Journal of South China University of Technology(Natural Science) >
Energy Management Strategies for Fuel Cell Vehicle Considering Air Conditioning Systems
Received date: 2024-08-04
Online published: 2024-12-13
Supported by
the National Natural Science Foundation of China(52472411)
In the actual operation of fuel cell hybrid electric vehicles, the air conditioning system provides a comfortable environment for drivers and passengers. However, the performance of the air conditioning system interacts with the vehicle’s energy distribution during operation. Therefore, it is necessary to integrate the air conditioning system into the energy management strategy, and design an energy management strategy that ensures the cabin temperature comfort requirements while also considering the overall hydrogen consumption efficiency of the vehicle. Firstly, based on the vehicle dynamics model, the heat balance equation was used to establish the heat pump air-conditioning system model and heat load model. Then, the dual delay depth deterministic strategy gradient (TD3-PER) algorithm combining the double Q network and the depth deterministic strategy gradient was used to establish the energy management strategy considering the energy consumption of the air conditioning system and the vehicle operation demand. Simulation under the typical NEDC driving cycle shows that with the TD3-PER energy management strategy, the air conditioning system can rapidly bring the cabin temperature to and maintain it within the comfortable range of 22 ℃ to 26 ℃ in 100 seconds, ensuring cooling/heating performance to maintain cabin comfort. This validates the feasibility of the TD3-PER energy management strategy when considering the air conditioning system. During cooling/heating operation, compared to the traditional Deep Deterministic Policy Gradient (DDPG) algorithm, the power distribution strategy based on the TD3-PER algorithm can extend the lifespan of both the fuel cell and the battery. Additionally, in terms of hydrogen consumption, the TD3-PER-based strategy can improve fuel economy by 2.59 percentage points during cooling and 3.58 percentage points during heating. This demonstrates that the TD3-PER algorithm-based energy management strategy offers significant advantages over traditional algorithms in terms of reducing hydrogen consumption and improving overall vehicle efficiency.
ZHAO Youqun , XU Zhou , YU Zhihao , LIN Fen , HE Kunpeng , YOU Qingshen . Energy Management Strategies for Fuel Cell Vehicle Considering Air Conditioning Systems[J]. Journal of South China University of Technology(Natural Science), 2025 , 53(6) : 56 -65 . DOI: 10.12141/j.issn.1000-565X.240396
| 1 | 郭硕，赵又群，潘陈兵，等 ．基于电堆输出电压的氢燃料电池系统水平衡控制方法：CN202310631515.0［P］．2023-08-01. |
| 2 | SAMPIETRO J L， PUIG V， COSTA-CASTELLó R ．Optimal sizing of storage elements for a vehicle based on fuel cells，supercapacitors，and batteries［J］．Energies， 2019，12（5）：925/1-27. |
| 3 | PENG J K， HE H W， XIONG R ．Study on energy management strategies for series-parallel plug-in hybrid electric buses［J］．Energy Procedia，2015，75： 1926-1931. |
| 4 | GHARIBEH H F， YAZDANKHAH A S， AZIZIAN M R ． Energy management of fuel cell electric vehicles based on working condition identification of energy storage systems，vehicle driving performance，and dynamic power factor［J］．Journal of Energy Storage，2020，31：101760/1-20. |
| 5 | LIU Y G， LI J， CHEN Z， et al ．Research on a multi-objective hierarchical prediction energy management strategy for range extended fuel cell vehicles［J］．Journal of Power Sources，2019，429：55-66. |
| 6 | TIAN X L， TAO F Z， FU Z M，et al ．Optimizing fuel economy of fuel cell hybrid electric vehicle based on energy management strategy with integrated rapid thermal regulation［J］．Engineering Applications of Artificial Intelligence，2024，132：107880/1-15. |
| 7 | ZHANG Y X， MA R， ZHAO D D，et al ．A novel energy management strategy based on dual reward function Q-learning for fuel cell hybrid electric vehicle［J］．IEEE Transactions on Industrial Electronics，2022，69（2）：1537-1547. |
| 8 | HUANG G， ZHAO P， ZHANG G L ．Real-time battery thermal management for electric vehicles based on deep reinforcement learning［J］．IEEE Internet of Things Journal，2022，9（15）：14060-14072. |
| 9 | CHIU C C， TSAI N C， LIN C C ．Near-optimal order-reduced control for A/C （air-conditioning） system of EVs （electric vehicles）［J］．Energy，2014，66（1）：342-353. |
| 10 | 张佳骞 ．包含空调系统的混合动力汽车能量管理策略优化仿真研究［D］．武汉：华中科技大学，2015. |
| 11 | HE H W， JIA H， SUN C，et al ．Stochastic model predictive control of air conditioning system for electric vehicles：sensitivity study， comparison and improvement［J］．IEEE Transactions on Industrial Informatics，2018，14（9）：4179-4189. |
| 12 | 曾育平 ．计及温度效应的插电式混合动力汽车实时优化控制策略［D］．重庆：重庆大学，2015. |
| 13 | 虞志浩，赵又群，潘陈兵，等 ．基于TD3-PER的氢燃料电池混合动力汽车能量管理策略研究［J］．汽车技术，2024（1）：13-19. |
| YU Zhihao， ZHAO Youqun， PAN Chenbing，et al ．Research on energy management strategy for hydrogen fuel cell hybrid vehicles based on TD3-PER［J］．Automobile Technology，2024（1）：13-19. | |
| 14 | 李明，薛庆峰，张可欣，等 ．电动汽车热泵空调系统性能分析［J］．吉林大学学报（工学版），2021，51（6）：1943-1952. |
| LI Ming， XUE Qingfeng F， ZHANG Kexin，et al ．Performance analysis of electric vehicle heat pump air conditioning system［J］．Journal of Jilin University （Engineering and Technology Edition），2021，51（6）：1943-1952. | |
| 15 | 张可欣 ．电动汽车热泵空调系统性能分析平台设计［D］．长春：吉林大学，2020. |
| 16 | KHAYYAM H， KOUZANI A Z， HU E J，et al ．Coordinated energy management of vehicle air conditioning system［J］．Applied Thermal Engineering，2011，31（5）：750-764. |
| 17 | MARCOS D， PINO F J， BORDONS C，et al ．The development and validation of a thermal model for the cabin of a vehicle［J］?．Applied Thermal Engineering，2014，66（1）：646-656. |
| 18 | KAMBLY K R， BRADLEY T H ．Estimating the HVAC energy consumption of plug-in electric vehicles［J］．Journal of Power Sources，2014，259：117-124. |
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