logo

SCIENCE CHINA Information Sciences, Volume 61, Issue 7: 070207(2018) https://doi.org/10.1007/s11432-017-9329-6

A stochastic logical model-based approximate solution for energy management problem of HEVs

More info
  • ReceivedOct 25, 2017
  • AcceptedDec 29, 2017
  • PublishedMay 21, 2018

Abstract

There is no abstract available for this article.


Acknowledgment

This work was supported by National Natural Science Foundation of China (Grant Nos. 61773090, 61304128).


References

[1] Borhan H, Vahidi A, Phillips A M. MPC-based energy management of a power-split hybrid electric vehicle. IEEE Trans Control Syst Technol, 2012, 20: 593-603 CrossRef Google Scholar

[2] Zhang J Y, Shen T L. Real-time fuel economy optimization with nonlinear MPC for PHEVs. IEEE Trans Control Syst Technol, 2016, 24: 2167-2175 CrossRef Google Scholar

[3] Di Cairano S, Bernardini D, Bemporad A. Stochastic MPC with learning for driver-predictive vehicle control and its application to HEV energy management. IEEE Trans Control Syst Technol, 2014, 22: 1018-1031 CrossRef Google Scholar

[4] Malikopoulos A A. A multiobjective optimization framework for online stochastic optimal control in hybrid electric vehicles. IEEE Trans Control Syst Technol, 2016, 24: 440-450 CrossRef Google Scholar

[5] Xiang C L, Ding F, Wang W D. MPC-based energy management with adaptive Markov-chain prediction for a dual-mode hybrid electric vehicle. Sci China Technol Sci, 2017, 60: 737-748 CrossRef Google Scholar

[6] Zhao Y, Li Z Q, Cheng D Z. Optimal control of logical control networks. IEEE Trans Automat Control, 2011, 56: 1766-1776 CrossRef Google Scholar

[7] Wu Y H, Shen T L. An algebraic expression of finite horizon optimal control algorithm for stochastic logical dynamical systems. Syst Control Lett, 2015, 82: 108-114 CrossRef Google Scholar

Copyright 2019 Science China Press Co., Ltd. 《中国科学》杂志社有限责任公司 版权所有

京ICP备18024590号-1