Study on MPC-based Energy Management for a Series Tracked Vehicle

Chao Wei, Xitao Wu, Sicheng Liu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

To improve the energy usage ratio of a series tracked vehicle, energy management control strategy based on model predictive control (MPC) was proposed. A nonlinear prediction model is established, and the cost function based on the equivalent fuel consumption model of the battery is used as the evaluation index, the dynamic programming (DP) algorithm is used to implement the rolling optimization solution in the prediction time domain which complete the real-time power allocation. Compared with rule-based control strategy, MPC can achieve a 4.1% better economy performance and more balanced state of charge (SOC).

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE 28th International Symposium on Industrial Electronics, ISIE 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1898-1902
Number of pages5
ISBN (Electronic)9781728136660
DOIs
Publication statusPublished - Jun 2019
Event28th IEEE International Symposium on Industrial Electronics, ISIE 2019 - Vancouver, Canada
Duration: 12 Jun 201914 Jun 2019

Publication series

NameIEEE International Symposium on Industrial Electronics
Volume2019-June

Conference

Conference28th IEEE International Symposium on Industrial Electronics, ISIE 2019
Country/TerritoryCanada
CityVancouver
Period12/06/1914/06/19

Keywords

  • dynamic programming
  • model predictive control
  • power distribution
  • series hybrid vehicle

Fingerprint

Dive into the research topics of 'Study on MPC-based Energy Management for a Series Tracked Vehicle'. Together they form a unique fingerprint.

Cite this