TY - JOUR
T1 - Health-aware energy management strategy for fuel cell hybrid bus considering air-conditioning control based on TD3 algorithm
AU - Jia, Chunchun
AU - Li, Kunang
AU - He, Hongwen
AU - Zhou, Jiaming
AU - Li, Jianwei
AU - Wei, Zhongbao
N1 - Publisher Copyright:
© 2023 Elsevier Ltd
PY - 2023/11/15
Y1 - 2023/11/15
N2 - The air-conditioning system (ACS), as a high-power component on the fuel cell hybrid electric bus (FCHEB), has a significant impact on the whole vehicle economy while maintaining comfortable temperature. Achieving cabin comfort in a way that reduces the whole vehicle operating cost is a great challenge. This task requires excellent coordination between the ACS and the on-board energy sources. Given that, this paper proposes an energy management strategy (EMS) with on-board energy sources health awareness considering air-conditioning control. Specifically, firstly, cabin comfort is combined with fuel cell/battery durability control to minimize total vehicle operating cost while satisfying cabin comfort. Secondly, the state-of-the-art twin delayed deep deterministic policy gradient algorithm is adopted to improve the training efficiency and optimization capability of the EMS to achieve the best power allocation. Finally, comparative analysis is performed to verify the effectiveness of the proposed EMS, and the results show that the proposed strategy can enhance training efficiency by 56.7% and decrease total operating cost by 8.58% compared to the benchmark strategy based on deep deterministic policy gradient.
AB - The air-conditioning system (ACS), as a high-power component on the fuel cell hybrid electric bus (FCHEB), has a significant impact on the whole vehicle economy while maintaining comfortable temperature. Achieving cabin comfort in a way that reduces the whole vehicle operating cost is a great challenge. This task requires excellent coordination between the ACS and the on-board energy sources. Given that, this paper proposes an energy management strategy (EMS) with on-board energy sources health awareness considering air-conditioning control. Specifically, firstly, cabin comfort is combined with fuel cell/battery durability control to minimize total vehicle operating cost while satisfying cabin comfort. Secondly, the state-of-the-art twin delayed deep deterministic policy gradient algorithm is adopted to improve the training efficiency and optimization capability of the EMS to achieve the best power allocation. Finally, comparative analysis is performed to verify the effectiveness of the proposed EMS, and the results show that the proposed strategy can enhance training efficiency by 56.7% and decrease total operating cost by 8.58% compared to the benchmark strategy based on deep deterministic policy gradient.
KW - Air-conditioning system
KW - Cabin comfort
KW - Energy management strategy
KW - Fuel cell hybrid electric bus
KW - Fuel cell/battery durability
UR - http://www.scopus.com/inward/record.url?scp=85165631341&partnerID=8YFLogxK
U2 - 10.1016/j.energy.2023.128462
DO - 10.1016/j.energy.2023.128462
M3 - Article
AN - SCOPUS:85165631341
SN - 0360-5442
VL - 283
JO - Energy
JF - Energy
M1 - 128462
ER -