PHEV Composite Energy Storage System Design and Parameter Optimization Based on MODA

被引：0
|
作者：
Wu Z.-Q. [1 ]
Ma B.-Y. [1 ]
Hu X.-Y. [1 ]
Hou L.-C. [1 ]
Cao B.-L. [1 ]
机构：
[1] College of Electrical Engineering, Yanshan University, Qinhuangdao
来源：
Zhongguo Gonglu Xuebao/China Journal of Highway and Transport | 2022年 / 35卷 / 05期
关键词：
Automotive engineering; HESS; MODA; Pareto; Real-time wavelet transform;
D O I：
10.19721/j.cnki.1001-7372.2022.05.024
中图分类号：
学科分类号：
摘要：
To improve the fuel economy of plug-in hybrid electric vehicle, reduce pollutant emissions, and solve the problem of low specific power of the single-power battery that unable to respond to transient power demand in plug-in hybrid, a hybrid energy storage system (HESS) with parallel connection between battery and super-capacitor was designed.In the HESS, a real-time wavelet power allocation strategy with a sliding window was adopt, and the length of the sliding window was selected. This power distribution strategy decomposed the required power of the HESS into high-frequency and low-frequency parts.The super-capacitor received high-frequency components and the battery received low-frequency components, so the impact of high-frequency components on the battery was avoided and the durability and reliability of the battery was improved. A rule-based control strategy was implemented, with vehicle fuel consumption and pollutant emissions as the optimization goals, and a multi-objective dragonfly algorithm (MODA) was used to optimize related control parameters.A plug-in hybrid electric vehicle with the HESS was developed based on ADVISOR software, and a simulation analysis was carried out in the New European Driving Cycle, the effectiveness of the algorithm was verified by comparison with the non-dominated sorting genetic algorithm with elite strategy (NSGA-Ⅱ). The research results show that the fuel consumption per 100 kilometers of the vehicle optimized by the MODA is reduced by 12.71% on average, and the comprehensive pollutant emission performance is reduced by 10.05% on average. Compared with the optimization before, the engine output power is reduced and the motor output power is increased, the working efficiency of the engine and the motor has been significantly improved. The convergence and coverage of the Pareto optimal solution is better than that of the NSGA-Ⅱ, and at the same time, the multiple Pareto optimal solution provides more choice space for vehicle design and optimization. © 2022, Editorial Department of China Journal of Highway and Transport. All right reserved.
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页码：254 / 265
页数：11
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