IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/6185743.html
   My bibliography  Save this article

Design and Optimization of the Power Management Strategy of an Electric Drive Tracked Vehicle

Author

Listed:
  • Qunzhang Tu
  • Xiaochen Zhang
  • Ming Pan
  • Chengming Jiang
  • Jinhong Xue

Abstract

This article studies the power management control strategy of electric drive system and, in particular, improves the fuel economy for electric drive tracked vehicles. Combined with theoretical analysis and experimental data, real-time control oriented models of electric drive system are established. Taking into account the workloads of engine and the SOC (state of charge) of battery, a fuzzy logic based power management control strategy is proposed. In order to achieve a further improvement in fuel economic, a DEHPSO algorithm (differential evolution based hybrid particle swarm optimization) is adopted to optimize the membership functions of fuzzy controller. Finally, to verify the validity of control strategy, a HILS (hardware-in-the-loop simulation) platform is built based on dSPACE and related experiments are carried out. The results indicate that the proposed strategy obtained good effects on power management, which achieves high working efficiency and power output capacity. Optimized by DEHPSO algorithm, fuel consumption of the system is decreased by 4.88% and the fuel economy is obviously improved, which will offer an effective way to improve integrated performance of electric drive tracked vehicles.

Suggested Citation

  • Qunzhang Tu & Xiaochen Zhang & Ming Pan & Chengming Jiang & Jinhong Xue, 2016. "Design and Optimization of the Power Management Strategy of an Electric Drive Tracked Vehicle," Mathematical Problems in Engineering, Hindawi, vol. 2016, pages 1-13, September.
    • Handle: RePEc:hin:jnlmpe:6185743
    DOI: 10.1155/2016/6185743
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2016/6185743.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/MPE/2016/6185743.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2016/6185743?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    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:hin:jnlmpe:6185743. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.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.