IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/368769.html
   My bibliography  Save this article

Online Energy Management of Plug-In Hybrid Electric Vehicles for Prolongation of All-Electric Range Based on Dynamic Programming

Author

Listed:
  • Zeyu Chen
  • Weiguo Liu
  • Ying Yang
  • Weiqiang Chen

Abstract

The employed energy management strategy plays an important role in energy saving performance and exhausted emission reduction of plug-in hybrid electric vehicles (HEVs). An application of dynamic programming for optimization of power allocation is implemented in this paper with certain driving cycle and a limited driving range. Considering the DP algorithm can barely be used in real-time control because of its huge computational task and the dependence on a priori driving cycle, several online useful control rules are established based on the offline optimization results of DP. With the above efforts, an online energy management strategy is proposed finally. The presented energy management strategy concerns the prolongation of all-electric driving range as well as the energy saving performance. A simulation study is deployed to evaluate the control performance of the proposed energy management approach. All-electric range of the plug-in HEV can be prolonged by up to 2.86% for a certain driving condition. The energy saving performance is relative to the driving distance. The presented energy management strategy brings a little higher energy cost when driving distance is short, but for a long driving distance, it can reduce the energy consumption by up to 5.77% compared to the traditional CD-CS strategy.

Suggested Citation

  • Zeyu Chen & Weiguo Liu & Ying Yang & Weiqiang Chen, 2015. "Online Energy Management of Plug-In Hybrid Electric Vehicles for Prolongation of All-Electric Range Based on Dynamic Programming," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-11, December.
  • Handle: RePEc:hin:jnlmpe:368769
    DOI: 10.1155/2015/368769
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2015/368769.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/MPE/2015/368769.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2015/368769?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
    ---><---

    Citations

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


    Cited by:

    1. Rudravaram Venkatasatish & Dhanamjayulu Chittathuru, 2023. "Coyote Optimization Algorithm-Based Energy Management Strategy for Fuel Cell Hybrid Power Systems," Sustainability, MDPI, vol. 15(12), pages 1-21, June.
    2. Xiaobin Ning & Jiazheng Wang & Yuming Yin & Jiarong Shangguan & Nanxin Bao & Ning Li, 2023. "Regenerative Braking Algorithm for Parallel Hydraulic Hybrid Vehicles Based on Fuzzy Q-Learning," Energies, MDPI, vol. 16(4), pages 1-18, February.
    3. Xu Wang & Ying Huang & Jian Wang, 2023. "Study on Driver-Oriented Energy Management Strategy for Hybrid Heavy-Duty Off-Road Vehicles under Aggressive Transient Operating Condition," Sustainability, MDPI, vol. 15(9), pages 1-25, May.

    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:368769. 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.