Optimization of Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles Based on Dynamic Programming

被引:53
作者
Du, Changqing [1 ,2 ,3 ]
Huang, Shiyang [1 ,2 ,3 ]
Jiang, Yuyao [4 ]
Wu, Dongmei [1 ,2 ,3 ]
Li, Yang [5 ]
机构
[1] Wuhan Univ Technol, Hubei Key Lab Adv Technol Automot Components, Wuhan 430070, Peoples R China
[2] Foshan Xianhu Lab, Adv Energy Sci & Technol Guangdong Lab, Foshan 528200, Peoples R China
[3] Wuhan Univ Technol, Hubei Res Ctr New Energy & Intelligent Connected, Wuhan 430070, Peoples R China
[4] Shanghai Customs Coll, Sch Customs & Publ Adm, Shanghai 201204, Peoples R China
[5] Tech Ctr Dongfeng Commercial Vehicle, Wuhan 430056, Peoples R China
关键词
electromobility; hybrid drive; fuel cell; energy management; optimization process; fuel economy; durability; OPTIMAL POWER MANAGEMENT; PRINCIPLE; SYSTEM; DESIGN;
D O I
10.3390/en15124325
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Fuel cell hybrid electric vehicles have attracted a large amount of attention in recent years owing to their advantages of zero emissions, high efficiency and low noise. To improve the fuel economy and system durability of vehicles, this paper proposes an energy management strategy optimization method for fuel cell hybrid electric vehicles based on dynamic programming. Rule-based and dynamic-programming-based strategies are developed based on building a fuel cell/battery hybrid system model. The rule-based strategy is improved with a power distribution scheme of dynamic programming strategy to improve the fuel economy of the vehicle. Furthermore, a limit on the rate of change of the output power of the fuel cell system is added to the rule-based strategy to avoid large load changes to improve the durability of the fuel cell. The simulation results show that the equivalent 100 km hydrogen consumption of the strategy based on the dynamic programming optimization rules is reduced by 6.46% compared with that before the improvement, and by limiting the rate of change of the output power of the fuel cell system, the times of large load changes are reduced. Therefore, the strategy based on the dynamic programming optimization rules effectively improves the fuel economy and system durability of vehicles.
引用
收藏
页数:25
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