Course 1 & 1a: System Integration, Simulation and Energy Management of Hybrid Electric Vehicles

Learn HEV System Simulation Methods for SIL and HIL Development of HEV Energy Management Strategies.

 

25 - 27 June 2018

Lecturer: Prof. Giorgio Rizzoni, The Ohio State University

Course can be taken completely (Day 1 to 3, Course 1) or just Day 1 for an overview of the Topic (Course 1a). 

Target Group

The intended audiences for this course are:

 

  • Automotive industry executives who wish to become acquainted with hybrid-electric powertrain technologies and model-based control development tools.
  • Automotive industry engineers and engineering managers with an interest in electrified powertrain control and energy management who wish to become better acquainted with system integration, energy management and SIL and HIL methods to design of energy management strategies for hybrid vehicles.


The course has been designed so that executives, managers and more senior engineers who may wish to be exposed to the foundations and to the language of hybrid-electric vehicle powertrain control may gain sufficient familiarity with the subject matter by attending Day 1 only.
Days 2 and 3 delve more deeply into the technical subject matter covered in overview form in Day 1, so that attending the full three days will make the participant closely acquainted with models, simulators and energy management algorithms development.  The course requires mechanical and electrical engineering background. Dipl.-Ing. / M.Sc. level mechanical or electrical engineering degree is preferred, but B.Sc. graduates with automotive engineering experience are also encouraged to attend.

More information about Prof. Rizzoni

Course Objectives

The objective of this course is to introduce the participants to HEV system integration and energy management concepts using modern simulation methods based on Matlab/Simulink tools. The 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.
The course is available in two formats (three-day, Course 1, and one-day, Course 1a). The broad objectives apply to both versions, but the specifics can be found below:

 

Objective 1     

(Courses 1 and 1a):

Evaluate energy consumption in road vehicles. Relate energy demand of driving cycles to fuel economy and CO2 emissions. Understand the concept and potential benefits of drivetrain hybridization strategies.

Objective 2

(Course 1): 

Develop mathematical models of energy use in combustion engine and mechanical transmission subsystems and use these models in a vehicle simulator to predict fuel consumption and CO2 emissions.

Objective 3

(Course 1): 

Develop mathematical models of electric traction drives and energy storage systems, used in hybrid vehicles. Use these models in electric and hybrid vehicle simulators to predict energy use and CO2 emissions.

Objective 4

(Course 1): 

Learn principles of energy management for hybrid electric vehicles, 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.

Course Outline

Day 1:

Understand the concept and potential benefits of drivetrain hybridization strategies. Evaluate energy consumption in road vehicles and relate energy demand of driving cycles to fuel economy and CO2 emissions.

Day 2:

Develop mathematical models of energy use in internal combustion (I.C.) engine and mechanical transmission subsystem and use the models to predict fuel consumption and CO2 emissions.

  • Analyze fuel consumption in vehicles
  • Learn how Hybrid Electric Vehicles (HEVS) compare with conventional vehicles;
  • Understand the concept and potential benefits of different hybrid powertrain topologies;
  • Learn the basic principles of energy management and optimal supervisory control strategy for hybrid electric vehicles;
  • Review the different types of electric machines and their principles of operation;
  • Review power converter technologies and their principles of operation;
  • Understand the most important properties of electrochemical energy storage devices and systems for automotive applications;
  • Develop an understanding of current performance and R&D targets for each of the three subsystems listed above;
  • Simulation exercise: review the structure of a plug-in hybrid-electric vehicle simulator, and exercise the simulator to conduct energy analysis in simulation.  A Simulink-based simulator is provided.
  • Review various I.C. engines and mechanical transmission configurations and their influence on vehicle fuel economy;
  • Understand how the Matlab/Simulink environment can be used to create a vehicle model through step by step instructions, using specially developed simulation code;
  • Simulation exercise: Develop an understanding of a conventional (non-hybrid) powertrain model and modify a powertrain vehicle simulator to analyze the functionality of the various components and their impact on fuel economy, with special emphasis on the importance of transmission management. A Simulink-based Simulator is provided.

Day 3, Part 1:

Develop a more in-depth understanding of electric machines, power converters and battery systems, and how to model the energy efficiency of electric traction drives and energy storage systems in XEVs. Use these models in electric and hybrid vehicle simulators to understand energy use.

Day 3, Part 2:

Understand supervisory control strategies for hybrid electric vehicles.

  • Review the details of electric machine and power converter operation and develop models appropriate for vehicle fuel economy prediction;
  • Review the details of energy storage systems and develop models of battery systems appropriate for vehicle fuel economy prediction;
  • Model and simulate electric traction systems and energy storage devices in a vehicle simulator and use these models to predict fuel consumption and CO2 emissions.
  • Review energy management concepts for hybrid electric powertrains and introduce principles of optimal control, including Dynamic Programming and Equivalent Consumption Minimization Strategy (ECMS).
  • Simulation exercise: Perform HEV analysis and simulation through optimization of the supervisory energy management controller fuel economy using a given HEV simulator implemented in Matlab/Simulink.  A Simulink-based simulator is provided.

Goals

Upon completion of the course the participants will be familiar energy analysis and modeling of hybrid-electric powertrains, with some principles of optimal control, and with Matlab/SimulinkTM tools for vehicle energy analysis and supervisory control, and with the design of energy management strategies using StateFlowTM.

For registration click here.