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Sizing for fuel cell/supercapacitor hybrid vehicles based on stochastic driving cycles

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  • Feroldi, Diego
  • Carignano, Mauro

Abstract

In this article, a methodology for the sizing and analysis of fuel cell/supercapacitor hybrid vehicles is presented. The proposed sizing methodology is based on the fulfilment of power requirements, including sustained speed tests and stochastic driving cycles. The procedure to generate driving cycles is also presented in this paper. The sizing algorithm explicitly accounts for the Equivalent Consumption Minimization Strategy (ECMS). The performance is compared with optimal consumption, which is found using an off-line strategy via Dynamic Programming. The sizing methodology provides guidance for sizing the fuel cell and the supercapacitor number. The results also include analysis on oversizing the fuel cell and varying the parameters of the energy management strategy. The simulation results highlight the importance of integrating sizing and energy management into fuel cell hybrid vehicles.

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  • Feroldi, Diego & Carignano, Mauro, 2016. "Sizing for fuel cell/supercapacitor hybrid vehicles based on stochastic driving cycles," Applied Energy, Elsevier, vol. 183(C), pages 645-658.
    • Handle: RePEc:eee:appene:v:183:y:2016:i:c:p:645-658
    DOI: 10.1016/j.apenergy.2016.09.008
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    2. Carmen Raga & Antonio Lázaro & Andrés Barrado & Alberto Martín-Lozano & Isabel Quesada, 2019. "Step-by-Step Small-Signal Modeling and Control of a Light Hybrid Electric Vehicle Propulsion System," Energies, MDPI, vol. 12(21), pages 1-20, October.
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    5. Song, Ke & Wang, Xiaodi & Li, Feiqiang & Sorrentino, Marco & Zheng, Bailin, 2020. "Pontryagin’s minimum principle-based real-time energy management strategy for fuel cell hybrid electric vehicle considering both fuel economy and power source durability," Energy, Elsevier, vol. 205(C).
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    8. Sulaiman, N. & Hannan, M.A. & Mohamed, A. & Ker, P.J. & Majlan, E.H. & Wan Daud, W.R., 2018. "Optimization of energy management system for fuel-cell hybrid electric vehicles: Issues and recommendations," Applied Energy, Elsevier, vol. 228(C), pages 2061-2079.
    9. Huang, Yanjun & Wang, Hong & Khajepour, Amir & Li, Bin & Ji, Jie & Zhao, Kegang & Hu, Chuan, 2018. "A review of power management strategies and component sizing methods for hybrid vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 132-144.
    10. Zhu, Jianyun & Chen, Li & Wang, Xuefeng & Yu, Long, 2020. "Bi-level optimal sizing and energy management of hybrid electric propulsion systems," Applied Energy, Elsevier, vol. 260(C).
    11. Carmen Raga & Andres Barrado & Antonio Lazaro & Alberto Martin-Lozano & Isabel Quesada & Pablo Zumel, 2018. "Influence of the Main Design Factors on the Optimal Fuel Cell-Based Powertrain Sizing," Energies, MDPI, vol. 11(11), pages 1-22, November.
    12. Mojgan Fayyazi & Paramjotsingh Sardar & Sumit Infent Thomas & Roonak Daghigh & Ali Jamali & Thomas Esch & Hans Kemper & Reza Langari & Hamid Khayyam, 2023. "Artificial Intelligence/Machine Learning in Energy Management Systems, Control, and Optimization of Hydrogen Fuel Cell Vehicles," Sustainability, MDPI, vol. 15(6), pages 1-38, March.
    13. Carmen Raga & Andres Barrado & Henry Miniguano & Antonio Lazaro & Isabel Quesada & Alberto Martin-Lozano, 2018. "Analysis and Sizing of Power Distribution Architectures Applied to Fuel Cell Based Vehicles," Energies, MDPI, vol. 11(10), pages 1-30, September.
    14. Abdeldjalil Djouahi & Belkhir Negrou & Boubakeur Rouabah & Abdelbasset Mahboub & Mohamed Mahmoud Samy, 2023. "Optimal Sizing of Battery and Super-Capacitor Based on the MOPSO Technique via a New FC-HEV Application," Energies, MDPI, vol. 16(9), pages 1-18, May.
    15. José Luis Sampietro & Vicenç Puig & Ramon Costa-Castelló, 2019. "Optimal Sizing of Storage Elements for a Vehicle Based on Fuel Cells, Supercapacitors, and Batteries," Energies, MDPI, vol. 12(5), pages 1-27, March.
    16. Daeil Hyun & Jaeyoung Han & Seokmoo Hong, 2023. "Power Management Strategy of Hybrid Fuel Cell Drones for Flight Performance Improvement Based on Various Algorithms," Energies, MDPI, vol. 16(24), pages 1-20, December.
    17. 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).
    18. 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).
    19. Yang Gao & Changhong Liu & Yuan Liang & Sadegh Kouhestani Hamed & Fuwei Wang & Bo Bi, 2022. "Minimizing Energy Consumption and Powertrain Cost of Fuel Cell Hybrid Vehicles with Consideration of Different Driving Cycles and SOC Ranges," Energies, MDPI, vol. 15(17), pages 1-12, August.
    20. Chen, Kui & Laghrouche, Salah & Djerdir, Abdesslem, 2019. "Degradation model of proton exchange membrane fuel cell based on a novel hybrid method," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    21. Haris, Muhammad & Hasan, Muhammad Noman & Qin, Shiyin, 2021. "Early and robust remaining useful life prediction of supercapacitors using BOHB optimized Deep Belief Network," Applied Energy, Elsevier, vol. 286(C).
    22. Alessandro Serpi & Mario Porru, 2019. "Modelling and Design of Real-Time Energy Management Systems for Fuel Cell/Battery Electric Vehicles," Energies, MDPI, vol. 12(22), pages 1-21, November.
    23. Li, Guidan & Yang, Zhe & Li, Bin & Bi, Huakun, 2019. "Power allocation smoothing strategy for hybrid energy storage system based on Markov decision process," Applied Energy, Elsevier, vol. 241(C), pages 152-163.
    24. Kurnia, Jundika C. & Sasmito, Agus P. & Shamim, Tariq, 2017. "Performance evaluation of a PEM fuel cell stack with variable inlet flows under simulated driving cycle conditions," Applied Energy, Elsevier, vol. 206(C), pages 751-764.
    25. 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).

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