Comparative study of energy management in parallel hybrid electric vehicles considering battery ageing

电池(电) 老化 能源管理 汽车工程 电动汽车 工程类 能量(信号处理) 医学 物理 功率(物理) 量子力学 内科学
作者
Fengqi Zhang,Lehua Xiao,Serdar Coskun,Hui Pang,Shaobo Xie,Kailong Liu,Yahui Cui
出处
期刊:Energy [Elsevier BV]
卷期号:264: 123219-123219 被引量:63
标识
DOI:10.1016/j.energy.2022.123219
摘要

This article presents a thorough comparative study of energy management strategies (EMSs) for a parallel hybrid electric vehicle (HEV), while the battery ageing is considered. The principle of dynamic programming (DP), Pontryagin's minimum principle (PMP), and equivalent consumption minimization strategy (ECMS) considering battery ageing is elaborated. The gearshift map is obtained from the optimization results in DP to prevent frequent shifts by taking into account drivability and fuel economy, which is then applied in the PMP and ECMS. Comparison of different EMSs is conducted by means of fuel economy, battery state-of-charge charge-sustainability, and computational efficiency. Moreover, battery ageing is included in the optimization solution by utilizing a control-oriented model, aiming to fulfill one of the main cost-related design concerns in the development of HEVs. Through a unified framework, the torque split and battery degradation are simultaneously optimized in this study. Simulations are carried out for DP, PMP, and ECMS to analyze their features, wherein results indicate that DP obtains the best fuel economy compared with other methods. Additionally, the difference between DP and PMP is about 2% in terms of fuel economy. The observations from analysis results provide a good insight into the merits and demerits of each approach. • Comparative studies of different energy management strategies are performed for a parallel HEV. • The fuel economy, drivability and battery ageing are concurrently considered. • The gearshift map is extracted considering drivability and fuel economy simultaneously. • A control-oriented battery ageing model is given to consider battery ageing dynamics into the optimization solution. • The performance for these methods under China's typical city driving conditions is analyzed.
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