Advances in Energy Research

Techno-Press (테크노프레스)
권호 표지
DOI QR코드

DOI QR Code

A new controller for energy management system of EV

  • Shujaat Husain (Department of Electrical Engineering, Jamia Millia Islamia) ;
  • Haroon Ashfaq (Department of Electrical Engineering, Jamia Millia Islamia) ;
  • Mohammad Asjad (Department of Mechanical Engineering, Jamia Millia Islamia)
  • Received : 2022.07.15
  • Accepted : 2022.09.09
  • Published : 2022.09.25
⟨ Previous Next ⟩

Abstract

Recent concerns about rising fuel prices and greenhouse gas emissions have focused attention on alternative energy sources, particularly in the transport sector. Transportation consumes 40% of overall fuel usage. As a result, a growing majority of researches on Electric Vehicles (EVs) and their Energy Management Systems (EMS) have been done. In order to enhance the performance and to meet the needs of drivers, more information regarding the EMS is needed. A new Energy Management System is proposed using a FOPID controller. To put the concept into practice, state equations are utilised. The fifth-order state-space model under study is a linked model with several inputs and outputs and the transfer matrices are calculated for decoupling the system. Utilizing these transfer matrices to decouple the system and FOPID controller is used to tune the system. The tuned parameters are minimized using a Particle Swarm Optimization (PSO) approach with Integral Time Absolute Error (ITAE) as the goal. When the suggested FOPID system's results are compared to those of PID-controlled systems, a sizable improvement is observed, which is explained by the results.

Keywords

References

  1. Carter, R., Cruden, A. and Hall, P.J. (2012), "Optimizing for efficiency or battery life in a battery/supercapacitor electric vehicle", IEEE T. Vehicular Technol., 61(4), 1526-1533. https://doi.org/10.1109/TVT.2012.2188551.
  2. George, M.A., Bhavani, I.D. and Kamath, D.V. (2020), "EX-CCII based FOPID controller for electric vehicle speed control", Proceedings of the 2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER). https://doi.org/10.1109/DISCOVER50404.2020.9278055.
  3. George, M.A., Kamat, D.V. and Kurian, C.P. (2021), "Electronically tunable ACO based fuzzy FOPID controller for effective speed control of electric vehicle", IEEE Access, 9, 73392-73412. https://doi.org/10.1109/ACCESS.2021.3080086.
  4. Hossain Lipu, M.S., Miah, M.S., Ansari, S., Meraj, S.T., Hasan, K., Elavarasan, R.M. and Hussain, A. (2022), "Power electronics converter technology integrated energy storage management in electric vehicles: Emerging trends, analytical assessment and future research opportunities", Electronics, 11(4), 562. https://doi.org/10.3390/electronics11040562.
  5. Husain, S. and Shrivastava, N.A. (2020), "A comparative analysis of multi-objective optimization algorithms for stand-alone hybrid renewable energy system", Proceedings of the 2020 2nd International Conference on Innovative Mechanisms for Industry Applications (ICIMIA), Bangalore, India. https://doi.org/10.1109/ICIMIA48430.2020.9074903.
  6. Husain, S. and Shrivastava, N.A. (2020), "Stand-alone hybrid renewable energy system: Optimization and sensitivity analysis", Proceedings of the 2020 International Conference on Electrical and Electronics Engineering (ICE3). https://doi.org/10.1109/ICE348803.2020.9122956.
  7. Javed, K., Ashfaq, H. and Singh, R. (2019), "Analysis and sizing of Hybrid Energy Storage System (Hess) topologies for solar photovoltaic applications", Int. J. Power Energ. Syst., 39(3).
  8. Javed, K., Ashfaq, H., Singh, R., Hussain, S.S. and Ustun, T.S. (2019), "Design and performance analysis of a stand-alone PV system with hybrid energy storage for rural India", Electronics, 8(9), 952. https://doi.org/10.3390/electronics8090952.
  9. Jiang, H., Xu, L., Li, J., Hu, Z. and Ouyang, M. (2019), "Energy management and component sizing for a fuel cell/battery/supercapacitor hybrid powertrain based on two-dimensional optimization algorithms", Energy, 177, 386-396. https://doi.org/10.1016/j.energy.2019.04.110.
  10. Karki, A., Phuyal, S., Tuladhar, D., Basnet, S. and Shrestha, B.P. (2020), "Status of pure electric vehicle power train technology and future prospects", Appl. Syst. Innovation, 3(3), 35. https://doi.org/10.3390/asi3030035.
  11. Li, H., Zhao, D., Zhang, Y., Liang, Z., Dang, H. and Liu, Y. (2020), "An improved state machine strategy for fuel-cell-based hybrid electric vehicles", Proceedings of the IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society. https://doi.org/10.1109/IECON43393.2020.9254705.
  12. Lopez, L.F.D.M., Garcia, F.S., Naranjo Hernandez, J.E. and Blas, N.G. (2021), "Speed proportional integrative derivative controller: Optimization functions in metaheuristic algorithms", J. Adv. Transport., https://doi.org/10.1155/2021/5538296.
  13. Lu, Z. and Zhang, X. (2022), "Composite non-linear control of hybrid energy-storage system in electric vehicle", Energies, 15(4), 1567. https://doi.org/10.3390/en15041567.
  14. Mora, L., Lugo, R., Moreno, C. and Amaya, J.E. (2016), "Parameters optimization of PID controllers using metaheuristics with physical implementation", Proceedings of the 2016 35th International Conference of the Chilean Computer Science Society (SCCC). https://doi.org/10.1109/SCCC.2016.7836043.
  15. Ryalat, M. and Laila, D. S. (2018), "A robust IDA-PBC approach for handling uncertainties in underactuated mechanical systems", IEEE T. Autom. Control, 63(10), 3495-3502. https://doi.org/10.1109/TAC.2018.2797191.
  16. Saib, S., Hamouda, Z. and Marouani, K. (2017), "Energy management in a fuel cell hybrid electric vehicle using a fuzzy logic approach", Proceedings of the 2017 5th International Conference on Electrical Engineering-Boumerdes (ICEE-B). https://doi.org/10.1109/ICEE-B.2017.8192197.
  17. Verma, M. and Srivastava, S. (2021), "A review on Effectiveness of Real time optimization techniques in power management system in hybrid electric vehicle", Int. J. New Technol. Res., 7(4), https://doi.org/10.31871/ijntr.7.4.13.
  18. Xu, L., Ouyang, M., Li, J., Yang, F., Lu, L. and Hua, J. (2013), "Application of Pontryagin's Minimal Principle to the energy management strategy of plugin fuel cell electric vehicles", Int. J. Hydrogen Energ., 38(24), 10104-10115. https://doi.org/10.1016/j.ijhydene.2013.05.125.
  19. Yang, B., Zhu, T., Zhang, X., Wang, J., Shu, H., Li, S. and Yu, T. (2020), 'Design and implementation of Battery/SMES hybrid energy storage systems used in electric vehicles: A nonlinear robust fractional-order control approach", Energy, 191, 116510. https://doi.org/10.1016/j.energy.2019.116510.
  20. Zhang, X., Lu, Z., Yuan, X., Wang, Y. and Shen, X. (2020), "L2-gain adaptive robust control for hybrid energy storage system in electric vehicles", IEEE T. Power Electr., 36(6), 7319-7332. https://doi.org/10.1109/TPEL.2020.3041653.
  21. Zhou, X., Sun, F., Zhang, C. and Sun, C. (2021), "Stochastic predictive co-optimization of the speed planning and powertrain controls for electric vehicles driving in random traffic environment", POWER-D-21-05695.