skip to main content

View PDF Download fulltext

Model free control of hybrid fuel-cell and supercapacitor powered electric vehicle

1Department of Electrical Engineering at Indian Institute of Technology (Indian School of Mines), Dhanbad, Jharkhand, 826004, India

2Intelligent Control and Smart Energy Research Lab, School of Engineering, University of Warwick, Coventry CV4 7AL, United Kingdom

3Department of Electrical Engineering, Jubail Industrial College, Jubail Industrial City, Saudi Arabia

4 Department of Electrical Engineering, National Institute of Technology, Jamshedpur, Jharkhand, 831014, India

5 Department of Electrical Engineering at Indian Institute of Technology (Banaras Hindu University), Varanasi, Uttar Pradesh, 221005, India

View all affiliations
Received: 2 Feb 2025; Revised: 15 Aug 2025; Accepted: 28 Oct 2025; Available online: 30 Dec 2025; Published: 1 Jan 2026.
Editor(s): H Hadiyanto
Open Access Copyright (c) 2026 The Author(s). Published by Centre of Biomass and Renewable Energy (CBIORE)
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Citation Format:
Abstract

This paper proposes a novel model-free control (MFC) strategy for hybrid electric vehicles (EVs) powered by a proton exchange membrane fuel cell (PEMFC) and a supercapacitor (SC). Unlike conventional model-based approaches that depend on accurate system identification and parameter tuning, the proposed framework employs ultra-local models to adapt dynamically to system variations without explicit modeling. The hybrid architecture is implemented using an interleaved boost converter for the PEMFC and a bidirectional buck–boost converter for the SC, coordinated to supply propulsion power and enable regenerative braking. Comprehensive MATLAB/Simulink simulations demonstrate that the proposed MFC achieves <3% current tracking error for both PEMFC and SC, ~750 ms settling time for PMSM speed variations, and <120 ms response for power transitions, while the DC bus voltage remains tightly regulated under dynamic load disturbances. Hardware-in-the-loop (HIL) validation on an OPAL-RT 5600 platform further confirms the method’s feasibility, showing a 20% reduction in execution time and enhanced robustness against parameter uncertainties compared to classical PI control. Experimental results also verify stable current sharing in interleaved converters, accurate voltage regulation in the SC branch, and smooth torque generation in the PMSM drive. Overall, the proposed control strategy provides a computationally efficient, fault-tolerant, and plug-and-play solution for next-generation EVs by reducing calibration effort and ensuring reliable operation under nonlinear and uncertain conditions, while demonstrating clear potential for real-time automotive applications.

Keywords: Fuel-cell; Hybrid electric vehicle; Energy storage; Power electronic control; Permanent magnet synchronous motor (PMSM) and Supercapacitor

Article Metrics:

