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A methodology to develop multi-physics dynamic fuel cell system models validated with vehicle realistic drive cycle data

Author

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  • Lopez-Juarez, M.
  • Rockstroh, T.
  • Novella, R.
  • Vijayagopal, R.

Abstract

Fuel cell (FC) technology has been identified as a technically attractive solution to decarbonize the transportation sector, especially for heavy-duty vehicles. In this context, the industry and the scientific community are in need of advanced fuel cell systems (FCS) models that are able to replicate real-world operating conditions. Due to the scarcity of said models in the open literature, this study aimed to develop a comprehensive methodology to calibrate and validate multi-physics dynamic FCS models. Therefore, the key contribution of this paper is the detailed description of the calibration process for each component and the calibration order. The specific focus here was to accurately describe the behavior of the FC stack as well as the cathode, anode, and cooling circuits of the balance of plant. The model was calibrated with the aid of experimental data from a Toyota Mirai FC electric vehicle, which was predominantly retrieved from the vehicle’s Controller Area Network (CAN) bus system thereby negating the need for major intrusion into the powertrain system. The validation process was deemed successful with the model being able to truthfully replicate the characteristics of the FC vehicle operated on the World-wide harmonized Light duty Test Cycle (WLTC) 3b and US06 driving cycle. The time-resolved physical parameters such as the cathode pressure, mass flow, or the FC stack temperature were captured with high fidelity, while the overall performance parameters such as the H2 consumption in the stack and the system, and the compressor energy consumption were predicted accurately with a deviation lower than 0.47%, 1.75% and 1.89% with respect to the experimental data, respectively.

Suggested Citation

  • Lopez-Juarez, M. & Rockstroh, T. & Novella, R. & Vijayagopal, R., 2024. "A methodology to develop multi-physics dynamic fuel cell system models validated with vehicle realistic drive cycle data," Applied Energy, Elsevier, vol. 358(C).
  • Handle: RePEc:eee:appene:v:358:y:2024:i:c:s0306261923019323
    DOI: 10.1016/j.apenergy.2023.122568
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    References listed on IDEAS

