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Real-Time Management for an EV Hybrid Storage System Based on Fuzzy Control

Author

Listed:
  • Dimitrios Rimpas

    (Department of Electrical & Electronics Engineering, University of West Attica, 250 Thivon Av., 122-44 Egaleo, Greece)

  • Stavrοs D. Kaminaris

    (Department of Electrical & Electronics Engineering, University of West Attica, 250 Thivon Av., 122-44 Egaleo, Greece)

  • Dimitrios D. Piromalis

    (Department of Electrical & Electronics Engineering, University of West Attica, 250 Thivon Av., 122-44 Egaleo, Greece)

  • George Vokas

    (Department of Electrical & Electronics Engineering, University of West Attica, 250 Thivon Av., 122-44 Egaleo, Greece)

Abstract

Following the European Climate Law of 2021 and the climate neutrality goal for zero-emission transportation by 2050, electric vehicles continue to gain market share, reaching 2.5 million vehicles in Q1 of 2023. Electric vehicles utilize an electric motor for propulsion powered by lithium batteries, which suffer from high temperatures caused by peak operation conditions and rapid charging, so hybridization with supercapacitors is implemented. In this paper, a fuzzy logic controller is employed based on a rule-based scheme and the Mamdani model to control the power distribution of the hybrid system, driven by the state of charge and duty cycle parameters. An active topology with one bi-directional DC-to-DC converter at each source is exploited in the MATLAB/Simulink environment, and five power states like acceleration and coasting are identified. Results show that the ideal duty cycle is within 0.40–0.50 as a universal value for all power states, which may vary depending on the available state of charge. Total efficiency is enhanced by 6%, sizing is increased by 22%, leading to a more compact layout, and battery life is extended by 20%. Future work includes testing with larger energy sources and the application of this management strategy in real-time operations.

Suggested Citation

  • Dimitrios Rimpas & Stavrοs D. Kaminaris & Dimitrios D. Piromalis & George Vokas, 2023. "Real-Time Management for an EV Hybrid Storage System Based on Fuzzy Control," Mathematics, MDPI, vol. 11(21), pages 1-18, October.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:21:p:4429-:d:1267304
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    References listed on IDEAS

    as
    1. Xiong, Rui & Duan, Yanzhou & Cao, Jiayi & Yu, Quanqing, 2018. "Battery and ultracapacitor in-the-loop approach to validate a real-time power management method for an all-climate electric vehicle," Applied Energy, Elsevier, vol. 217(C), pages 153-165.
    2. Dong, Ao & Ma, Ruifei & Deng, Yelin, 2023. "Optimization on charging of the direct hybrid lithium-ion battery and supercapacitor for high power application through resistance balancing," Energy, Elsevier, vol. 273(C).
    3. Xinyu Zhao & Yunxiao Zhang & Xueying Cui & Le Wan & Jinlong Qiu & Erfa Shang & Yongchang Zhang & Haisen Zhao, 2023. "Wavelet Packet-Fuzzy Optimization Control Strategy of Hybrid Energy Storage Considering Charge–Discharge Time Sequence," Sustainability, MDPI, vol. 15(13), pages 1-17, July.
    4. Adrian Chmielewski & Piotr Piórkowski & Krzysztof Bogdziński & Jakub Możaryn, 2023. "Application of a Bidirectional DC/DC Converter to Control the Power Distribution in the Battery–Ultracapacitor System," Energies, MDPI, vol. 16(9), pages 1-40, April.
    5. Tsemekidi Tzeiranaki, Sofia & Economidou, Marina & Bertoldi, Paolo & Thiel, Christian & Fontaras, Georgios & Clementi, Enrico Luca & Franco De Los Rios, Camilo, 2023. "“The impact of energy efficiency and decarbonisation policies on the European road transport sector”," Transportation Research Part A: Policy and Practice, Elsevier, vol. 170(C).
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