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Performance evaluation of a hybrid hydrogen fuel cell/battery bus with fuel cell degradation and battery aging

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  • Mousavi, Shadi Bashiri
  • Ahmadi, Pouria
  • Raeesi, Mehrdad

Abstract

Public transportation is an effective way to reduce emissions and decrease in fossil fuel consumption challenges. The idea of employing green energy systems in public transportation can significantly change the quality of life in the near future. In this regard, the hydrogen fuel cell bus which uses hydrogen as a main fuel and utilizes small battery systems for the rest of the required energy demands is simulated and investigated in this research study. Additionally, two real driving cycles are employed for dynamic modeling. Therefore, to fill the gaps in the field of public bus performance, heating, ventilation and air conditioning (HVAC) systems, fuel cell degradation, and battery aging, a precise model is presented in the Simcenter Amesim software. Time-dependent thermal loads and variations of passenger numbers are also considered for the HVAC system. Machine learning techniques are employed to predict fuel cell degradation and battery aging. The model is based on calendar and cyclic aging phenomena. Finally, the performance of the hybrid bus is evaluated during operation. Results show that more than 60% of energy is consumed in electric motors and increasing the number of passengers directly affects the amount of energy consumption reaches the maximum of 28 MJ for 40 passengers and additionally affects the final cabin temperature. After 2000 h of operation, the ammount of hydrogen consumption increased by approximately 10% compared to a new bus due to fuel cell degradation. In addition, the capacity loss of the battery reaches 17.6% after a year for the maximum ambient temperature of 36 °C.

Suggested Citation

  • Mousavi, Shadi Bashiri & Ahmadi, Pouria & Raeesi, Mehrdad, 2024. "Performance evaluation of a hybrid hydrogen fuel cell/battery bus with fuel cell degradation and battery aging," Renewable Energy, Elsevier, vol. 227(C).
  • Handle: RePEc:eee:renene:v:227:y:2024:i:c:s0960148124005214
    DOI: 10.1016/j.renene.2024.120456
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    References listed on IDEAS

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    1. Shrivastava, Prashant & Soon, Tey Kok & Idris, Mohd Yamani Idna Bin & Mekhilef, Saad, 2019. "Overview of model-based online state-of-charge estimation using Kalman filter family for lithium-ion batteries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
    2. Chen, Dongfang & Pei, Pucheng & Meng, Yining & Ren, Peng & Li, Yuehua & Wang, Mingkai & Wang, Xizhong, 2022. "Novel extraction method of working condition spectrum for the lifetime prediction and energy management strategy evaluation of automotive fuel cells," Energy, Elsevier, vol. 255(C).
    3. Kalghatgi, Gautam, 2018. "Is it really the end of internal combustion engines and petroleum in transport?," Applied Energy, Elsevier, vol. 225(C), pages 965-974.
    4. Hu, Jianjun & Wang, Yangguang & Zou, Lingbo & Wang, Zhouxin, 2023. "Adaptive rule control strategy for composite energy storage fuel cell vehicle based on vehicle operating state recognition," Renewable Energy, Elsevier, vol. 204(C), pages 166-175.
    5. Sahraei, Mohammad Ali & Duman, Hakan & Çodur, Muhammed Yasin & Eyduran, Ecevit, 2021. "Prediction of transportation energy demand: Multivariate Adaptive Regression Splines," Energy, Elsevier, vol. 224(C).
    6. Izadi, Ali & Shahafve, Masoomeh & Ahmadi, Pouria & Hanafizadeh, Pedram, 2023. "Design, and optimization of COVID-19 hospital wards to produce Oxygen and electricity through solar PV panels with hydrogen storage systems by neural network-genetic algorithm," Energy, Elsevier, vol. 263(PA).
    7. Weckerle, C. & Nasir, M. & Hegner, R. & Bürger, I. & Linder, M., 2020. "A metal hydride air-conditioning system for fuel cell vehicles – Functional demonstration," Applied Energy, Elsevier, vol. 259(C).
    8. Guo, Yuanjun & Yang, Zhile & Liu, Kailong & Zhang, Yanhui & Feng, Wei, 2021. "A compact and optimized neural network approach for battery state-of-charge estimation of energy storage system," Energy, Elsevier, vol. 219(C).
    9. Mousavi, Shadi Bashiri & Ahmadi, Pouria & Adib, Mahdieh & Izadi, Ali, 2023. "Techno-economic assessment of an efficient liquid air energy storage with ejector refrigeration cycle for peak shaving of renewable energies," Renewable Energy, Elsevier, vol. 214(C), pages 96-113.
    10. Li, Yanwen & Wang, Chao & Gong, Jinfeng, 2017. "A multi-model probability SOC fusion estimation approach using an improved adaptive unscented Kalman filter technique," Energy, Elsevier, vol. 141(C), pages 1402-1415.
    11. Ajanovic, A. & Glatt, A. & Haas, R., 2021. "Prospects and impediments for hydrogen fuel cell buses," Energy, Elsevier, vol. 235(C).
    12. Zhou, Yang & Ravey, Alexandre & Péra, Marie-Cecile, 2020. "Multi-mode predictive energy management for fuel cell hybrid electric vehicles using Markov driving pattern recognizer," Applied Energy, Elsevier, vol. 258(C).
    13. İnci, Mustafa & Büyük, Mehmet & Demir, Mehmet Hakan & İlbey, Göktürk, 2021. "A review and research on fuel cell electric vehicles: Topologies, power electronic converters, energy management methods, technical challenges, marketing and future aspects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    14. Ahmadi, Pouria & Raeesi, Mehrdad & Changizian, Sina & Teimouri, Aidin & Khoshnevisan, Alireza, 2022. "Lifecycle assessment of diesel, diesel-electric and hydrogen fuel cell transit buses with fuel cell degradation and battery aging using machine learning techniques," Energy, Elsevier, vol. 259(C).
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