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Interval type 2 fuzzy PI-enhanced state space model for battery management in battery electric utility vehicles operating in an indoor logistics environment

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Języki publikacji
EN
Abstrakty
EN
This research presents an advanced control approach for battery management in battery electric utility vehicles (BEUV) operating in indoor logistics environments. The proposed approach utilizes a combination of proportional-integral (PI), fuzzy PI, and interval type 2 fuzzy PI (IT2fuzzyPI) control structures to augment the state space model for battery management. The state space model incorporates the voltage and current of each battery cell as state variables and considers the current demand from the electric motor as an input. By integrating fuzzy logic with PI control and considering uncertainty, the IT2fuzzyPI structure offers improved control recital and system robustness in the occurrence of nonlinearities, uncertainties, and turbulences. The outcomes of the simulation validate the effectiveness of the proposed scheme in managing the battery pack system’s state of charge and controlling the rates of charging and discharging. The IT2fuzzyPI control significantly improves the overall proficiency and longevity of the battery system, making it suitable for battery electric utility vehicles in logistics environments. This research contributes to the field of battery management systems, providing a valuable tool for designing and evaluating high-performance electric vehicles with enhanced control capabilities.
Rocznik
Strony
art. no. e150330
Opis fizyczny
Bibliogr. 31 poz., rys., tab.
Twórcy
  • Electrical and Electronics Engineering, V.S.B. Engineering College, Karur, Tamil Nadu, India
  • Electrical and Electronics Engineering, K.S.R. College of Engineering, Tiruchengode, Tamil Nadu, India
Bibliografia
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  • [3] M.S.H. Lipu et al., “Battery Management, Key Technologies, Methods, Issues, and Future Trends of Electric Vehicles: A Pathway toward Achieving Sustainable Development Goals,” Batteries, vol. 8, no. 9, p. 119, 2022, doi: 10.3390/batteries8090119.
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  • [5] A.K.M.A. Habib, M.K. Hasan, G.F. Issa, D. Singh, S. Islam, and T.M. Ghazal, “Lithium-Ion Battery Management System for Electric Vehicles: Constraints, Challenges, and Recommendations,” Batteries, vol. 9, no. 3, p. 152, 2023, doi: 10.3390/batteries9030152.
  • [6] K.W. See et al., “Critical review and functional safety of a battery management system for large-scale lithium-ion battery pack technologies,” Int. J. Coal Sci. Technol., vol. 9, p. 36, 2022, doi: 10.1007/s40789-022-00494-0.
  • [7] S. Thangavel, D. Mohanraj, T. Girijaprasanna, S. Raju, C. Dhanamjayulu, and S.M. Muyeen, “A Comprehensive Review on Electric Vehicle: Battery Management System, Charging Station, Traction Motors,” IEEE Access, vol. 11, pp. 20994–21019, 2023, doi: 10.1109/ACCESS.2023.3250221.
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  • [9] R. Katuri, G and Srinivasa Rao, “Modelling and simulation of Math function based controller combined with PID for smooth switching between the battery and ultracapacitor,” Aust. J. Electr. Electron. Eng., vol. 16, no. 3, pp. 163–175, 2019, doi: 10.1080/1448837X.2019.1640009.
  • [10] S.A. Taher and S. Mansouri, “Optimal PI controller design for active power in grid-connected SOFC DG system,” Int. J. Electr. Power Energy Syst., vol. 60, pp. 268–274, 2014, doi: 10.1016/j.ijepes.2014.02.010.
  • [11] T. Girijaprasanna and C. Dhanamjayulu, “A Review on Different State of Battery Charge Estimation Techniques and Management Systems for EV Applications,” Electronics, vol. 11, no. 11, pp. 1795, 2022. doi: 10.3390/electronics11111795.
  • [12] Z. Zhang, H. Shi, R. Zhu, H. Zhao, and Y. Zhu, “Research on electric vehicle charging load prediction and charging mode optimization,” Bull. Pol. Acad. Sci. Tech. Sci., vol. 70, no. 2, pp. 399–414, 2021, doi: 10.24425/aee.2021.136992.
  • [13] G. Napoli, A. Polimeni, S. Micari, G. Dispenza, V. Antonucci, and L. Andaloro, “Freight distribution with electric vehicles: A case study in Sicily. Delivery van development,” Transp. Eng., vol. 3, p. 100048, 2021, doi: 10.1016/j.treng.2021.100048.
  • [14] A.A. Juan, C.A. Mendez, J. Faulin, J. De Armas, and S.E. Grasman, “Electric Vehicles in Logistics and Transportation: A Survey on Emerging Environmental, Strategic, and Operational Challenges,” Energies, vol. 9, no. 2, p. 86, 2016, doi: 10.3390/en9020086.
  • [15] A.D. Jadhav and S. Nair, “Battery Management using Fuzzy Logic Controller,” J. Phys.: Conf. Ser., vol. 1172, p. 012093, 2018, doi: 10.1088/1742-6596/1172/1/012093.
  • [16] S. Nahar, M.R.M. Arnob, and A.H.M. Shatil, “Augmentation of Battery Management Systems in Smart-Grid operation using Fuzzy Logic,” in proc. 2nd Int. Conf. on Robotics, Electrical and Signal Processing Techniques (ICREST), Bangladesh, 2016, pp. 85–89, doi: 10.1109/ICREST51555.2021.9331034.
