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Comparison of Electric Vehicle’s Energy Consumption Factors for Different Road Types

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  • Enjian Yao
  • Zhiqiang Yang
  • Yuanyuan Song
  • Ting Zuo

Abstract

Energy-optimal route planning for electric vehicle (EV) is highly required for the wide-spread use of EV, which is hindered by limited battery capacity and relative short cruising range. Obtaining the cost for each link (i.e., link energy consumption) in road networks plays a key role in energy-optimal route planning process. The link energy consumption depends mainly on energy consumption factor, which is related to not only vehicle speed but also road type. This study aims to analyze the difference of EV’s energy consumption factors for different road types. According to the floating car data (FCD) collected from the road network in Beijing, the vehicle specific power (VSP) distributions under different average travel speeds for different road types are analyzed firstly, and then the EV’s energy consumption rates under different VSP-Bins are calculated. By using VSP as an intermediate variable, EV’s energy consumption factor models for different road types are established and the difference of EV’s energy consumption factors is analyzed. The results show that road type-based energy consumption factor should be used in EV’s energy-optimal route planning process.

Suggested Citation

  • 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.
    • Handle: RePEc:hin:jnddns:328757
    DOI: 10.1155/2013/328757
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    3. Qiang Xing & Zhong Chen & Ziqi Zhang & Xiao Xu & Tian Zhang & Xueliang Huang & Haiwei Wang, 2020. "Urban Electric Vehicle Fast-Charging Demand Forecasting Model Based on Data-Driven Approach and Human Decision-Making Behavior," Energies, MDPI, vol. 13(6), pages 1-32, March.
    4. Aghajan-Eshkevari, Saleh & Ameli, Mohammad Taghi & Azad, Sasan, 2023. "Optimal routing and power management of electric vehicles in coupled power distribution and transportation systems," Applied Energy, Elsevier, vol. 341(C).
    5. Triluck Kusalaphirom & Thaned Satiennam & Wichuda Satiennam, 2023. "Factors Influencing the Real-World Electricity Consumption of Electric Motorcycles," Energies, MDPI, vol. 16(17), pages 1-11, September.
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    7. Yang, Xiong & Zhuge, Chengxiang & Shao, Chunfu & Huang, Yuantan & Hayse Chiwing G. Tang, Justin & Sun, Mingdong & Wang, Pinxi & Wang, Shiqi, 2022. "Characterizing mobility patterns of private electric vehicle users with trajectory data," Applied Energy, Elsevier, vol. 321(C).
    8. Ioannou, Petros & Giuliano, Genevieve & Dessouky, Maged & Chen, Pengfei & Dexter, Sue, 2020. "Freight Load Balancing and Efficiencies in Alternative Fuel Freight Modes," Institute of Transportation Studies, Working Paper Series qt3ns4b894, Institute of Transportation Studies, UC Davis.
    9. Graba, M. & Mamala, J. & Bieniek, A. & Sroka, Z., 2021. "Impact of the acceleration intensity of a passenger car in a road test on energy consumption," Energy, Elsevier, vol. 226(C).
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    11. Zhao, Fangxia & Shang, HuaYan & Cui, JiHui, 2023. "Role of electric vehicle driving behavior on optimal setting of wireless charging lane," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 618(C).
    12. Wang, Zihao & Ge, Hongxia & Cheng, Rongjun, 2020. "An extended macro model accounting for the driver’s timid and aggressive attributions and bounded rationality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    13. Dwivedi, Pankaj Prasad & Sharma, Dilip Kumar, 2023. "Evaluation and ranking of battery electric vehicles by Shannon’s entropy and TOPSIS methods," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 212(C), pages 457-474.
    14. Luin, Blaž & Petelin, Stojan & Al-Mansour, Fouad, 2019. "Microsimulation of electric vehicle energy consumption," Energy, Elsevier, vol. 174(C), pages 24-32.
    15. Maksymilian Mądziel & Tiziana Campisi, 2023. "Energy Consumption of Electric Vehicles: Analysis of Selected Parameters Based on Created Database," Energies, MDPI, vol. 16(3), pages 1-18, February.
    16. Ecer, Fatih, 2021. "A consolidated MCDM framework for performance assessment of battery electric vehicles based on ranking strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    17. 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.
    18. Bi, Huibo & Shang, Wen-Long & Chen, Yanyan & Wang, Kezhi & Yu, Qing & Sui, Yi, 2021. "GIS aided sustainable urban road management with a unifying queueing and neural network model," Applied Energy, Elsevier, vol. 291(C).
    19. Jarosław Mamala & Michał Śmieja & Krzysztof Prażnowski, 2021. "Analysis of the Total Unit Energy Consumption of a Car with a Hybrid Drive System in Real Operating Conditions," Energies, MDPI, vol. 14(13), pages 1-16, July.
    20. Ioannou, Petros & Chen, Pengfei, 2023. "Centrally Coordinated Schedules and Routes of Airport Shuttles with LAX Terminals as Application Area," Institute of Transportation Studies, Working Paper Series qt6gg7r6c5, Institute of Transportation Studies, UC Davis.
    21. 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.
    22. Li, Lifu & Liu, Qin, 2019. "Acceleration curve optimization for electric vehicle based on energy consumption and battery life," Energy, Elsevier, vol. 169(C), pages 1039-1053.

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