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    1. Sara Luciani & Andrea Tonoli, 2022. "Control Strategy Assessment for Improving PEM Fuel Cell System Efficiency in Fuel Cell Hybrid Vehicles," Energies, MDPI, vol. 15(6), pages 1-17, March.
    2. Quan, Shengwei & He, Hongwen & Chen, Jinzhou & Zhang, Zhendong & Han, Ruoyan & Wang, Ya-Xiong, 2023. "Health-aware model predictive energy management for fuel cell electric vehicle based on hybrid modeling method," Energy, Elsevier, vol. 278(PA).
    3. Desantes, J.M. & Novella, R. & Pla, B. & Lopez-Juarez, M., 2022. "A modeling framework for predicting the effect of the operating conditions and component sizing on fuel cell degradation and performance for automotive applications," Applied Energy, Elsevier, vol. 317(C).
    4. Xu, Xiaodan & Aziz, H.M. Abdul & Liu, Haobing & Rodgers, Michael O. & Guensler, Randall, 2020. "A scalable energy modeling framework for electric vehicles in regional transportation networks," Applied Energy, Elsevier, vol. 269(C).
    5. Min, Dehao & Song, Zhen & Chen, Huicui & Wang, Tianxiang & Zhang, Tong, 2022. "Genetic algorithm optimized neural network based fuel cell hybrid electric vehicle energy management strategy under start-stop condition," Applied Energy, Elsevier, vol. 306(PB).
    6. Deng, Zhihua & Chen, Qihong & Zhang, Liyan & Zhou, Keliang & Zong, Yi & Fu, Zhichao & Liu, Hao, 2021. "Data-driven reconstruction of interpretable model for air supply system of proton exchange membrane fuel cell," Applied Energy, Elsevier, vol. 299(C).
    7. Molina, S. & Novella, R. & Pla, B. & Lopez-Juarez, M., 2021. "Optimization and sizing of a fuel cell range extender vehicle for passenger car applications in driving cycle conditions," Applied Energy, Elsevier, vol. 285(C).
    8. Gong, Zhichao & Wang, Bowen & Xu, Yifan & Ni, Meng & Gao, Qingchen & Hou, Zhongjun & Cai, Jun & Gu, Xin & Yuan, Xinjie & Jiao, Kui, 2022. "Adaptive optimization strategy of air supply for automotive polymer electrolyte membrane fuel cell in life cycle," Applied Energy, Elsevier, vol. 325(C).
    9. Asensio, F.J. & San Martín, J.I. & Zamora, I. & Oñederra, O., 2018. "Model for optimal management of the cooling system of a fuel cell-based combined heat and power system for developing optimization control strategies," Applied Energy, Elsevier, vol. 211(C), pages 413-430.
    10. Desantes, J.M. & Novella, R. & Pla, B. & Lopez-Juarez, M., 2021. "Impact of fuel cell range extender powertrain design on greenhouse gases and NOX emissions in automotive applications," Applied Energy, Elsevier, vol. 302(C).
    11. Yang, Zirong & Du, Qing & Jia, Zhiwei & Yang, Chunguang & Xuan, Jin & Jiao, Kui, 2019. "A comprehensive proton exchange membrane fuel cell system model integrating various auxiliary subsystems," Applied Energy, Elsevier, vol. 256(C).
    12. Zhang, Hongtao & Li, Xianguo & Liu, Xinzhi & Yan, Jinyue, 2019. "Enhancing fuel cell durability for fuel cell plug-in hybrid electric vehicles through strategic power management," Applied Energy, Elsevier, vol. 241(C), pages 483-490.
    13. Anselma, Pier Giuseppe & Belingardi, Giovanni, 2022. "Fuel cell electrified propulsion systems for long-haul heavy-duty trucks: present and future cost-oriented sizing," Applied Energy, Elsevier, vol. 321(C).
    14. Zeng, Tao & Zhang, Caizhi & Hu, Minghui & Chen, Yan & Yuan, Changrong & Chen, Jingrui & Zhou, Anjian, 2018. "Modelling and predicting energy consumption of a range extender fuel cell hybrid vehicle," Energy, Elsevier, vol. 165(PB), pages 187-197.
    15. Li, Bing & Wan, Kechuang & Xie, Meng & Chu, Tiankuo & Wang, Xiaolei & Li, Xiang & Yang, Daijun & Ming, Pingwen & Zhang, Cunman, 2022. "Durability degradation mechanism and consistency analysis for proton exchange membrane fuel cell stack," Applied Energy, Elsevier, vol. 314(C).
    16. Shan, Jing & Gazdzicki, Pawel & Lin, Rui & Schulze, Mathias & Friedrich, K. Andreas, 2017. "Local resolved investigation of hydrogen crossover in polymer electrolyte fuel cell," Energy, Elsevier, vol. 128(C), pages 357-365.
    17. Wu, Zhen & Tan, Peng & Chen, Bin & Cai, Weizi & Chen, Meina & Xu, Xiaoming & Zhang, Zaoxiao & Ni, Meng, 2019. "Dynamic modeling and operation strategy of an NG-fueled SOFC-WGS-TSA-PEMFC hybrid energy conversion system for fuel cell vehicle by using MATLAB/SIMULINK," Energy, Elsevier, vol. 175(C), pages 567-579.
    18. Deng, Zhihua & Chen, Qihong & Zhang, Liyan & Zong, Yi & Zhou, Keliang & Fu, Zhichao, 2020. "Control oriented data driven linear parameter varying model for proton exchange membrane fuel cell systems," Applied Energy, Elsevier, vol. 277(C).
    19. Park, Junhwi & Lee, Donguk & Lim, Daejin & Yee, Kwanjung, 2022. "A refined sizing method of fuel cell-battery hybrid system for eVTOL aircraft," Applied Energy, Elsevier, vol. 328(C).
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    Cited by:

    1. Orazio Barbera, 2024. "Fuel Cell-Based and Hybrid Power Generation Systems Modelling," Energies, MDPI, vol. 17(13), pages 1-6, July.

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