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access icon free Online energy management of a hybrid fuel cell vehicle considering the performance variation of the power sources

  • Author(s): Razieh Ghaderi 1 ; Mohsen Kandidayeni 2, 3 ; Mehdi Soleymani 1, 4 ; Loïc Boulon 3 ; Hicham Chaoui 5
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  • Source: Volume 10, Issue 4, December 2020, p. 360 – 368
    DOI:  10.1049/iet-est.2020.0035 , Print ISSN 2042-9738, Online ISSN 2042-9746
© The Institution of Engineering and Technology
Received 26/03/2020, Accepted 02/10/2020, Revised 22/09/2020, Published 07/10/2020

This study investigates the impact of battery and fuel cell (FC) degradation on energy management of a FC hybrid electric vehicle. In this respect, an online energy management strategy (EMS) is proposed considering simultaneous online adaptation of battery and FC models. The EMS is based on quadratic programming which is integrated into an online battery and proton exchange membrane FC (PEMFC) parameters identification. Considering the battery and PEMFC states of health, three scenarios have been considered for the EMS purpose, and the performance of the proposed EMS has been examined under two driving cycles. Numerous test scenarios using standard driving cycles reveal that the ageing of battery and PEMFC has a considerable impact on the hydrogen consumption. Moreover, the proposed EMS can successfully tackle the model uncertainties owing to the performance drifts of the power sources at the mentioned scenarios.

Inspec keywords: fuel cell vehicles; proton exchange membrane fuel cells; hybrid electric vehicles; energy management systems; quadratic programming

Other keywords: FC hybrid electric vehicle; performance variation; numerous test scenarios; hybrid fuel cell vehicle; EMS purpose; online energy management strategy; FC models; quadratic programming; considerable impact; online battery; performance drifts; power sources; PEMFC; standard driving cycles