  • [17] H.A. Calinao, A. Bandala, R. Gustilo, E. Dadios, and M. Rosales, “Battery Management System with Temperature Monitoring Through Fuzzy Logic Control,” in proc. IEEE Region 10 Conference (TENCON), Osaka, Japan, 2020, pp. 852–857, doi: 10.1109/TENCON50793.2020.9293756.
  • [18] O. Castillo and P. Melin, “A review on interval type-2 fuzzy logic applications in intelligent control,” Inf. Sci., vol. 279, pp. 615–631, 2014, doi: 10.1016/j.ins.2014.04.015.
  • [19] P. Gunasekaran, S. Sundramoorthy and N.P. Pulikesi, “Fault data injection attack on car-following model and mitigation based on interval type-2 fuzzy logic controller,” IET Cyber Phys. Syst. Theory Appl., vol. 4, no. 2, pp. 128–138, 2018, doi: 10.1049/ietcps.2018.5012.
  • [20] S. Dey and M. Khanra, “Cybersecurity of Plug-In Electric Vehicles: Cyberattack Detection During Charging,” IEEE Trans. Ind. Electron., vol. 68, no. 1, pp. 478–487, 2021, doi: 10.1109/TIE.2020.2965497.
  • [21] A. Faraz, A. Ambikapathy, S. Thangavel, K. Logavani, G.A. Prasad, “Battery Electric Vehicles (BEVs),” in Electric Vehicles. Green Energy and Technology, N. Patel, A.K. Bhoi, S. Padmanaban, J.B. Holm-Nielsen, Eds., Springer Singapore, 2021.
  • [22] K. Buts, L. Dewan, and M.P.R. Prasad, “PI-Based Feedback Control Technique for Current Control of the Battery Energy Storage System,” in proc. 2022 IEEE 10th Power India International Conference (PIICON), New Delhi, India, 2022, pp. 1–4, doi: 10.1109/PIICON56320.2022.10045157.
  • [23] S. Behera, N.B.D. Choudhury, and N. Swain, “Battery Energy Management and Power Control in Microgrids using PI and Fuzzy Logic Controller based SMA,” in proc. 2022 4th International Conference on Energy, Power and Environment (ICEPE), Shillong, India, 2022, pp. 1–5, doi: 10.1109/ICEPE55035.2022.9798033.
  • [24] M. Zerouali, A.E. Ougli, and B. Tidhaf, “A robust fuzzy logic PI controller for solar system battery charging,” Int. J. Power Electron. Drive Syst., vol. 14, no. 1, pp. 384–394, 2023, doi: 10.11591/ijpeds.v14.i1.pp384-394.
  • [25] O.S.S. Hussian, H.M. Elsayed, and M.A.M. Hassan, “Fuzzy Logic Control for a Stand-Alone PV System with PI Controller for Battery Charging Based on Evolutionary Technique,” in proc. 2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), Metz, France, 2019, pp. 889–894, doi: 10.1109/IDAACS.2019.8924269.
  • [26] M. Praharaj, D. Sain, and B.M. Mohan, “Development, experimental validation, and comparison of interval type-2 Mamdani fuzzy PID controllers with different footprints of uncertainty,” Inf. Sci., vol. 601, pp. 374–402, 2022, doi: 10.1016/j.ins.2022.03.095.
  • [27] M.A. Abdel Ghany, M.E. Bahgat, W.M. Refaey, and S. Sharaf, “Practical interval type-2 fuzzy self-tuning of PID controller to servo permanent magnet synchronous motor,” J. Electr. Syst. Inf. Technol., vol. 7, p. 1, 2020, doi: 10.1186/s43067-019-0008-x.
  • [28] K.P. Chou, M. Prasad,Y.Y. Lin, S. Joshi, C.T. Lin, and J.Y. Chang, “Takagi-Sugeno-Kang type collaborative fuzzy rule based system,” in proc. 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM), Orlando, USA, 2015, pp. 315–320, doi: 10.1109/CIDM.2014.7008684.
  • [29] A. Taskin and T. Kumbasar, “An Open Source Matlab/Simulink Toolbox for Interval Type-2 Fuzzy Logic Systems,” in proc. 2015 IEEE Symposium Series on Computational Intelligence, Cape Town, South Africa, 2016, pp. 1561–1568, doi: 10.1109/SSCI.2015.220.
  • [30] P. Gunasekaran et al., “Adaptive cruise control system with fractional order ANFIS PD+I controller: optimization and validation,” J. Braz. Soc. Mech. Sci. Eng., vol. 46, no. 4, p. 184, Apr. 2024, doi: 10.1007/s40430-024-04699-z.
  • [31] M. Nasir, N. Safitiri, Y. Rachamawati, and M. Arhami, “A Concept of V2G Battery Charging Station as Implementation of IOT and Cyber Physical System,” Bull. Pol. Acad. Sci. Tech. Sci., vol. 69, no. 2, pp. 269–273, 2023, doi: 10.24425/ijet.2023.144360.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-5e872d20-de6f-4dc2-89ba-02605c6916d9
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