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Reinforcement learning based energy management systems and hydrogen refuelling stations for fuel cell electric vehicles: An overview

机译:基于强化学习的燃料电池电动汽车能源管理系统和加氢站:概述

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? 2022 Hydrogen Energy Publications LLCThis paper examines the current state of the art of hydrogen refuelling stations-based production and storage systems for fuel cell hybrid electric vehicles (FCHEV). Nowadays, the emissions are increasing rapidly due to the usage of fossil fuels and the demand for hydrogen refuelling stations (HRS) is emerging to replace the conventional vehicles with FCHEVs. Hence, the availability of HRS and its economic aspects are discussed. In addition, a comprehensive study is presented on the energy storage systems such as batteries, supercapacitors and fuel cells which play a major role in the FCHEVs. An energy management system (EMS) is essential to meet the load requirement with effective utilisation of power sources with various optimizing techniques. A detailed comparative analysis is presented on the merits of Reinforcement learning (RL) for the FCHEVs. The significant challenges are discussed in depth with potential solutions for future work.
机译:?2022 Hydrogen Energy Publications LLC这篇论文研究了基于加氢站的燃料电池混合动力电动汽车 (FCHEV) 生产和存储系统的当前技术水平。如今,由于化石燃料的使用,排放量正在迅速增加,对加氢站(HRS)的需求正在兴起,以用FCHEV取代传统车辆。因此,讨论了HRS的可用性及其经济方面。此外,还对在FCHEV中发挥重要作用的储能系统(如电池、超级电容器和燃料电池)进行了全面研究。能源管理系统 (EMS) 对于通过各种优化技术有效利用电源来满足负载要求至关重要。对FCHEV的强化学习(RL)的优点进行了详细的比较分析。深入讨论了重大挑战,并为未来的工作提供了潜在的解决方案。

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