Easy selection & implementation of data, models, control or cycles

Run batch mode +Distributed computing

Build and compare large number of technology, powertrain, options

Database Management

Enables MIL, SIL, RCP, HIL, CIL

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Autonomie Flexibility Used to Develop Specific Labeling Version for Europe in Collaboration with ACEA

ACEA provided all the requirements

Argonne customized Autonomie to meet the specific labeling needs. Most of the modifications were related to deleting flexibility available in the full version.

First version of the tool delivered to ACEA this week in Brussels

The tailored labeling version will be made available at no cost on our website (www.autonomie.net)

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Summary Establishes tool and framework for enterprise-wide collaboration

Common framework for all MBD activities

Provides complete user customization by an open architecture

Simulates from single components, subsystems to entire vehicles

Manages models, data, processes, results and control code from research to production

A software environment and standard framework

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