  1. Aliane, A., Saadi, R., & Saadi, S. (2016). Model-free control for a PMSM drive, International Journal of Electrical Power & Energy Systems, 77, 416–423
  2. https://doi.org/10.1016/j.ijepes.2015.11.008
  3. Benayed, A. B., & Bentouba, S. (2021). Movement of a solar electric vehicle controlled by ANN-based DTC in hot climate regions. International Journal of Renewable Energy Development, 10(1), 61–70. https://doi.org/10.14710/ijred.2021.18596
  4. Benbouzid, M. E. H. (2000). A review of permanent magnet synchronous motors and drives. IEEE Transactions on Industrial Electronics, 49(6), 1125–1135. https://doi.org/10.1109/41.897790
  5. Bose, B. K. (2002). Modern Power Electronics and AC Drives. Prentice Hall
  6. Ceraolo, M. (2004). Battery Models for Hybrid and Electric Vehicle Simulation. Vehicle Power and Propulsion Conference, IEEE. 504–509. https://doi.org/10.1109/VPPC.2004.1429243
  7. Chanda, R. C., Vafaei-Zadeh, A., Hanifah, H., Ashrafi, D. M., & Ahmed, T. (2024). Achieving a sustainable future by analyzing electric vehicle adoption in developing nations through an extended technology acceptance model. Sustainable Futures, 8, 100386. https://doi.org/10.1016/j.sftr.2024.100386
  8. Chau, K. T., Gao, Y., & Chan, C. C. (2011). Overview of Power Electronics for Electric Vehicles, IEEE Transactions on Industrial Electronics, 59(11), 4457–4468. https://doi.org/10.1109/TIE.2011.2163722
  9. El-Sousy, F. F. M. (2013). Intelligent optimal recurrent wavelet Elman neural network control system for permanent-magnet synchronous motor servo drive. IEEE Transactions on Industrial Informatics, 9(4), 1986–2003
  10. Emadi, A., Lee, Y. J., & Rajashekara, K. (2008). Power electronics and motor drives in electric, hybrid electric, and plug-in hybrid electric vehicles. IEEE Transactions on Industrial Electronics, 55(6), 2237–2245. https://doi.org/10.1109/TIE.2008.2008460
  11. Fliess, M., & Join, C. (2013). Model-free control. International Journal of Control, 86, 2228–2252. https://doi.org/10.1080/00207179.2013.810345
  12. Huang, G., Zhang, Y., Huang, Y. and Li, H., (2022) Model-Free Sliding Mode Control for PMSM Drive System Based on Ultra-Local Model, Energy Engineering, 119(2), 649–669, https://doi.org/10.32604/ee.2022.018898
  13. Gao, D. W., Dougal, R. A., & Liu, S. (2005). Power enhancement of an actively controlled battery/ultracapacitor hybrid. IEEE Transactions on Power Electronics, 20(1), 236–243. https://doi.org/10.1109/TPEL.2004.839785
  14. Gao, S., Wei, Y., Zhang, D., Qi, H., Wei, Y., & Yang, Z. (2022). Model-free hybrid parallel predictive speed control based on ultralocal model of PMSM for electric vehicles. IEEE Transactions on Industrial Electronics, 69(10), 9739–9748. https://doi.org/10.1109/TIE.2021.3110832
  15. Ge, Y. (2024). Adaptive control of plug-in hybrid electric vehicles based on energy management strategy and dynamic programming algorithm. International Journal of Renewable Energy Development, 13(6), 1104–1114. https://doi.org/10.14710/ijred.2024.60463
  16. Herchi, H., Khlaief, A., & Mimouni, M. F. (2020). Real-time implementation of model-free control for energy management in hybrid electric vehicles. Journal of Power Sources, 448, 227374. https://doi.org/10.1016/j.jpowsour.2019.227374
  17. Hicham, C., Nasri, A., & Kayisli, K. (2021). A novel method of electric scooter torque estimation using the space vector modulation control. International Journal of Renewable Energy Development, 10(2). https://doi.org/10.14710/ijred.2021.33403
  18. Join, C., & Fliess, M. (2017). Model-free control and intelligent PID controllers: Towards a possible trivialization of nonlinear control? IFAC-PapersOnLine, 50(1), 14264–14271. https://doi.org/10.1016/j.ifacol.2017.08.2386
  19. Kang, Y., Zhang, L., Yang, H., & Cheng, D. (2019). Energy management strategy for fuel cell/supercapacitor hybrid vehicle based on fuzzy logic and extremum seeking control. Energy Conversion and Management, 195, 957–967. https://doi.org/10.1016/j.enconman.2019.05.076
  20. Khaligh, A., & Li, Z. (2010). Battery, ultracapacitor, fuel cell, and hybrid energy storage systems for electric, hybrid electric, fuel cell, and plug-in hybrid electric vehicles: State of the art. IEEE Transactions on Vehicular Technology, 59(6), 2806–2814. https://doi.org/10.1109/TVT.2010.2053650
  21. Khan, M. J., & Iqbal, M. T. (2015). Modulation strategies for improved performance of boost converters in fuel cell systems. IEEE Transactions on Power Electronics, 30(11), 6407–6415. https://doi.org/10.1109/TPEL.2014.2387857
  22. Khan, M. W., Wang, J., Xiong, L., & Ma, M. (2019). Fractional order sliding mode control of PMSG-wind turbine exploiting clean energy resource. International Journal of Renewable Energy Development, 8(1). https://doi.org/10.14710/ijred.8.1.81-89
