The Multi-Objective Optimization of Powertrain Design and Energy Management Strategy for Fuel Cell–Battery Electric Vehicle

Jiaming Zhou, Chunxiao Feng, Qingqing Su, Shangfeng Jiang, Zhixian Fan, Jiageng Ruan, Shikai Sun and Leli Hu
Additional contact information
Jiaming Zhou: School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China
Chunxiao Feng: School of Automotive Engineering, Shandong Jiaotong University, Jinan 250357, China
Qingqing Su: School of Automotive Engineering, Shandong Jiaotong University, Jinan 250357, China
Shangfeng Jiang: Yutong Bus Co., Ltd., Zhengzhou 450016, China
Zhixian Fan: Zhongtong Bus Holding Co., Ltd., Liaocheng 252000, China
Jiageng Ruan: Department of Materials and Manufacturing, Beijing University of Technology, Beijing 100124, China
Shikai Sun: China Transport Telecommunications & Information Center, Beijing 100011, China
Leli Hu: School of Automobile and Transportation Engineering, Jiangsu University, Zhenjiang 212013, China

Sustainability, 2022, vol. 14, issue 10, 1-19

Abstract: Considering the limited driving range and inconvenient energy replenishment way of battery electric vehicle, fuel cell electric vehicles (FC EVs) are taken as a promising way to meet the requirements for long-distance low-carbon driving. However, due to the limitation of FC power ability, a battery is usually adopted as the supplement power source to fill the gap between the requirement of driving and the serviceability of FC. In consequence, energy management is essential and crucial to an efficient power flow to the wheel. In this paper, a self-optimizing power matching strategy is proposed, considering the energy efficiency and battery degradation, via implementing a deep deterministic policy gradient. Based on the proposed strategy, less energy consumption and longer FC and battery life can be expected in FC EV powertrain with optimal hybridization degree.

Keywords: fuel cell; hybrid electric vehicle; EMS; particle swarm optimization (PSO); machine learning (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

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