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Driving cycles construction for electric vehicles considering road environment: A case study in Beijing

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  • Zhang, Jin
  • Wang, Zhenpo
  • Liu, Peng
  • Zhang, Zhaosheng
  • Li, Xiaoyu
  • Qu, Changhui

Abstract

With the trend of transportation electrification, driving cycles have been widely recognized as effective tools to tackle the challenges of the optimal design, management and evaluation of electric vehicles. In this work, real-world driving data recorded on 1 Hz of 40 electric taxis in Beijing area for 6 months are obtained and fused with road environment information to construct driving cycles tailored for electric vehicles. The conventional Micro-trip method is improved based on minimum comprehensive parameters deviation, which achieve better accuracy with less computational load. A novel improved Markov Monte Carlo method considering the driving features on different roads is proposed to reflect the features of road environment in the driving cycles. 53 parameters including characteristic and distribution parameters are extracted from driving data and used to comprehensively describe the features of driving process, in which the road environment and energy related parameters are also included. Based on Mean absolute percentage error and K-S test, the performances of the proposed methods have been investigated, and the constructed driving cycles as well as NEDC are verified and compared to real-world driving condition.

Suggested Citation

  • Zhang, Jin & Wang, Zhenpo & Liu, Peng & Zhang, Zhaosheng & Li, Xiaoyu & Qu, Changhui, 2019. "Driving cycles construction for electric vehicles considering road environment: A case study in Beijing," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    • Handle: RePEc:eee:appene:v:253:y:2019:i:c:31
    DOI: 10.1016/j.apenergy.2019.113514
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    1. Agudelo, Andrés F. & García-Contreras, Reyes & Agudelo, John R. & Armas, Octavio, 2016. "Potential for exhaust gas energy recovery in a diesel passenger car under European driving cycle," Applied Energy, Elsevier, vol. 174(C), pages 201-212.
    2. Gong, Huiming & Zou, Yuan & Yang, Qingkai & Fan, Jie & Sun, Fengchun & Goehlich, Dietmar, 2018. "Generation of a driving cycle for battery electric vehicles：A case study of Beijing," Energy, Elsevier, vol. 150(C), pages 901-912.
    3. Ruan, Jiageng & Walker, Paul D. & Watterson, Peter A. & Zhang, Nong, 2016. "The dynamic performance and economic benefit of a blended braking system in a multi-speed battery electric vehicle," Applied Energy, Elsevier, vol. 183(C), pages 1240-1258.
    4. Choi, Wonjae & Song, Han Ho, 2018. "Well-to-wheel greenhouse gas emissions of battery electric vehicles in countries dependent on the import of fuels through maritime transportation: A South Korean case study," Applied Energy, Elsevier, vol. 230(C), pages 135-147.
    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. Bizhong Xia & Haiqing Wang & Mingwang Wang & Wei Sun & Zhihui Xu & Yongzhi Lai, 2015. "A New Method for State of Charge Estimation of Lithium-Ion Battery Based on Strong Tracking Cubature Kalman Filter," Energies, MDPI, vol. 8(12), pages 1-15, November.
    7. Wang, Hewu & Zhang, Xiaobin & Ouyang, Minggao, 2015. "Energy consumption of electric vehicles based on real-world driving patterns: A case study of Beijing," Applied Energy, Elsevier, vol. 157(C), pages 710-719.
    8. Armas, Octavio & García-Contreras, Reyes & Ramos, Ángel, 2013. "Impact of alternative fuels on performance and pollutant emissions of a light duty engine tested under the new European driving cycle," Applied Energy, Elsevier, vol. 107(C), pages 183-190.
    9. Yi, Chenyu & Epureanu, Bogdan I. & Hong, Sung-Kwon & Ge, Tony & Yang, Xiao Guang, 2016. "Modeling, control, and performance of a novel architecture of hybrid electric powertrain system," Applied Energy, Elsevier, vol. 178(C), pages 454-467.
    10. M. Hadi Amini & Orkun Karabasoglu, 2018. "Optimal Operation of Interdependent Power Systems and Electrified Transportation Networks," Energies, MDPI, vol. 11(1), pages 1-25, January.
    11. Brady, John & O’Mahony, Margaret, 2016. "Development of a driving cycle to evaluate the energy economy of electric vehicles in urban areas," Applied Energy, Elsevier, vol. 177(C), pages 165-178.
    12. Wolfram, Paul & Wiedmann, Thomas, 2017. "Electrifying Australian transport: Hybrid life cycle analysis of a transition to electric light-duty vehicles and renewable electricity," Applied Energy, Elsevier, vol. 206(C), pages 531-540.
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    Cited by:

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    2. Triluck Kusalaphirom & Thaned Satiennam & Wichuda Satiennam & Atthapol Seedam, 2022. "Development of a Real-World Eco-Driving Cycle for Motorcycles," Sustainability, MDPI, vol. 14(10), pages 1-14, May.
    3. 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).
    4. Hongli Liu & Weiguo Yun & Bin Li & Mengling Dai & Yangyuhang Wang, 2023. "A Quantitative Study on Driving Behavior Economy Based on Big Data from the Pure Electric Bus," Sustainability, MDPI, vol. 15(10), pages 1-16, May.
    5. David Watling & Patrícia Baptista & Gonçalo Duarte & Jianbing Gao & Haibo Chen, 2022. "Systematic Method for Developing Reference Driving Cycles Appropriate to Electric L-Category Vehicles," Energies, MDPI, vol. 15(9), pages 1-28, May.
    6. Schücking, Maximilian & Jochem, Patrick, 2021. "Two-stage stochastic program optimizing the cost of electric vehicles in commercial fleets," Applied Energy, Elsevier, vol. 293(C).

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