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A novel optimization-based method to develop representative driving cycle in various driving conditions

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  • Cui, Yuepeng
  • Zou, Fumin
  • Xu, Hao
  • Chen, Zhihui
  • Gong, Kuangmin

Abstract

The lack representativeness of in-used driving cycles has raised substantial concerns regarding the enlarging gap between real-world fuel consumption and type-approval. Considering the high randomness of existing driving cycle development methods, the developed cycle still has low representativeness in capturing the patterns in the real-world. In this study, a novel data-driven driving cycle development method MMACO-MC based on Min-Max Ant Colony Optimization (MMACO) and Markov Chain is proposed to improve the representativeness of driving cycles. The proposed MMACO-MC is then applied to develop driving cycles in Fuzhou city under various driving conditions. Significant differences in cycle parameters have been observed in different driving conditions, which further lead to a 15% deviation on the FCR estimation (Fuel Consumption Rate). Meanwhile, the FCR estimation in the whole region of Fuzhou also deviates from the standard cycles from 22.8% to 29.4%. Lastly, the optimal cycle length is explored to ensure the stability of FCR estimation under various traffic scenarios. This study highlighted the necessity of optimization-based driving cycle development in the accuracy of fuel consumption estimation. The proposed method and the conclusions could be applied as a reference by the authorities to establish fuel consumption standards in the future.

Suggested Citation

  • Cui, Yuepeng & Zou, Fumin & Xu, Hao & Chen, Zhihui & Gong, Kuangmin, 2022. "A novel optimization-based method to develop representative driving cycle in various driving conditions," Energy, Elsevier, vol. 247(C).
    • Handle: RePEc:eee:energy:v:247:y:2022:i:c:s0360544222003589
    DOI: 10.1016/j.energy.2022.123455
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    1. Huo, Hong & Yao, Zhiliang & He, Kebin & Yu, Xin, 2011. "Fuel consumption rates of passenger cars in China: Labels versus real-world," Energy Policy, Elsevier, vol. 39(11), pages 7130-7135.
    2. 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.
    3. Wang, Jinghui & Rakha, Hesham A., 2016. "Fuel consumption model for conventional diesel buses," Applied Energy, Elsevier, vol. 170(C), pages 394-402.
    4. Chen, Zeyu & Zhang, Qing & Lu, Jiahuan & Bi, Jiangman, 2019. "Optimization-based method to develop practical driving cycle for application in electric vehicle power management: A case study in Shenyang, China," Energy, Elsevier, vol. 186(C).
    5. Cui, Yuepeng & Xu, Hao & Zou, Fumin & Chen, Zhihui & Gong, Kuangmin, 2021. "Optimization based method to develop representative driving cycle for real-world fuel consumption estimation," Energy, Elsevier, vol. 235(C).
    6. Greene, David L. & Khattak, Asad J. & Liu, Jun & Wang, Xin & Hopson, Janet L. & Goeltz, Richard, 2017. "What is the evidence concerning the gap between on-road and Environmental Protection Agency fuel economy ratings?," Transport Policy, Elsevier, vol. 53(C), pages 146-160.
    7. 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.
    8. Jie Lin & Debbie A. Niemeier, 2003. "Estimating Regional Air Quality Vehicle Emission Inventories: Constructing Robust Driving Cycles," Transportation Science, INFORMS, vol. 37(3), pages 330-346, August.
    9. Chang, Chia-Lin & Mai, Te-Ke & McAleer, Michael, 2019. "Establishing national carbon emission prices for China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 106(C), pages 1-16.
    10. Pavlovic, Jelica & Marotta, Alessandro & Ciuffo, Biagio, 2016. "CO2 emissions and energy demands of vehicles tested under the NEDC and the new WLTP type approval test procedures," Applied Energy, Elsevier, vol. 177(C), pages 661-670.
    11. Wang, Sinan & Chen, Kangda & Zhao, Fuquan & Hao, Han, 2019. "Technology pathways for complying with Corporate Average Fuel Consumption regulations up to 2030: A case study of China," Applied Energy, Elsevier, vol. 241(C), pages 257-277.
    12. Luin, Blaž & Petelin, Stojan & Al-Mansour, Fouad, 2019. "Microsimulation of electric vehicle energy consumption," Energy, Elsevier, vol. 174(C), pages 24-32.
    13. Zhang, Shaojun & Wu, Ye & Liu, Huan & Huang, Ruikun & Un, Puikei & Zhou, Yu & Fu, Lixin & Hao, Jiming, 2014. "Real-world fuel consumption and CO2 (carbon dioxide) emissions by driving conditions for light-duty passenger vehicles in China," Energy, Elsevier, vol. 69(C), pages 247-257.
    14. Ben Dror, Maya & Qin, Lanzhi & An, Feng, 2019. "The gap between certified and real-world passenger vehicle fuel consumption in China measured using a mobile phone application data," Energy Policy, Elsevier, vol. 128(C), pages 8-16.
    15. 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.
    16. Hongwen, He & Jinquan, Guo & Jiankun, Peng & Huachun, Tan & Chao, Sun, 2018. "Real-time global driving cycle construction and the application to economy driving pro system in plug-in hybrid electric vehicles," Energy, Elsevier, vol. 152(C), pages 95-107.
    17. 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.
    18. Ali Ashtari & Eric Bibeau & Soheil Shahidinejad, 2014. "Using Large Driving Record Samples and a Stochastic Approach for Real-World Driving Cycle Construction: Winnipeg Driving Cycle," Transportation Science, INFORMS, vol. 48(2), pages 170-183, May.
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