Optimal Power Allocation Factor Based Real Time Energy Management Strategy for a Plug-in Hybrid Electric Vehicle

被引：0
|
作者：
Liu H. [1 ,2 ]
Li X. [1 ]
Wang W. [1 ,2 ]
Han L. [1 ,2 ]
Yan Z. [1 ]
机构：
[1] School of Mechanical Engineering, Beijing Institute of Technology, Beijing
[2] National Key Lab of Vehicular Transmission, Beijing Institute of Technology, Beijing
来源：
Jixie Gongcheng Xuebao/Journal of Mechanical Engineering | 2019年 / 55卷 / 04期
关键词：
Energy management strategy; Global optimal model; Plug-in hybrid electric vehicle; Power allocation factor; Real time control;
D O I：
10.3901/JME.2019.04.091
中图分类号：
学科分类号：
摘要：
Plug-in hybrid electric vehicle (PHEV) has the advantages both of traditional hybrid electric vehicle(HEV) and electric vehicle (EV), which not only has long driving distance but only has good fuel economy. Energy management strategy is the key technology for achieving fuel-saving potential. In order to solve the real-time optimization problem of energy management of plug-in hybrid electric vehicle. A PHEV with driving modes manual selection function is regarded as researching object and power allocation factor (PAF) is proposed. When PHEV switches modes from charge-depleting (CD) to charge-sustaining (CS) at any point of SOC, PAF plays a role to adjust the engine best working line dynamically to get a better fuel economy. A global optimization model for PAF is built and adaptive simulated annealing (ASA) algorithm is used to get the optimal PAF offline. The effect of PAF and SOC to fuel economy is observed and the optimal PAF line for real time control is obtained. Then optimal PAF based real time control energy management strategy is proposed and simulation experiment is carried out over two driving cycles. The results indicate that fuel economy of PHEV has an improvement about 16.99 % by PAF-based control strategy. © 2019 Journal of Mechanical Engineering.
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页码：91 / 101
页数：10
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