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Network-level energy consumption estimation for electric vehicles considering vehicle and user heterogeneity

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  • Wang, Hua
  • Zhao, De
  • Meng, Qiang
  • Ong, Ghim Ping
  • Lee, Der-Horng

Abstract

As a green transport means, electric vehicle (EV) has received widespread attention in recent years and an increasing number of cities have been establishing their EV transport systems including EV fleet management and charging infrastructure. Transport policy-makers are concerning about the system performance of an EV charging system measured by energy consumption and user experience. We in this paper aim to develop an effective method for the expected total energy consumption estimation (ETEC) of EV charging systems deployed in a dense city. To achieve this objective, we firstly introduce the nonlinear charging profile, its impacts on energy consumption as well as user experience, and present an approach for estimating the nonlinear charging time. We then elaborate our method to estimate energy consumption for one-time EV charging by addressing four kinds of energy losses in charging process. Next, charging frequency by considering multi-type EVs, and their heterogeneities and different charging needs for normal and fast charging systems is analyzed in depth. These two together determine the network-wide energy consumption and a pro-rated approach is used to figure out the spatial distribution of energy consumption. A case study of Singapore is conducted in the end to validate the proposed methodology. Numerical results reveal a trade-off between energy saving and user experience, and also demonstrate the importance of considering heterogeneities of driving range, charging preference and daily travel mileage.

Suggested Citation

  • Wang, Hua & Zhao, De & Meng, Qiang & Ong, Ghim Ping & Lee, Der-Horng, 2020. "Network-level energy consumption estimation for electric vehicles considering vehicle and user heterogeneity," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 30-46.
  • Handle: RePEc:eee:transa:v:132:y:2020:i:c:p:30-46
    DOI: 10.1016/j.tra.2019.10.010
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    References listed on IDEAS

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    1. Apostolaki-Iosifidou, Elpiniki & Codani, Paul & Kempton, Willett, 2017. "Measurement of power loss during electric vehicle charging and discharging," Energy, Elsevier, vol. 127(C), pages 730-742.
    2. Wang, Hua & Zhao, De & Meng, Qiang & Ong, Ghim Ping & Lee, Der-Horng, 2019. "A four-step method for electric-vehicle charging facility deployment in a dense city: An empirical study in Singapore," Transportation Research Part A: Policy and Practice, Elsevier, vol. 119(C), pages 224-237.
    3. Burski, Zbigniew & Mijalska-Szewczak, Izabela & Wasilewski, Jacek & Szczepanik, Małgorzata, 2016. "Evaluation of energy consumption of vehicles in EU Trans-European Transport Network," Transportation Research Part A: Policy and Practice, Elsevier, vol. 92(C), pages 120-130.
    4. Fan Yang & Yuanyuan Xie & Yelin Deng & Chris Yuan, 2018. "Predictive modeling of battery degradation and greenhouse gas emissions from U.S. state-level electric vehicle operation," Nature Communications, Nature, vol. 9(1), pages 1-10, December.
    5. Liu, Kai & Wang, Jiangbo & Yamamoto, Toshiyuki & Morikawa, Takayuki, 2016. "Modelling the multilevel structure and mixed effects of the factors influencing the energy consumption of electric vehicles," Applied Energy, Elsevier, vol. 183(C), pages 1351-1360.
    6. Gardner, Lauren M. & Duell, Melissa & Waller, S. Travis, 2013. "A framework for evaluating the role of electric vehicles in transportation network infrastructure under travel demand variability," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 76-90.
    7. Yang, S.C. & Li, M. & Lin, Y. & Tang, T.Q., 2014. "Electric vehicle’s electricity consumption on a road with different slope," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 402(C), pages 41-48.
    8. Scarinci, Riccardo & Rast, Frédéric & Bierlaire, Michel, 2017. "Needed reduction in mobility energy consumption to meet the goal of a 2000-watt society," Transportation Research Part A: Policy and Practice, Elsevier, vol. 101(C), pages 133-148.
    9. Fiori, Chiara & Ahn, Kyoungho & Rakha, Hesham A., 2016. "Power-based electric vehicle energy consumption model: Model development and validation," Applied Energy, Elsevier, vol. 168(C), pages 257-268.
    10. 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.
    11. Cedric De Cauwer & Joeri Van Mierlo & Thierry Coosemans, 2015. "Energy Consumption Prediction for Electric Vehicles Based on Real-World Data," Energies, MDPI, vol. 8(8), pages 1-21, August.
    12. Poudenx, Pascal, 2008. "The effect of transportation policies on energy consumption and greenhouse gas emission from urban passenger transportation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(6), pages 901-909, July.
    13. Chen, T. Donna & Kockelman, Kara M. & Hanna, Josiah P., 2016. "Operations of a shared, autonomous, electric vehicle fleet: Implications of vehicle & charging infrastructure decisions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 243-254.
    14. Wang, Ning & Pan, Huizhong & Zheng, Wenhui, 2017. "Assessment of the incentives on electric vehicle promotion in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 101(C), pages 177-189.
    15. Pelletier, Samuel & Jabali, Ola & Laporte, Gilbert & Veneroni, Marco, 2017. "Battery degradation and behaviour for electric vehicles: Review and numerical analyses of several models," Transportation Research Part B: Methodological, Elsevier, vol. 103(C), pages 158-187.
    16. Plötz, Patrick & Funke, Simon Árpád & Jochem, Patrick, 2018. "The impact of daily and annual driving on fuel economy and CO2 emissions of plug-in hybrid electric vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 331-340.
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