IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v3y2010i11p1821-1830d10300.html
   My bibliography  Save this article

Dynamic Modeling and Simulation on a Hybrid Power System for Electric Vehicle Applications

Author

Listed:
  • Hong-Wen He

    (National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing, 10081, China)

  • Rui Xiong

    (National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing, 10081, China)

  • Yu-Hua Chang

    (The Faculty of Automotive and Construction Machinery Engineering, Warsaw University of Technology, Warsaw, 02-524, Poland)

Abstract

Hybrid power systems, formed by combining high-energy-density batteries and high-power-density ultracapacitors in appropriate ways, provide high-performance and high-efficiency power systems for electric vehicle applications. This paper first establishes dynamic models for the ultracapacitor, the battery and a passive hybrid power system, and then based on the dynamic models a comparative simulation between a battery only power system and the proposed hybrid power system was done under the UDDS (Urban Dynamometer Driving Schedule). The simulation results showed that the hybrid power system could greatly optimize and improve the efficiency of the batteries and their dynamic current was also decreased due to the participation of the ultracapacitors, which would have a good influence on batteries’ cycle life. Finally, the parameter matching for the passive hybrid power system was studied by simulation and comparisons.

Suggested Citation

  • Hong-Wen He & Rui Xiong & Yu-Hua Chang, 2010. "Dynamic Modeling and Simulation on a Hybrid Power System for Electric Vehicle Applications," Energies, MDPI, vol. 3(11), pages 1-10, November.
    • Handle: RePEc:gam:jeners:v:3:y:2010:i:11:p:1821-1830:d:10300
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/3/11/1821/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/3/11/1821/
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kyuhyun Sim & Sang-Min Oh & Ku-Young Kang & Sung-Ho Hwang, 2017. "A Control Strategy for Mode Transition with Gear Shifting in a Plug-In Hybrid Electric Vehicle," Energies, MDPI, vol. 10(7), pages 1-15, July.
    2. Hongwen He & Rui Xiong & Jinxin Fan, 2011. "Evaluation of Lithium-Ion Battery Equivalent Circuit Models for State of Charge Estimation by an Experimental Approach," Energies, MDPI, vol. 4(4), pages 1-17, March.
    3. Changle Xiang & Yanzi Wang & Sideng Hu & Weida Wang, 2014. "A New Topology and Control Strategy for a Hybrid Battery-Ultracapacitor Energy Storage System," Energies, MDPI, vol. 7(5), pages 1-23, April.
    4. Lei Zhang & Zhenpo Wang & Fengchun Sun & David G. Dorrell, 2014. "Online Parameter Identification of Ultracapacitor Models Using the Extended Kalman Filter," Energies, MDPI, vol. 7(5), pages 1-14, May.
    5. Pablo Moreno-Torres & Marcos Blanco & Marcos Lafoz & Jaime R. Arribas, 2015. "Educational Project for the Teaching of Control of Electric Traction Drives," Energies, MDPI, vol. 8(2), pages 1-18, January.
    6. Rui Xiong & Hongwen He & Fengchun Sun & Kai Zhao, 2012. "Online Estimation of Peak Power Capability of Li-Ion Batteries in Electric Vehicles by a Hardware-in-Loop Approach," Energies, MDPI, vol. 5(5), pages 1-15, May.
    7. Jorge Garcia & Pablo Garcia & Fabio Giulii Capponi & Giulio De Donato, 2018. "Analysis, Modeling, and Control of Half-Bridge Current-Source Converter for Energy Management of Supercapacitor Modules in Traction Applications," Energies, MDPI, vol. 11(9), pages 1-22, August.
    8. Hongwen He & Zhentong Liu & Liming Zhu & Xinlei Liu, 2012. "Dynamic Coordinated Shifting Control of Automated Mechanical Transmissions without a Clutch in a Plug-In Hybrid Electric Vehicle," Energies, MDPI, vol. 5(8), pages 1-16, August.
    9. Jun Bi & Yongxing Wang & Shuai Sun & Wei Guan, 2018. "Predicting Charging Time of Battery Electric Vehicles Based on Regression and Time-Series Methods: A Case Study of Beijing," Energies, MDPI, vol. 11(5), pages 1-18, April.
    10. Qiao Zhang & Weiwen Deng, 2016. "An Adaptive Energy Management System for Electric Vehicles Based on Driving Cycle Identification and Wavelet Transform," Energies, MDPI, vol. 9(5), pages 1-24, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:3:y:2010:i:11:p:1821-1830:d:10300. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.