  23. Kim, S. K., Lee, J. S., & Lee, K. B. (2017). Self-tuning adaptive speed controller for permanent magnet synchronous motor. IEEE Transactions on Power Electronics, 32(2), 1493–1506. https://doi.org/10.1109/TPEL.2016.2549021
  24. Kommula, B. N., & Kota, V. R. (2019). A novel single input double output (SIDO) converter for torque ripple minimization in solar-powered BLDC motor. International Journal of Renewable Energy Development, 8(2), 161. https://doi.org/10.14710/ijred.8.2.161-168
  25. Li, J., & Chen, X. (2019). Adaptive model-free control for nonlinear electric vehicle drivetrains. IEEE Transactions on Industrial Informatics, 15(7), 3933–3941. https://doi.org/10.1109/TII.2018.2874727
  26. Li, Q., Yang, W., Yin, Y., & Chen, W. (2020). Real-time implementation of maximum net power strategy based on sliding mode variable structure control for proton-exchange membrane fuel cell system. IEEE Transactions on Transportation Electrification, 6(1), 288–297. https://doi.org/10.1109/TTE.2020.2970835
  27. Li, S., Zhang, Y., & Cao, D. (2017). Adaptive fuzzy model predictive control for energy management in hybrid electric vehicles. IEEE Transactions on Vehicular Technology, 66(9), 7717–7728. https://doi.org/10.1109/TVT.2017.2690927
  28. Li, X., Song, X., & Yang, J. (2018). Robust control of fuel cell/supercapacitor hybrid power system based on model-free control strategy. Energy Conversion and Management, 157, 35–47. https://doi.org/10.1016/j.enconman.2017.11.007
  29. Liu, B., Zhou, B., & Ni, T. (2018). Principle and stability analysis of an improved self-sensing control strategy for surface-mounted PMSM drives using second-order generalized integrators. IEEE Transactions on Energy Conversion, 33(1), 126–136. https://doi.org/10.1109/TEC.2017.2737000
  30. Liu, Y., Qu, W., Liu, S., & Han, J. (2020). A model-free adaptive control approach for permanent magnet synchronous motors using ultra-local models, ISA Transactions, 100, 251–260
  31. https://doi.org/10.1016/j.isatra.2019.12.020
  32. Moreno, J., Ortuzar, M. E., & Dixon, J. W. (2006). Energy-management system for a hybrid electric vehicle, using ultracapacitors and neural networks. IEEE Transactions on Industrial Electronics, 53(2), 614–623. https://doi.org/10.1109/TIE.2006.871219
  33. Moseley, P. T., & Garche, J. (2009). Electrochemical Energy Storage for Renewable Sources and Grid Balancing. Elsevier
  34. Mungporn, P., Yodwong, B., Thounthong, P., Nahid-Mobarakeh, B., Takorabet, N., Guilbert, D., Kumam, P., Bizon, N., & Kaewprapha, C. (2019). Model-free control of multiphase interleaved boost converter for fuel cell/reformer power generation. In Proceedings of IEEE Research, Invention, and Innovation Congress (RI2C) (pp. 1–6). https://doi.org/10.1109/RI2C48728.2019.8999872
  35. Mustafa, G. I. Y., Wang, H. P., & Tian, Y. (2019). Model-free adaptive fuzzy logic control for a half-car active suspension system. Studies in Informatics and Control, 28(1), 13–24. https://doi.org/10.24846/v28i1y201902
  36. Onori, S., Serrao, L., & Rizzoni, G. (2016). Hybrid Electric Vehicles: Energy Management Strategies. Springer
  37. Paganelli, G., Ercole, A. L., & Del Pizzo, A. (2002). General supervisory control policy for the energy optimization of charge-sustaining hybrid electric vehicles. Journal of Dynamic Systems, Measurement, and Control, 124(3), 506–514
  38. Peng, J., Wang, Y., & Ma, S. (2021). A robust adaptive sliding-mode controller for PMSM drives with parameter uncertainties. IEEE Transactions on Industrial Electronics, 68(7), 5847–5856. https://doi.org/10.1109/TIE.2020.2992844
  39. Quang, N., & Dittrich, J.-A. (2001). Vector Control of Three-Phase AC Machines: System Development in the Practice. Springer
  40. Renaudineau, H., Houari, A., & Shahin, A. (2014). Efficiency optimization through current-sharing for paralleled DC–DC boost converters with parameter estimation. IEEE Transactions on Power Electronics, 29(2), 759–767. https://doi.org/10.1109/TPEL.2013.2254093
  41. Romli, M. I., Rajkumar, R. K., Wan, W. Y., Wai, C. L., Arelhi, R., & Isa, D. (2016). The effectiveness of new solar photovoltaic system with supercapacitor for rural areas. International Journal of Renewable Energy Development, 5(3), 249. https://doi.org/10.14710/ijred.5.3.249-256
  42. Saad, M. (2021). Hardware-in-the-loop simulation of PEM fuel cell and ultracapacitor hybrid energy system. Energy Reports, 7, 4214–4226
  43. Sciarretta, A., & Guzzella, L. (2007). Control of hybrid electric vehicles. IEEE Control Systems Magazine, 27(2), 60–70. https://doi.org/10.1109/MCS.2007.338280
  44. Shetty, D., & Sabhahit, J. N. (2024). Grey wolf optimization and incremental conductance-based hybrid MPPT technique for solar-powered induction motor driven water pump. International Journal of Renewable Energy Development, 13(1), 52–61. https://doi.org/10.14710/ijred.2024.50715
