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Strategies for the Modelisation of Electric Vehicle Energy Consumption: A Review

Author

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  • Andrea Di Martino

    (Department of Energy, Politecnico di Milano, Via La Masa, 34, 20156 Milan, Italy)

  • Seyed Mahdi Miraftabzadeh

    (Department of Energy, Politecnico di Milano, Via La Masa, 34, 20156 Milan, Italy)

  • Michela Longo

    (Department of Energy, Politecnico di Milano, Via La Masa, 34, 20156 Milan, Italy)

Abstract

The continuous technical improvements involving electric motors, battery packs, and general powertrain equipment make it strictly necessary to predict or evaluate the energy consumption of electric vehicles (EVs) with reasonable accuracy. The significant improvements in computing power in the last decades have allowed the implementation of various simulation scenarios and the development of strategies for vehicle modelling, thus estimating energy consumption with higher accuracy. This paper gives a general overview of the strategies adopted to model EVs for evaluating or predicting energy consumption. The need to develop such solutions is due to the basis of each analysis, as well as the type of results that must be produced and delivered. This last point strongly influences the whole set-up process of the analysis, from the available and collected dataset to the choice of the algorithm itself.

Suggested Citation

  • Andrea Di Martino & Seyed Mahdi Miraftabzadeh & Michela Longo, 2022. "Strategies for the Modelisation of Electric Vehicle Energy Consumption: A Review," Energies, MDPI, vol. 15(21), pages 1-20, October.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:21:p:8115-:d:959222
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    References listed on IDEAS

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    2. Ma, Yifan & Sun, Wei & Zhao, Zhoulun & Gu, Leqi & Zhang, Hui & Jin, Yucheng & Yuan, Xinmei, 2024. "Physically rational data augmentation for energy consumption estimation of electric vehicles," Applied Energy, Elsevier, vol. 373(C).

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