Optimal online energy management strategy of a fuel cell hybrid bus via reinforcement learning

被引：0
|
作者：
Vehicle Measurement Control and Safety Key Laboratory of Sichuan Province, School of Automobile and Transportation, Xihua University, Chengdu [1 ]
610039, China
不详 [2 ]
610039, China
不详 [3 ]
611730, China
不详 [4 ]
41296, Sweden
机构：
来源：
Energy Convers. Manage. | 2024年
关键词：
D O I：
暂无
中图分类号：
学科分类号：
摘要：
An energy management strategy (EMS) based on reinforcement learning is proposed in this study to enhance the fuel economy and durability of a fuel cell hybrid bus (FCHB). Firstly, a comprehensive powertrain system model for the FCHB is established, mainly including the FCHB's power balance, fuel cell system (FCS) efficiency, and aging models. Secondly, the state–action space, state transition probability matrix (TPM), and multi-objective reward function of Q-learning algorithm are designed to improve the fuel economy and the durability of power sources. The FCHB's demand power and battery state of charge (SOC) serve as the state variables and the FCS output power is used as the action variable. Using the demonstration FCHB data, a state TPM is created to represent the overall operation. Finally, an EMS employing Q-learning is formulated to optimize the fuel economy of FCHB, maintain battery SOC, suppress FCS power fluctuations, and enhance FCS lifetime. The proposed EMS is tested and verified through hardware-in-the-loop (HIL) tests. The simulation results demonstrate the effectiveness of the proposed strategy. Compared to a rule-based EMS, the Q-learning-based EMS can improve the energy economy by 7.8%. Furthermore, it is only a 3.7% difference to the best energy economy under dynamic optimization, while effectively reducing the decline and enhancing the durability of the FCS. © 2023 Elsevier Ltd
引用
收藏
相关论文
共 50 条
  • [21] Deep reinforcement learning based energy management strategy for range extend fuel cell hybrid electric vehicle
    Huang, Yin
    Hu, Haoqin
    Tan, Jiaqi
    Lu, Chenlei
    Xuan, Dongji
    ENERGY CONVERSION AND MANAGEMENT, 2023, 277
  • [22] Deep stochastic reinforcement learning-based energy management strategy for fuel cell hybrid electric vehicles
    Jouda, Basel
    Al-Mahasneh, Ahmad Jobran
    Abu Mallouh, Mohammed
    ENERGY CONVERSION AND MANAGEMENT, 2024, 301
  • [23] Energy Management Strategy based on Reinforcement Learning for Fuel Cell Hybrid Vehicle with A New Reward Function Approach
    Baumler, Antoine
    Benterki, Abdelmoudjib
    2023 IEEE VEHICLE POWER AND PROPULSION CONFERENCE, VPPC, 2023,
  • [24] A reinforcement learning energy management strategy for fuel cell hybrid electric vehicles considering driving condition classification
    Kang, Xu
    Wang, Yujie
    Chen, Zonghai
    SUSTAINABLE ENERGY GRIDS & NETWORKS, 2024, 38
  • [25] Reinforcement Learning based Energy Management for Fuel Cell Hybrid Electric Vehicles
    Guo, Liang
    Li, Zhongliang
    Outbib, Rachid
    IECON 2021 - 47TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY, 2021,
  • [26] Training-efficient and cost-optimal energy management for fuel cell hybrid electric bus based on a novel distributed deep reinforcement learning framework
    Huang, Ruchen
    He, Hongwen
    Gao, Miaojue
    APPLIED ENERGY, 2023, 346
  • [27] Energy management of fuel cell hybrid electric bus in mountainous regions: A deep reinforcement learning approach considering terrain characteristics
    Tang, Tianfeng
    Peng, Qianlong
    Shi, Qing
    Peng, Qingguo
    Zhao, Jin
    Chen, Chaoyi
    Wang, Guangwei
    ENERGY, 2024, 311
  • [28] Optimal Dimensioning and Power Management of a Fuel Cell/Battery Hybrid Bus via Convex Programming
    Hu, Xiaosong
    Murgovski, Nikolce
    Johannesson, Lars Mardh
    Egardt, Bo
    IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2015, 20 (01) : 457 - 468
  • [29] Modeling and Energy Management Strategy Research of Fuel Cell Bus
    Wang Z.
    Xie Y.
    Sun W.
    Zang P.
    Tongji Daxue Xuebao/Journal of Tongji University, 2019, 47 (01): : 97 - 103and123
  • [30] An Economic Driving Energy Management Strategy for the Fuel Cell Bus
    Guo, Jinquan
    He, Hongwen
    Wei, Zhongbao
    Li, Jianwei
    IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION, 2023, 9 (04) : 5074 - 5084
12345