System Integration, Simulation and Energy Management of HEVs
Short Course Description
This 3-day short course introduces participants to HEV system integration and energy management concepts using modern simulation methods based on Matlab/Simulink tools.
Participants will use a modular simulator compatible with software- and hardware-in-the-loop control development systems, describing the energy flows in conventional and hybrid vehicles and analyzing energy management strategies in a series of computer laboratory exercises that culminates with the participants developing their own energy management strategy based on the simulator developed during the course. Participants receive a copy of the modular Matlab/Simulink simulator used in the exercises.
Participants in this short course will learn how to:
- Evaluate energy consumption in road vehicles. Relate energy demand of driving cycles to fuel economy and CO2 emissions. Understand the concept and benefits of drivetrain hybridization strategies.
- Develop mathematical models of energy use in combustion engine & mechanical transmission subsystems & use the models in a vehicle simulator to predict fuel consumption and CO2 emissions.
- Develop mathematical models of electric traction drives and energy storage systems, used in hybrid vehicles, including thermal models. Use these models in electric and hybrid vehicle simulators to predict energy use and CO2 emissions. Describe battery electrical and thermal management systems. Introduce high voltage and battery safety concepts.
- Learn principles of energy management for HEVs, including mathematical methods such as Dynamic Programming, as well as real-time implementable strategies such as ECMS. Explore and improve HEV supervisory control design and energy management using a hybrid-electric vehicle simulator.
Giorgio Rizzoni has served in his current role as director for the Center for Automotive Research since 1999, while holding faculty appointments in both Mechanical and Aerospace Engineering (MAE) and Electrical and Computer Engineering (ECE). He has been continuously engaged in graduate and undergraduate curriculum development on subjects related to system dynamics, mechatronics, powertrain modeling, hybrid-electric vehicles and system fault diagnosis. Rizzoni is a three-time recipient of the MAE External Advisory Board Excellence in Teaching Award and in 1996 received the College of Engineering Stanley Harrison Award for Excellence in Engineering Education.