Subjects: Fuel cells; Transportation; Fuel cells

References

    1. 1)
      • 10. Huang, Y., Wang, H., Khajepour, A., et al: ‘A review of power management strategies and component sizing methods for hybrid vehicles’, Renew. Sust. Energy Rev., 2018, 96, pp. 132–144.
    2. 2)
      • 51. Carignano, M., Roda, V., Costa-Castelló, R., et al: ‘Assessment of energy management in a fuel cell/battery hybrid vehicle’, IEEE access, 2019, 7, pp. 16110–16122.
    3. 3)
      • 22. Kamal, E., Adouane, L.: ‘Intelligent energy management strategy based on artificial neural fuzzy for hybrid vehicle’, IEEE Trans. Intell. Veh., 2017, 3, (1), pp. 112–125.
    4. 4)
      • 26. Chen, J., Xu, C., Wu, C., et al: ‘Adaptive fuzzy logic control of fuel-cell-battery hybrid systems for electric vehicles’, IEEE Trans. Ind. Inf., 2016, 14, (1), pp. 292–300.
    5. 5)
      • 42. Squadrito, G., Maggio, G., Passalacqua, E., et al: ‘An empirical equation for polymer electrolyte fuel cell (pefc) behaviour’, J. Appl. Electrochem., 1999, 29, (12), pp. 1449–1455.
    6. 6)
      • 2. Zoundi, Z.: ‘Co2 emissions, renewable energy and the environmental kuznets curve, a panel cointegration approach’, Renew. Sust. Energy Rev., 2017, 72, pp. 1067–1075.
    7. 7)
      • 46. Zhao, X., Li, Y., Liu, Z., et al: ‘Thermal management system modeling of a water-cooled’, Int. J. Hydrog. Energy, 2015, 40, (7), pp. 3048–3056.
    8. 8)
      • 1. Karamanev, D., Pupkevich, V., Penev, K., et al: ‘Biological conversion of hydrogen to electricity for energy storage’, Energy, 2017, 129, pp. 237–245.
    9. 9)
      • 18. Li, Q., Huang, W., Chen, W., et al: ‘Regenerative braking energy recovery strategy based on pontryagin's minimum principle for fell cell/supercapacitor hybrid locomotive’, Int. J. Hydrog. Energy, 2019, 44, (11), pp. 5454–5461.
    10. 10)
      • 29. Wang, Y., Moura, S.J., Advani, S.G., et al: ‘Optimization of powerplant component size on board a fuel cell/battery hybrid bus for fuel economy and system durability’, Int. J. Hydrog. Energy, 2019, 44, (33), pp. 18283–18292.
    11. 11)
      • 43. Ettihir, K., Boulon, L., Becherif, M., et al: ‘Online identification of semi-empirical model parameters for pemfcs’, Int. J. Hydrog. Energy, 2014, 39, (36), pp. 21165–21176.
    12. 12)
      • 4. Samuelsen, S.: ‘The automotive future belongs to fuel cells range, adaptability, and refueling time will ultimately put hydrogen fuel cells ahead of batteries’, IEEE Spectr., 2017, 54, (2), pp. 38–43.
    13. 13)
      • 30. Wang, Y., Moura, S.J., Advani, S.G., et al: ‘Power management system for a fuel cell/battery hybrid vehicle incorporating fuel cell and battery degradation’, Int. J. Hydrog. Energy, 2019, 44, (16), pp. 8479–8492.
    14. 14)
      • 40. Huria, T., Ceraolo, M., Gazzarri, J., et al: ‘Simplified extended kalman filter observer for soc estimation of commercial power-oriented lfp lithium battery cells’, 2013. Available at https://doiorg/104271/2013-01-1544.
    15. 15)
      • 39. Yuan, J., Yang, L., Chen, Q.: ‘Intelligent energy management strategy based on hierarchical approximate global optimization for plug-in fuel cell hybrid electric vehicles’, Int. J. Hydrog. Energy, 2018, 43, (16), pp. 8063–8078.
    16. 16)
      • 6. Martinez, C.M., Hu, X., Cao, D., et al: ‘Energy management in plug-in hybrid electric vehicles: recent progress and a connected vehicles perspective’, IEEE Trans. Veh. Technol., 2016, 66, (6), pp. 4534–4549.
    17. 17)
      • 38. Xia, B., Lao, Z., Zhang, R., et al: ‘Online parameter identification and state of charge estimation of lithium-ion batteries based on forgetting factor recursive least squares and nonlinear kalman filter’, Energies, 2018, 11, (1), p. 3.
    18. 18)
      • 21. Zhang, W., Li, J., Xu, L., et al: ‘Optimization for a fuel cell/battery/capacity tram with equivalent consumption minimization strategy’, Energy Convers. Manage., 2017, 134, pp. 59–69.
    19. 19)
      • 25. Yan, Y., Li, Q., Chen, W., et al: ‘Optimal energy management and control in multimode equivalent energy consumption of fuel cell/supercapacitor of hybrid electric tram’, IEEE Trans. Ind. Electron., 2018, 66, (8), pp. 6065–6076.
    20. 20)
      • 24. Wang, Y., Sun, Z., Chen, Z.: ‘Energy management strategy for battery/supercapacitor/fuel cell hybrid source vehicles based on finite state machine’, Appl. Energy, 2019, 254, p. 113707.
    21. 21)
      • 20. Li, H., Ravey, A., N'Diaye, A., et al: ‘A novel equivalent consumption minimization strategy for hybrid electric vehicle powered by fuel cell, battery and supercapacitor’, J. Power Sources, 2018, 395, pp. 262–270.
    22. 22)
      • 9. Li, H., Ravey, A., N'Diaye, A., et al: ‘A review of energy management strategy for fuel cell hybrid electric vehicle’. 2017 IEEE Vehicle Power and Propulsion Conf. (VPPC), Belfort, France, 2017, pp. 1–6.
    23. 23)
      • 23. Kazemi, H., Fallah, Y.P., Nix, A., et al: ‘Predictive aecms by utilization of intelligent transportation systems for hybrid electric vehicle powertrain control’, IEEE Trans. Intell. Veh., 2017, 2, (2), pp. 75–84.
    24. 24)
      • 49. Chen, H., Pei, P., Song, M.: ‘Lifetime prediction and the economic lifetime of proton exchange membrane fuel cells’, Appl. Energy, 2015, 142, pp. 154–163.
    25. 25)
      • 44. Liso, V., Nielsen, M.P., Kaer, S.K., et al: ‘Thermal modeling and temperature control of a pem fuel cell system for forklift applications’, Int. J. Hydrog. Energy, 2014, 39, (16), pp. 8410–8420.
    26. 26)
