An adaptive co-state design method for PMP-based energy management of plug-in hybrid electric vehicles based on fuzzy logical control

被引：0
|
作者：
Liu, Xiaodong [1 ]
Du, Juan [1 ]
Ma, Jian [2 ]
Liu, Gang [3 ]
Xiong, Yanfeng [3 ]
机构：
[1] School of Mechanical & Automotive Engineering, Liaocheng University, Shandong, Liaocheng,252000, China
[2] School of Automobile, Chang'an University, Xi'an,710064, China
[3] Beijing Foton Daimler Automotive Co., Ltd, Huairou, Beijing,101400, China
来源：
Journal of Energy Storage | 2024年 / 102卷
关键词：
The determination of the optimal co-state in Pontryagin's minimum principle-based (PMP-based) energy management strategy (EMS) in real-time remains a significant challenge. This paper proposes a fuzzy logic-based approach to tackle this problem. Firstly; an offline optimization method based on the multi-island genetic algorithm (MIGA) is proposed to calculate the optimal co-state of the PMP-based EMS for a plug-in hybrid electric vehicle (PHEV) based on the provided driving cycles. Secondly; a comprehensive evaluation of the influence on the optimal co-state is conducted based on the vehicle's velocity and load; utilizing real-life and representative driving scenarios. Subsequently; a fuzzy logic-based controller is formulated for online modification of the co-state; with inputs including vehicle velocity; load; and acceleration. Finally; the proposed method is evaluated against benchmarks including dynamic programming (DP); charge-depleting and charge-sustaining (CD-CS); and PMP-constant solutions using nine actual driving cycles. The findings demonstrate that the controller with the fuzzy logic method displays significant adaptability to diverse driving cycles. The proposed PMP-adaptive strategy exhibits significant improvement compared to CD-CS; with energy-saving effectiveness approaching DP solutions. In addition; the computational efficiency of the PMP-adaptive is superior to that of the CD-CS; which presents a valuable advantage for real-time applications. © 2024 Elsevier Ltd;
D O I：
10.1016/j.est.2024.114118
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