Adaptive Energy Management Strategy for Plug-in Hybrid Electric Bus Based on Equivalent Factor Optimization

被引：0
|
作者：
Yang Y. [1 ,2 ]
Zhang Y. [1 ]
Zhang B. [2 ]
Hu S. [2 ]
机构：
[1] Low Emission Vehicle Research Lab, Beijing Institute of Technology, Beijing
[2] Qing Gong College, North China University of Science and Technology, Tangshan
来源：
Qiche Gongcheng/Automotive Engineering | 2020年 / 42卷 / 03期
关键词：
ECMS; Energy management strategy; Equivalent factor optimization; Improved shooting algorithm; PHEB;
D O I：
10.19562/j.chinasae.qcgc.2020.03.003
中图分类号：
学科分类号：
摘要：
A real-time energy management strategy based on equivalent factor optimization is proposed for a plug-in hybrid electric bus (PHEB). Firstly, a fast calculation method of equivalent factor (EF) is designed, in which the range of EF is determined first according to the power parameters of vehicle, then the EF is quickly calculated by shooting algorithm. Next, an adaptive equivalent fuel consumption minimization strategy (A-ECMS) based on linear decline of battery state of charge (SOC) is proposed, and by utilizing the vehicle position information provided by the vehicle global positioning system (GPS) to update the equivalent factor online, the real-time tracking of reference SOC is achieved. Finally, a comparative simulation on A-ECMS is conducted against rule-based strategy, standard ECMS and dynamic programming strategy, and the results show that the A-ECMS proposed based on equivalent factor optimization has best control effects in both fuel economy and robustness of SOC control. © 2020, Society of Automotive Engineers of China. All right reserved.
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页码：292 / 298and306
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共 13 条
  • [1] Martinez C.M., Hu X., Cao D., Et al., Energy management in plug-in hybrid electric vehicles: recent progress and a connected vehicles perspective, IEEE Trans.Veh. Technol., 66, pp. 4534-4549, (2017)
  • [2] Amini M.H., Islam A., Allocation of electric vehicle's parking lots in distribution network, IEEE PES Innovative Smart Grid Technologies Conference (ISGT), pp. 1-5, (2014)
  • [3] Li G., Zhang J., He H., Battery SOC constraint comparison for predictive energy management of plug-in hybrid electric bus, Applied Energy, 194, pp. 578-587, (2017)
  • [4] Pisu P., Rizzoni G., A comparative study of supervisory control strategies for hybrid electric vehicles, IEEE Trans Contr Syst Technol, 15, pp. 506-518, (2007)
  • [5] Gao Y.M., Ehsani M., Design and control methodology of plug-in hybrid electric vehicles, IEEE Trans Ind Electron, 57, pp. 633-640, (2010)
  • [6] Arabali A., Ghofrani M., Etezadi-Amoli M., Et al., Genetic-algorithm-based optimization approach for energy management, IEEE Trans Power Del, 28, pp. 162-170, (2013)
  • [7] Peng J., He H., Xiong R., Rule based energy management strategy for a series-parallel plug-in hybrid electric bus optimized by dynamic programming, Applied Energy, 185, pp. 1633-1643, (2017)
  • [8] Onori S., Tribioli L., Adaptive pontryagin's minimum principle supervisory controller design for the plug-in hybrid GM chevrolet volt, Applied Energy, 147, pp. 224-234, (2015)
  • [9] Liu H., Wang C., Zhao X., Et al., An adaptive-equivalent consumption minimum strategy for an extended-range electric bus based on target driving cycle generation, Energies, 11, 7, (2018)
  • [10] Yang C., Du S., Li L., Et al., Adaptive real-time optimal energy management strategy based on equivalent factors optimization for plug-in hybrid electric vehicle, Applied Energy, 203, pp. 883-896, (2017)
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