  45. Soricellis, M. D., Rù, D. D., & Bolognani, S. (2018). A robust current control based on proportional-integral observers for permanent magnet synchronous machines. IEEE Transactions on Industry Applications, 54(2), 1437–1447. https://doi.org/10.1109/TIA.2017.2783345
  46. Srinivas, V. L., & Wu, J. (2022). Topology and parameter identification of distribution network using smart meter and µPMU measurements. IEEE Transactions on Instrumentation and Measurement, 71, 1–14. https://doi.org/10.1109/TIM.2022.3150711
  47. Srinivas, V. L., Singh, B., & Mishra, S. (2020). Seamless mode transition technique for virtual synchronous generators and method thereof. IEEE Transactions on Industrial Informatics, 16(8), 5254–5266. https://doi.org/10.1109/TII.2019.2958759
  48. Sriprang, S., Mekhilef, S., Rahim, N. A., & Van, H. A. (2019). Design and implementation of robust decoupling control for permanent magnet synchronous generator in wind power applications. IEEE Transactions on Industry Applications, 55(1), 655–664
  49. https://doi.org/10.1109/TIA.2018.2869613
  50. Sriprang, S., Nahid-Mobarakeh, B., Takorabet, N., Thounthong, P., Pierfederici, S., Kumam, P., Bizon, N., & Mungporn, P. (2019). Modeling of flatness-based control with disturbance observer-based parameter estimation for PMSM drive. WSEAS Transactions on Electronics, 10(3), 19–27
  51. Sulaiman, S. A., Othman, M. F., & Karim, M. R. (2015). “Dynamic Modeling and Control of PEM Fuel Cell System for Vehicle Applications,” International Journal of Hydrogen Energy, vol. 40, no. 14, pp. 4853–4864. https://doi.org/10.1016/j.ijhydene.2015.02.048
  52. Sun, X., & Zhu, W. (2020). Real-time hardware-in-the-loop simulation and control of hybrid electric vehicles. IEEE Access, 8, 117870–117880. https://doi.org/10.1109/ACCESS.2020.3004111
  53. Tayebi, A., Leclerc, C., & Rakotondrabe, M. (2019). Model-free control of uncertain MIMO nonlinear systems: Application to electric motor drives. International Journal of Control, 92(12), 2846–2858. https://doi.org/10.1080/00207179.2018.1535080
  54. Teng, C., Ji, Z., Yan, P., Wang, Z., & Ye, X. (2024). Orderly charging strategy for electric vehicles based on multi-level adjustability. International Journal of Renewable Energy Development, 13(2), 245–255. https://doi.org/10.14710/ijred.2024.51179
  55. Thounthong, P., & Pierfederici, S. (2010). A new control law based on the differential flatness principle for multiphase interleaved DC-DC converter. IEEE Transactions on Circuits and Systems II: Express Briefs, 57(11), 903–907. https://doi.org/10.1109/TCSII.2010.2076330
  56. Toliyat, H. A., & Rahman, K. M. (2003). Recent advances in power electronics and drives for EV/HEV applications. IEEE Power Engineering Society General Meeting, 2003, 1–6. https://doi.org/10.1109/PES.2003.1267310
  57. Vu, N. T. T., Yu, D. Y., Choi, H. H., & Jung, J. W. (2013). T–S fuzzy-model-based sliding-mode control for surface-mounted permanent-magnet synchronous motors considering uncertainties. IEEE Transactions on Industrial Electronics, 60(10), 4281–4291. https://doi.org/10.1109/TIE.2012.2226413
  58. Wada, T., & Shibata, T. (2019). Model-free adaptive control for automotive systems. Control Engineering Practice, 86, 10–22. https://doi.org/10.1016/j.conengprac.2019.01.012
  59. Wu, B., Toliyat, H. A., & Rahman, K. M. (2003). Modeling and control of electric machines for hybrid electric vehicles. IEEE Transactions on Industrial Electronics, 51(3), 635–642. https://doi.org/10.1109/TIE.2003.811438
  60. Yang, M., Lang, X., Long, J., & Xu, D. (2017). Flux immunity robust predictive current control with incremental model and extended state observer for PMSM drive. IEEE Transactions on Power Electronics, 32(12), 9267–9279. https://doi.org/10.1109/TPEL.2017.2661819
  61. Zhang, H., & Li, Y. (2022). Fault-tolerant control in electric vehicles: A review and future perspectives. IEEE Transactions on Transportation Electrification, 8(2), 1236–1250. https://doi.org/10.1109/TTE.2022.3155271
  62. Zhao, H., Chen, W., & Wang, L. (2011). Robust Control of Fuel Cell Power Systems Using Adaptive Techniques, IEEE Transactions on Control Systems Technology, 19(5), 1073–1080. https://doi.org/10.1109/TCST.2010.2081569
  63. Zhao, Y., Wang, Y., & Gao, Z. (2018). Active disturbance rejection control for PMSM drives with disturbance estimation and compensation, IEEE Transactions on Industrial Electronics, 65(3), 2602–2611
  64. https://doi.org/10.1109/TIE.2017.2748058
  65. Zhu, Z. Q., & Howe, D. (2007). Electrical machines and drives for electric, hybrid, and fuel cell vehicles. Proceedings of the IEEE, 95(4), 746–765. https://doi.org/10.1109/JPROC.2007.892490

Last update:

No citation recorded.

Last update: 2026-01-12 15:21:30

No citation recorded.