1 / 18

Fuzzy Logic Control for Parallel Hybrid Vehicles: Toyota Prius

Fuzzy Logic Control for Parallel Hybrid Vehicles: Toyota Prius. By: Jason Silver Nazim Mufti James Townsend Elikplim Tutsi Dornor. Instructor : Riadh Habash . T.A. : Fouad F. Khalil . References.

gaetano
Download Presentation

Fuzzy Logic Control for Parallel Hybrid Vehicles: Toyota Prius

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Fuzzy Logic Control for Parallel Hybrid Vehicles: Toyota Prius By: Jason Silver Nazim Mufti James Townsend Elikplim Tutsi Dornor Instructor : Riadh Habash T.A. : Fouad F. Khalil

  2. References • [1] Niels J. Schouten, Mutasim A. Salman, and Naim A. Kheir, “Fuzzy Logic Control for Parallel Hybrid Vehicles” in IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, VOL. 10, NO. 3, MAY 2002 • Basis of our system design., Provided us with the rules and conditions for the fuzzy logic controller and the power controller. • [2] http://www.toyota.ca, retrieved on March 7, 2007 • Used to retrieve specifications of the Toyota Prius. • [3] B. K. Powell, K. E. Bailey, and S. R. Cikanek, “Dynamic modeling and control of hybrid electric vehicle powertrain systems,” IEEE Contr. Syst. Mag., pp. 17–33, Oct. 1998. • Used to better understand hybrid vehicle modelling. Authors design a dynamic car model and powertrain model.

  3. References • [4] C. C. Lee, “Fuzzy logic in control systems,” IEEE Trans. Syst., Man, Cybern., vol. 20, pp. 404–435, 1990. • Used to help in the design of the fuzzy logic controller. Authors implement a fuzzy logic controller in a control system. • [5] B. M. Baumann, “Intelligent control strategies for hybrid vehicles usingneural networks and fuzzy logic,” Master’s thesis, Dept. Elect. Eng.,Ohio State Univ., Columbus, 1997. • Used to help in the design of the hybrid vehicle and fuzzy logic controller. Authors developed a fuzzy logic control technique for the powertrain of a hybrid vehicle.

  4. Parallel Hybrid Vehicle (PHV) • Electric Motor (EM) and Internal Combustion Engine (ICE) combined in parallel • Advantages • Very efficient • Environmentally friendly • Quiet • Disadvantages • Lower performance • Expensive • Requires complicated control system

  5. Our Control System • Designed with the specifications of a Toyota Prius. • Methods: • Pseudo Feedback (Jason Silver & Elikplim Tutsi Dornor) • Fuzzy Logic (Nazim Mufti & James Townsend) • Energy Management System (Elikplim Tutsi Dornor & Nazim Mufti) • Simulink Implementation (James Townsend & Jason Silver)

  6. Fuzzy Logic Controller • Designed using Sugeno Controller in Simulink Fuzzy Toolbox

  7. Fuzzy Logic Controller

  8. Fuzzy Logic Controller • Inputs

  9. Fuzzy Logic Controller • Outputs • Generated Power (Pgen) • This value depends on the inputs above • Ranges from 0 to 40 kW • ScalingFactor • Depends on State of Charge (SOC) only • Ranges from 0-1

  10. Pseudo Feedback • Needed to generate inputs for the Charge Decision Block • Input • Throttle (taken in as Pdriver) • Ranges from 0 -100kW • Electric Motor Speed (Wem) • Ranges from 0 – 1000 rad/s • Output • Pem (EM power)

  11. Charge Decision • Decides whether SOC should increase or decrease • Decrease: EM operation as motor • Increase: EM operation as generator • Input • Pem (from Pseudo Feedback) • Output • Dynamic SOC

  12. Charge Decision Block

  13. Energy Management System • Generated Power and Scaling Factor come from the FLC • Pdriver comes directly from the initial driver inputs • The system delegates power % between ICE and EM, using specs of the Prius

  14. Energy Management System Block

  15. Top Level Design

  16. Top Level Design • Initial Inputs

  17. Top Level Design • System Outputs

  18. Conclusion • From the graph above it is shown that the controller successfully delegates power to the EM and ICE efficiently • SOC remains optimal • Limitations included lack of information in the power controller design

More Related