Energy management of a power-split plug-in hybrid electric vehicle based on genetic algorithm and quadratic programming

被引:212
作者
Chen, Zheng [1 ]
Mi, Chris Chunting [1 ]
Xiong, Rui [1 ]
Xu, Jun [1 ]
You, Chenwen [1 ]
机构
[1] Univ Michigan, Dearborn, MI 48128 USA
基金
美国国家科学基金会;
关键词
Fuel-rate; Genetic algorithm (GA); Plug-in hybrid electric vehicle (PHEV); Quadratic programming (QP); State of charge (SOC); State of health (SOH); BATTERY STATE; OPTIMIZATION;
D O I
10.1016/j.jpowsour.2013.09.085
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
This paper introduces an online and intelligent energy management controller to improve the fuel economy of a power-split plug-in hybrid electric vehicle (PHEV). Based on analytic analysis between fuelrate and battery current at different driveline power and vehicle speed, quadratic equations are applied to simulate the relationship between battery current and vehicle fuel-rate. The power threshold at which engine is turned on is optimized by genetic algorithm (GA) based on vehicle fuel-rate, battery state of charge (SOC) and driveline power demand. The optimal battery current when the engine is on is calculated using quadratic programming (QP) method. The proposed algorithm can control the battery current effectively, which makes the engine work more efficiently and thus reduce the fuel-consumption. Moreover, the controller is still applicable when the battery is unhealthy. Numerical simulations validated the feasibility of the proposed controller. (C) 2013 Elsevier B.V. All rights reserved.
引用
收藏
页码:416 / 426
页数:11
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