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A two-stage eco-cooling control strategy for electric vehicle thermal management system considering multi-source information fusion

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  • Zhao, Yihang
  • Dan, Dan
  • Zheng, Siyu
  • Wei, Mingshan
  • Xie, Yi

Abstract

Thermal management systems (TMS) of electric vehicles (EV) have a significant impact on cabin thermal comfort and battery life, and few studies have adequately considered it. This study proposes a two-stage eco-cooling (TSEC) control strategy to reduce TMS energy consumption while improving cabin thermal comfort and extending battery life. Multi-source information, such as vehicle speed, weather conditions, passenger characteristics, and battery conditions, are all considered. In the first stage, the passenger characteristics and battery conditions are used to calculate the cabin comfort temperature and the battery's optimal operating temperature, respectively. The dynamic programming (DP) algorithm is used to optimize cabin and battery temperature trajectories. Fuzzy PID-based controllers are used in the second stage to achieve the desired temperature. The air conditioning (AC)-cabin thermal model and the battery thermal-electro-aging model have been developed and validated. The proposed TSEC control strategy can improve cabin thermal comfort by automatically adjusting the calculated comfort temperature. Compared with the on-off and PID controllers, the battery life under the TSEC control strategy is improved by 21.48% and 8.55%, respectively, and the energy consumption is reduced by 42.86% and 18.54%, respectively. The proposed control strategy may provide new insight into the TMS of electric vehicles.

Suggested Citation

  • Zhao, Yihang & Dan, Dan & Zheng, Siyu & Wei, Mingshan & Xie, Yi, 2023. "A two-stage eco-cooling control strategy for electric vehicle thermal management system considering multi-source information fusion," Energy, Elsevier, vol. 267(C).
    • Handle: RePEc:eee:energy:v:267:y:2023:i:c:s0360544222034934
    DOI: 10.1016/j.energy.2022.126606
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    References listed on IDEAS

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    1. Pengyu Lu & Qing Gao & Liang Lv & Xiaoye Xue & Yan Wang, 2019. "Numerical Calculation Method of Model Predictive Control for Integrated Vehicle Thermal Management Based on Underhood Coupling Thermal Transmission," Energies, MDPI, vol. 12(2), pages 1-27, January.
    2. Akula, Rajesh & Balaji, C., 2022. "Thermal management of 18650 Li-ion battery using novel fins–PCM–EG composite heat sinks," Applied Energy, Elsevier, vol. 316(C).
    3. Huang, Xianghui & Li, Kuining & Xie, Yi & Liu, Bin & Liu, Jiangyan & Liu, Zhaoming & Mou, Lunjie, 2022. "A novel multistage constant compressor speed control strategy of electric vehicle air conditioning system based on genetic algorithm," Energy, Elsevier, vol. 241(C).
    4. Lander, Laura & Kallitsis, Evangelos & Hales, Alastair & Edge, Jacqueline Sophie & Korre, Anna & Offer, Gregory, 2021. "Cost and carbon footprint reduction of electric vehicle lithium-ion batteries through efficient thermal management," Applied Energy, Elsevier, vol. 289(C).
    5. Ren, Ruyang & Zhao, Yaohua & Diao, Yanhua & Liang, Lin, 2022. "Experimental study on preheating thermal management system for lithium-ion battery based on U-shaped micro heat pipe array," Energy, Elsevier, vol. 253(C).
    6. Ma, Yan & Ding, Hao & Liu, Yongqin & Gao, Jinwu, 2022. "Battery thermal management of intelligent-connected electric vehicles at low temperature based on NMPC," Energy, Elsevier, vol. 244(PA).
    7. Huang, Yanjun & Khajepour, Amir & Bagheri, Farshid & Bahrami, Majid, 2016. "Optimal energy-efficient predictive controllers in automotive air-conditioning/refrigeration systems," Applied Energy, Elsevier, vol. 184(C), pages 605-618.
    8. Wan, Taocheng & Bai, Yan & Wang, Tingxiang & Wei, Zhuo, 2022. "BPNN-based optimal strategy for dynamic energy optimization with providing proper thermal comfort under the different outdoor air temperatures," Applied Energy, Elsevier, vol. 313(C).
    9. Mahmoudzadeh Andwari, Amin & Pesiridis, Apostolos & Rajoo, Srithar & Martinez-Botas, Ricardo & Esfahanian, Vahid, 2017. "A review of Battery Electric Vehicle technology and readiness levels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 414-430.
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    Cited by:

    1. Meng Li & Siyu Zheng & Mingshan Wei, 2023. "Flow Loss Analysis and Structural Optimization of Multiway Valves for Integrated Thermal Management Systems in Electric Vehicles," Energies, MDPI, vol. 16(13), pages 1-22, June.
    2. Jixian Sun & Dan Dan & Mingshan Wei & Senlin Cai & Yihang Zhao & Edward Wright, 2023. "Pack-Level Modeling and Thermal Analysis of a Battery Thermal Management System with Phase Change Materials and Liquid Cooling," Energies, MDPI, vol. 16(15), pages 1-16, August.
    3. Dan Dan & Yihang Zhao & Mingshan Wei & Xuehui Wang, 2023. "Review of Thermal Management Technology for Electric Vehicles," Energies, MDPI, vol. 16(12), pages 1-38, June.

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