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Real-Time Implementable Integrated Energy and Cabin Temperature Management for Battery Life Extension in Electric Vehicles

Author

Listed:
  • Mattia Mauro

    (Department of Mechanical and Aerospace Engineering (DIMEAS), Politecnico di Torino, 10129 Turin, Italy)

  • Atriya Biswas

    (Mechanical Engineering, McMaster University, Hamilton, ON L8S 4L8, Canada)

  • Carlo Fiorillo

    (Department of Mechanical and Aerospace Engineering (DIMEAS), Politecnico di Torino, 10129 Turin, Italy)

  • Hao Wang

    (Mechanical Engineering, McMaster University, Hamilton, ON L8S 4L8, Canada)

  • Ezio Spessa

    (Department of Mechanical and Aerospace Engineering (DIMEAS), Politecnico di Torino, 10129 Turin, Italy)

  • Federico Miretti

    (Department of Mechanical and Aerospace Engineering (DIMEAS), Politecnico di Torino, 10129 Turin, Italy)

  • Ryan Ahmed

    (Mechanical Engineering, McMaster University, Hamilton, ON L8S 4L8, Canada)

  • Angelo Bonfitto

    (Department of Mechanical and Aerospace Engineering (DIMEAS), Politecnico di Torino, 10129 Turin, Italy)

  • Ali Emadi

    (Mechanical Engineering, McMaster University, Hamilton, ON L8S 4L8, Canada)

Abstract

Among many emerging technologies, battery electric vehicles (BEVs) have emerged as a prominent and highly supported solution to stringent emissions regulations. However, despite their increasing popularity, key challenges that might jeopardize their further spread are the lack of charging infrastructure, battery life degradation, and the discrepancy between the actual and promised all-electric driving range. The primary focus of this paper is to formulate an integrated energy and thermal comfort management (IETM) strategy. This strategy optimally manages the electrical energy required by the heating, ventilation, and air conditioning (HVAC) unit, the most impacting auxiliary in terms of battery load, to minimize battery life degradation over any specific drive cycle while ensuring the actual cabin temperature hovers within the permissible tolerance limit from the reference cabin temperature and the driver-requested traction power is always satisfied. This work incorporates a state-of-health (SOH) estimation model, a high-fidelity cabin thermodynamics model, and an HVAC model into the forward-approach simulation model of a commercially available BEV to showcase the impact and efficacy of the proposed IETM strategy for enhancing battery longevity. The instantaneous optimization problem of IETM is solved by the golden-section search method leveraging the convexity of the objective function. Simulated results under different driving scenarios show that the improvement brought by the proposed ITEM controller can minimize battery health degradation by up to 4.5% and energy consumption by up to 2.8% while maintaining the cabin temperature deviation within permissible limits from the reference temperature.

Suggested Citation

  • Mattia Mauro & Atriya Biswas & Carlo Fiorillo & Hao Wang & Ezio Spessa & Federico Miretti & Ryan Ahmed & Angelo Bonfitto & Ali Emadi, 2024. "Real-Time Implementable Integrated Energy and Cabin Temperature Management for Battery Life Extension in Electric Vehicles," Energies, MDPI, vol. 17(13), pages 1-20, June.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:13:p:3185-:d:1424769
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    References listed on IDEAS

    as
    1. Cong Zhang & Dai Wang & Bin Wang & Fan Tong, 2020. "Battery Degradation Minimization-Oriented Hybrid Energy Storage System for Electric Vehicles," Energies, MDPI, vol. 13(1), pages 1-21, January.
    2. Liimatainen, Heikki & van Vliet, Oscar & Aplyn, David, 2019. "The potential of electric trucks – An international commodity-level analysis," Applied Energy, Elsevier, vol. 236(C), pages 804-814.
    3. Wu, Yue & Huang, Zhiwu & Li, Dongjun & Li, Heng & Peng, Jun & Stroe, Daniel & Song, Ziyou, 2024. "Optimal battery thermal management for electric vehicles with battery degradation minimization," Applied Energy, Elsevier, vol. 353(PA).
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