Mode l Pre dic tive Control for E ne rg y- e ffic ie nt Ma ne uve - - PowerPoint PPT Presentation

Mode l Pre dic tive Control for E ne rg y- e ffic ie nt Ma ne uve ring of Conne c te d Autonomous Ve hic le s

So uthwe st Re se a rc h I nstitute Unive rsity o f Mic hig a n T

• yo ta Mo to r E

ng ine e ring & Ma nufa c turing , No rth Ame ric a , I nc .

Sc o tt Ho tz, Assista nt Dire c to r

As the prime contractor SwRI will leverage its expertise in CAVs, powertrains, and vehicle and component evaluation. The University of Michigan brings a broad range of experience on advanced engine and vehicle controls. TEMA will serve in an advisory and support role as a passive collaborator, and will provide vehicles and instrumentation.

• Vehicle Benchmarking
• CAV Development
• Traffic Simulation
• CAV in the loop dyno

testing

• Vehicle Model

Development

• Traffic Flow Information
• Traffic Data Analysis
• Mcity Automated Vehicle

Test Facility

• OEM Vehicle Integration
• Powertrain Model

Validation

• Bypass Control Assistance
• Production Implementation

Perspective

• Optimal Control Algorithm Development
• Powertrain Optimization

20% Energy Consumption Reduction CAV Enabled Toyota Prius Prime PHEV

SOC Distance

Trip Energy Management Macroscopic: utilize V2C Driving Power Management Mesoscopic: utilize V2V and V2I

• 25000
• 20000
• 15000
• 10000
• 5000

• 5

Predictive VD & PT Control Structure Realistic Traffic Simulation

Develop Traffic Volume Vehicle Simulation Generate Road Networks Validate Traffic Model

3D Vehicle Simulation

Human Driver Advisory Automated Driver

10%

Expand SOC Limit

7% 3%

Pwr/Spd Optimization SOC Planning

Precision CAV Chassis Dyno Testing

Vehicle speed/ position, Signal Phase and Timing, Speed

DRCC System

Vehicle speed Road type/ grade Engine on/off Engine torque MG1 torque MG2 torque friction brake

Energy Management ECU

Powertrain States

Subsystem ECU

Power Request

Dyno Controller

Position Safety Constraints

Radar VD&PT Control ECU Bypass Traffic Simulator Simulated DSRC RF Coverage/ Roadside and Vehicle Unit DSRC Onboard Unit

Technology-to-Market approach

• The Technology-to-Market (T2M) plan will be developed during the first

quarter of this effort

• SwRI will identify an internal T2M lead, and is evaluating options for

external support

• This technology will be developed in a way that minimizes the barriers

to entry into the market  This technology will initially be applied to a human driven vehicle  Later integrated into an automated vehicle

• Market Discovery and validation

 Do drivers want this?  Are there other markets to consider?  Are NEXTCAR assumptions valid?  What is the energy cost of CAV tech?

• Will the algorithms be robust to any changes in

parameters or uncertainties, penetration rate, any delay in the system?

• Can the optimization problem be solved quickly for

real-time implementation?

• Are there any opportunities to improve engine

efficiency in this highly optimized PHEV?

Key Challenges