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Urban-scale estimation model of carbon emissions for ride-hailing electric vehicles during operational phase

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  • Huang, Hai-chao
  • He, Hong-di
  • Peng, Zhong-ren

Abstract

Ride-hailing Electric Vehicles (EVs) offer a dual benefit by mitigating carbon emissions and providing convenient transportation solutions. Nevertheless, current emissions estimation models for urban-scale lack consideration of the real-world travel behaviors during operational phase. This study extracted the characteristics of ride-hailing EVs in Shanghai and Shenzhen based on 14.77 million real-world driving records, and established an emission estimation model. The emission estimation model delineates the relationship between speed State of Charge (SOC) and operational efficient of ride-hailing EVs in cities. Compared to traditional methods relying on manufacturer-claimed energy consumption rates, the developed model demonstrates a 38.4% increase in accuracy. It reveals that ride-hailing EVs deviate from the optimal speed in approximately 90% of their trips under the current urban transportation system. A 5 km/h increase in ride-hailing EV speed can improve emission reduction potential, cutting annual emissions by 0.89 ktCO2 in Shanghai and 4.74 ktCO2 in Shenzhen. Additionally, when a ride-hailing EV operates with SOC between 10 and 30%, emissions are 21.4%–36.0% higher compared to SOC between 70 and 90%. At last, the model derives emission factors for ride-hailing EVs during operational phase in Shanghai and Shenzhen are 0.2635 and 0.1535 10−5MtCO2kWh−1km−1

Suggested Citation

  • Huang, Hai-chao & He, Hong-di & Peng, Zhong-ren, 2024. "Urban-scale estimation model of carbon emissions for ride-hailing electric vehicles during operational phase," Energy, Elsevier, vol. 293(C).
    • Handle: RePEc:eee:energy:v:293:y:2024:i:c:s0360544224004377
    DOI: 10.1016/j.energy.2024.130665
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    as
    1. Hasan, Saiful & Simsekoglu, Özlem, 2020. "The role of psychological factors on vehicle kilometer travelled (VKT) for battery electric vehicle (BEV) users," Research in Transportation Economics, Elsevier, vol. 82(C).
    2. Ryuji Kawamoto & Hideo Mochizuki & Yoshihisa Moriguchi & Takahiro Nakano & Masayuki Motohashi & Yuji Sakai & Atsushi Inaba, 2019. "Estimation of CO 2 Emissions of Internal Combustion Engine Vehicle and Battery Electric Vehicle Using LCA," Sustainability, MDPI, vol. 11(9), pages 1-15, May.
    3. Xu, Xiaodan & Aziz, H.M. Abdul & Liu, Haobing & Rodgers, Michael O. & Guensler, Randall, 2020. "A scalable energy modeling framework for electric vehicles in regional transportation networks," Applied Energy, Elsevier, vol. 269(C).
    4. Shiqi Ou & Rujie Yu & Zhenhong Lin & Huanhuan Ren & Xin He & Steven Przesmitzki & Jessey Bouchard, 2020. "Intensity and daily pattern of passenger vehicle use by region and class in China: estimation and implications for energy use and electrification," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 25(3), pages 307-327, March.
    5. Jochem, Patrick & Babrowski, Sonja & Fichtner, Wolf, 2015. "Assessing CO2 emissions of electric vehicles in Germany in 2030," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 68-83.
    6. 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.
    7. 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.
    8. Zhang, Jin & Wang, Zhenpo & Liu, Peng & Zhang, Zhaosheng, 2020. "Energy consumption analysis and prediction of electric vehicles based on real-world driving data," Applied Energy, Elsevier, vol. 275(C).
    9. Chenen Ma & Lina Madaniyazi & Yang Xie, 2021. "Impact of the Electric Vehicle Policies on Environment and Health in the Beijing–Tianjin–Hebei Region," IJERPH, MDPI, vol. 18(2), pages 1-14, January.
    10. Troy R. Hawkins & Bhawna Singh & Guillaume Majeau‐Bettez & Anders Hammer Strømman, 2013. "Comparative Environmental Life Cycle Assessment of Conventional and Electric Vehicles," Journal of Industrial Ecology, Yale University, vol. 17(1), pages 53-64, February.
    11. Rebecca E. Ciez & J. F. Whitacre, 2019. "Examining different recycling processes for lithium-ion batteries," Nature Sustainability, Nature, vol. 2(2), pages 148-156, February.
    12. Hoehne, Christopher G. & Chester, Mikhail V., 2016. "Optimizing plug-in electric vehicle and vehicle-to-grid charge scheduling to minimize carbon emissions," Energy, Elsevier, vol. 115(P1), pages 646-657.
    13. Bi, Jun & Wang, Yongxing & Sai, Qiuyue & Ding, Cong, 2019. "Estimating remaining driving range of battery electric vehicles based on real-world data: A case study of Beijing, China," Energy, Elsevier, vol. 169(C), pages 833-843.
    14. Wu, Ye & Yang, Zhengdong & Lin, Bohong & Liu, Huan & Wang, Renjie & Zhou, Boya & Hao, Jiming, 2012. "Energy consumption and CO2 emission impacts of vehicle electrification in three developed regions of China," Energy Policy, Elsevier, vol. 48(C), pages 537-550.
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    1. Zhang, Zhe & Yu, Qing & Gao, Kun & He, Hong-Di & Liu, Yang & Huang, Haichao, 2025. "Carbon emission reduction benefits of ride-hailing vehicle electrification considering energy structure," Applied Energy, Elsevier, vol. 377(PA).

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