Introduction to Modeling and Simulation of Hybrid Electric Vehicles

Presenter Information

• Name: Kevin Oshiro
• Affiliation: Application Engineering Group, MathWorks
• Background:
  • Electrical and Mechanical Engineering
  • Experience at Packers Kenworth Research and Development Center
  • Specializes in hybrid electric vehicle powertrains for medium and heavy-duty trucks
  • Interests: Model-based design, physical modeling tools, mechatronic systems, system-level control strategies
  • Mentors the Eco-Car student competition

Presentation Objective

• Provide a foundation for modeling and simulating hybrid electric vehicles (HEVs)
• Conduct analysis such as:
  • HEV architecture selection
  • Energy consumption estimates
  • Performance estimates over different drive cycles
  • Component selection
• Aid in the HEV design process

Model-Based Design Process Steps

1. Model HEV Architectures and Powertrain Plant Models
   • Engine
   • Electrical Components
   • Drivetrain Components
2. Develop and Implement HEV Control Algorithms
3. Conduct HEV Design Optimization Process

Motivation for Modeling HEVs

• Design Challenges:
  • Selecting powertrain architecture/topology
  • Selecting and sizing components (e.g., motor, battery)
  • Modeling HEV plant and control algorithms
  • Optimizing system performance over wide operating conditions
  • Implementing control algorithms for real-time execution

Example: HEV Architecture Selection

• Typical Parallel/Series Parallel Topology
  • P0 Location: Front of the engine (connected to engine crankshaft via front accessory drive belt)
  • P1 Location: Flywheel side of the engine
  • P2 Location: Input to transmission, includes clutch between motor and engine
  • P3 Location: Inside transmission or on its output
  • P4 Location: On the axle not connected to the internal combustion engine
• Examples:
  • P2 Parallel Architecture: Full electric mode, parallel hybrid mode
  • P1/P3 Series Parallel Architecture: EV mode, series hybrid, parallel hybrid
• Simulation Benefits: Assessing pros/cons of architectures virtually saves time vs. physical prototypes

Example: Component Selection and Sizing

• Electric Machine Options:
  • Types: Interior permanent-magnet, induction machines
  • Specifications: Maximum torque, maximum power
• Battery Options:
  • Types, energy capacity, cell/module configurations
  • Charge/discharge power capability
• Transmission Options:
  • Multi-speed (AMTs, dual-clutch, automatics, fixed gearing)
  • Planetary gear sets for input power split HEVs (Toyota Prius, GM Volt)
  • Gear ratio selection

Example: Performance Optimization

• Operating Conditions:
  • Different drive cycles (e.g., FTP 72, highway VT, aggressive driving cycle US 06)
  • Road grades, temperature ranges
• HEV Controller Goals:
  • Reduce energy consumption
  • Reduce emissions
  • Meet drivability requirements (acceleration, speed maintenance at different grades)

Solution: Model-Based Design Process

• Examples:
  1. Build Plant Models and Develop Control Algorithms
     • Systems level model for component sizing and performance assessment
     • Closed-loop control development early in the design process
  2. Optimize Control and Plant Simultaneously
• Model Reuse: Important throughout the process (code generation, hardware-in-loop, verification, validation)

Complete Hybrid Electric Vehicle Example

• Simulink Environment: Powertrain Blockset tool
• Closed-loop System Level Vehicle Model:
  • Drive Cycle Source Block: Generates standard/user-specified speed vs. time signal
  • Virtual Driver Model: Generates accelerator and brake pedal signals
  • Controllers: Use signals and feedback to output torque commands
  • Vehicle System: Physical models of engine, motors, batteries, drivetrain output torques and forces
  • Visualization System: Displays dynamic signals during simulation
• Forward-looking Simulation: Stepping forward incrementally in time
• Visualization:
  • Vehicle speed vs. drive cycle target speed
  • Actuator torques/speeds (engine, motor)
  • Battery current, state of charge
  • Fuel economy (mpg equivalent)

Conclusion

• Advantages of Modeling and Simulation:
  • Assess performance and energy consumption
  • Size physical components
  • Optimize controls and system
• Key to Successful HEV Design: Model-based design process

Next Steps

• Watch subsequent examples to learn:
  • How to model an HEV
  • Implement HEV control algorithms
  • Conduct HEV design optimization

Thank you!