文献类型：期刊文献

英文题名：Review of control strategies for onboard fuel cells: Insights from degradation mechanisms under variable load conditions

作者：Wu, Qi[1];Li, Songyang[1];Hou, Zhongjun[2];Lu, Liyang[2];Gu, Xin[2];Chen, Haofeng[1,3];Luan, Weiling[1]

机构：[1]East China Univ Sci & Technol, CPCIF Key Lab Adv Battery Syst & Safety, Shanghai 200237, Peoples R China;[2]Shanghai Hydrogen Prop Technol Co Ltd, Shanghai 201800, Peoples R China;[3]Univ Strathclyde, Dept Mech & Aerosp Engn, Glasgow City G1 1XJ, Scotland

年份：2024

卷号：110

起止页码：628

外文期刊名：INTERNATIONAL JOURNAL OF HYDROGEN ENERGY

收录：;EI(收录号：20250817916565);WOS:【SCI-EXPANDED(收录号:WOS:001430661300001)】；

基金：The authors gratefully acknowledge the support from the National Natural Science Foundation of China (52375144 and 52375145) during the course of this work.

语种：英文

外文关键词：Fuel cell; Variable load; Degradation mechanism; Control strategy

摘要：This review paper aims to explore the degradation mechanism and control strategies employed for onboard fuel cells operating under changing load conditions. The performance of fuel cells is crucial for various applications, particularly in vehicles, where factors like road conditions and driving habits lead to fluctuating power demands. While current research examines the impact of operating conditions on fuel cell durability and discusses various mitigation approaches, there remains a critical gap in correlating degradation mechanisms with control system strategy optimization. Through systematic analysis, this review identifies three primary degradation mechanisms under variable loads: potential cycle, parameter alternation, and localized gas starvation-each influenced by changes in power demand. These mechanisms are found to directly correspond to the optimization requirements of three key systems: Power electrical system, Water and thermal management systems, and Reactant system, respectively. The complex interplay of parameters such as temperature, pressure, and humidity can fluctuate beyond the optimal range, resulting in irreversible damage to fuel cell components. Such parameter variations cause irreversible damage to fuel cell components. Traditional control methods have limitations in handling multiple parameter changes. The integration of artificial intelligence (AI) with conventional control methods shows better results. This combined approach offers improved adaptability and efficiency for dynamic operations. Understanding degradation mechanisms is essential for control system optimization. The implementation of integrated control strategies can extend fuel cell life and enhance their performance under variable load conditions.