      • 12. Zhou, W., Yang, L., Cai, Y., et al: ‘Dynamic programming for new energy vehicles based on their work modes part i: electric vehicles and hybrid electric vehicles’, J. Power Sources, 2018, 406, pp. 151–166.
    27. 27)
      • 33. Ettihir, K., Boulon, L., Agbossou, K.: ‘Optimization-based energy management strategy for a fuel cell/battery hybrid power system’, Appl. Energy, 2016, 163, pp. 142–153.
    28. 28)
      • 7. Ali, A.M., Söffker, D.: ‘Towards optimal power management of hybrid electric vehicles in real-time: A review on methods, challenges, and state-of-the-art solutions’, Energies, 2018, 11, (3), p. 476.
    29. 29)
      • 31. Zhou, D., Al-Durra, A., Matraji, I., et al: ‘Online energy management strategy of fuel cell hybrid electric vehicles: a fractional-order extremum seeking method’, IEEE Trans. Ind. Electron., 2018, 65, (8), pp. 6787–6799.
    30. 30)
      • 50. Chaoui, H., Gualous, H.: ‘Online parameter and state estimation of lithium-ion batteries under temperature effects’, Electr. Power Syst. Res., 2017, 145, pp. 73–82.
    31. 31)
      • 27. Li, Z., Khajepour, A., Song, J.: ‘A comprehensive review of the key technologies for pure electric vehicles’, Energy, 2019, 182, pp. 824–839.
    32. 32)
      • 14. Chen, Z., Wu, Y., Guo, N., et al: ‘Energy management for plug-in hybrid electric vehicles based on quadratic programming with optimized engine on-off sequence’. IECON 2017-43rd Annual Conf. of the IEEE Industrial Electronics Society, Beijing, People's Republic of China, 2017, pp. 7134–7139.
    33. 33)
      • 19. Xie, S., Hu, X., Xin, Z., et al: ‘Pontryagin's minimum principle based model predictive control of energy management for a plug-in hybrid electric bus’, Appl. Energy, 2019, 236, pp. 893–905.
    34. 34)
      • 41. Kandidayeni, M., Macias, A., Amamou, A., et al: ‘Overview and benchmark analysis of fuel cell parameters estimation for energy management purposes’, J. Power Sources, 2018, 380, pp. 92–104.
    35. 35)
      • 5. Schipper, F., Aurbach, D.: ‘A brief review: past, present and future of lithium ion batteries’, Russ. J. Electrochem., 2016, 52, (12), pp. 1095–1121.
    36. 36)
      • 13. Zhang, R., Tao, J.: ‘Ga-based fuzzy energy management system for fc/sc-powered hev considering h 2 consumption and load variation’, IEEE Trans. Fuzzy Syst., 2018, 26, (4), pp. 1833–1843.
    37. 37)
      • 32. Zhou, D., Ravey, A., Al-Durra, A., et al: ‘A comparative study of extremum seeking methods applied to online energy management strategy of fuel cell hybrid electric vehicles’, Energy Convers. Manage., 2017, 151, pp. 778–790.
    38. 38)
      • 34. Fernandez, A.O.M., Kandidayeni, M., Boulon, L., et al: ‘An adaptive state machine based energy management strategy for a multi-stack fuel cell hybrid electric vehicle’, IEEE Trans. Veh. Technol., 2019, 69, (1), pp. 220–234.
    39. 39)
      • 8. Sulaiman, N., Hannan, M., Mohamed, A., et al: ‘Optimization of energy management system for fuel-cell hybrid electric vehicles: issues and recommendations’, Appl. Energy, 2018, 228, pp. 2061–2079.
    40. 40)
      • 37. Kandidayeni, M., Macias, A., Boulon, L., et al: ‘Investigating the impact of ageing and thermal management of a fuel cell system on energy management strategies’, Appl. Energy, 2020, 274, p. 115293.
    41. 41)
      • 11. Zhou, W., Yang, L., Cai, Y., et al: ‘Dynamic programming for new energy vehicles based on their work modes part ii: fuel cell electric vehicles’, J. Power Sources, 2018, 407, pp. 92–104.
    42. 42)
      • 16. Koot, M., Kessels, J.T., De-Jager, B., et al: ‘Energy management strategies for vehicular electric power systems’, IEEE Trans. Veh. Technol., 2005, 54, (3), pp. 771–782.
    43. 43)
      • 48. Yue, M., Jemei, S., Zerhouni, N., et al: ‘Towards the energy management of a fuel cell/battery vehicle considering degradation’. 2017 IEEE Vehicle Power and Propulsion Conf. (VPPC), Belfort, France, 2017, pp. 1–6.
    44. 44)
      • 45. Oruganti, P.S., Ahmed, Q., Jung, D.: ‘Effects of thermal and auxiliary dynamics on a fuel cell based range extender’. SAE Technical Paper, 2018.
    45. 45)
      • 28. Li, H., Ravey, A., N'Diaye, A., et al: ‘Online adaptive equivalent consumption minimization strategy for fuel cell hybrid electric vehicle considering power sources degradation’, Energy Convers. Manage., 2019, 192, pp. 133–149.
    46. 46)
      • 35. Kandidayeni, M., Fernandez, A.O.M., Khalatbarisoltani, A., et al: ‘An online energy management strategy for a fuel cell/battery vehicle considering the driving pattern and performance drift impacts’, IEEE Trans. Veh. Technol., 2019, 68, (12), pp. 11427–11438.
    47. 47)
      • 3. Ehsani, M., Gao, Y., Longo, S., et al: ‘Modern electric, hybrid electric, and fuel cell vehicles’ (CRC Press, USA, 2018).
    48. 48)
      • 36. Ghaderi, R., Kandidayeni, M., Soleymani, M., et al: ‘Investigation of the battery degradation impact on the energy management of a fuel cell hybrid electric vehicle’. 2019 IEEE Vehicle Power and Propulsion Conf. (VPPC), Hanoi, Vietnam, 2019, pp. 1–6.
    49. 49)
      • 15. Chen, Z., Mi, C.C., Xiong, R., et al: ‘Energy management of a power-split plug-in hybrid electric vehicle based on genetic algorithm and quadratic programming’, J. Power Sources, 2014, 248, pp. 416–426.
    50. 50)
      • 17. Liu, Y., Li, J., Chen, Z., et al: ‘Research on a multi-objective hierarchical prediction energy management strategy for range extended fuel cell vehicles’, J. Power Sources, 2019, 429, pp. 55–66.
    51. 51)
      • 47. Ballard: ‘FCvelocity-9SSL V4.3’, 2017.
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