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A Comprehensive Model to Estimate Electric Vehicle Battery’s State of Charge for a Pre-Scheduled Trip Based on Energy Consumption Estimation

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  • Quynh T. Tran

    (Hawaii Natural Energy Institute, University of Hawai’i at Mānoa, Honolulu, HI 96822, USA
    Institute of Energy Science, Vietnam Academy of Science and Technology, Hanoi 10000-04, Vietnam)

  • Leon Roose

    (Hawaii Natural Energy Institute, University of Hawai’i at Mānoa, Honolulu, HI 96822, USA)

  • Chayaphol Vichitpunt

    (Digital Strategy Department, Provincial Electricity Authority, Chatuchak, Bangkok 10900, Thailand)

  • Kumpanat Thongmai

    (Power Economic Policy Department, Provincial Electricity Authority, Chatucha, Bangkok 10900, Thailand)

  • Krittanat Noisopa

    (Provincial Electricity Authority KhokKham Branch, Samut Sakhon 74000, Thailand)

Abstract

EV development is being prioritized in order to attain the target of net zero emissions by 2050. Electric vehicles have the potential to decrease greenhouse gas (GHG) emissions, which contribute to global warming. The driving range of electric vehicles is a significant limitation that prevents people from using them generally. This paper proposes a comprehensive model for calculating the amount of energy needed to charge EVs for a scheduled trip. The model contains anticipated consumption energy for the whole trip as well as contingency energy to account for unpredictable conditions. The model is simple to apply to various types of electric vehicles and produces results with sufficient precision. A number of driving tests with different road characteristics and weather conditions were implemented to evaluate the success of the proposed method. The findings could help the users feel more confidence when driving EVs, promote the usage of EVs, and advocate for the increased use of green and renewable energy sources.

Suggested Citation

  • Quynh T. Tran & Leon Roose & Chayaphol Vichitpunt & Kumpanat Thongmai & Krittanat Noisopa, 2022. "A Comprehensive Model to Estimate Electric Vehicle Battery’s State of Charge for a Pre-Scheduled Trip Based on Energy Consumption Estimation," Clean Technol., MDPI, vol. 5(1), pages 1-13, December.
    • Handle: RePEc:gam:jcltec:v:5:y:2022:i:1:p:2-37:d:1012577
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    References listed on IDEAS

    as
    1. Enjian Yao & Zhiqiang Yang & Yuanyuan Song & Ting Zuo, 2013. "Comparison of Electric Vehicle’s Energy Consumption Factors for Different Road Types," Discrete Dynamics in Nature and Society, Hindawi, vol. 2013, pages 1-7, December.
    2. Seyed Mahdi Miraftabzadeh & Michela Longo & Federica Foiadelli, 2021. "Estimation Model of Total Energy Consumptions of Electrical Vehicles under Different Driving Conditions," Energies, MDPI, vol. 14(4), pages 1-15, February.
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