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Energy management and emission control for range extended electric vehicles

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  • Wang, Yaxin
  • Lou, Diming
  • Xu, Ning
  • Fang, Liang
  • Tan, Piqiang

Abstract

Range extended electric vehicles (REEVs), transition vehicles between combustion engine vehicles and electric vehicles, have been widely used due to their advantages of low fuel consumption and low emissions. By optimizing power management and after-treatment system control strategies, it is possible to achieve lower fuel consumption and emissions. This study proposes an integrated control method based on optimization strategies for the auxiliary power unit (APU) on/off system and energy management optimization for extended hybrid electric vehicles. The Elitist Nondominated Sorting Genetic Algorithm (NSGA-II) optimization method is used to determine the control parameters. In addition, considering the frequent start and stop characteristics of the APU caused by the optimization strategy, closed-loop control of the urea injection is established to solve the ammonia leakage problem. Due to their high computational efficiency, the proposed energy management and urea injection algorithms can be easily implemented in real time. The actual operating emissions of engines under the different strategies are tested on a semi-physical simulation platform, focusing on the analysis and comparison of NOx emissions. The conclusion has certain reference significance for vehicle production.

Suggested Citation

  • Wang, Yaxin & Lou, Diming & Xu, Ning & Fang, Liang & Tan, Piqiang, 2021. "Energy management and emission control for range extended electric vehicles," Energy, Elsevier, vol. 236(C).
    • Handle: RePEc:eee:energy:v:236:y:2021:i:c:s0360544221016182
    DOI: 10.1016/j.energy.2021.121370
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    References listed on IDEAS

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    1. Song, Ziyou & Li, Jianqiu & Hou, Jun & Hofmann, Heath & Ouyang, Minggao & Du, Jiuyu, 2018. "The battery-supercapacitor hybrid energy storage system in electric vehicle applications: A case study," Energy, Elsevier, vol. 154(C), pages 433-441.
    2. Lian, Renzong & Peng, Jiankun & Wu, Yuankai & Tan, Huachun & Zhang, Hailong, 2020. "Rule-interposing deep reinforcement learning based energy management strategy for power-split hybrid electric vehicle," Energy, Elsevier, vol. 197(C).
    3. García, Antonio & Carlucci, Paolo & Monsalve-Serrano, Javier & Valletta, Andrea & Martínez-Boggio, Santiago, 2020. "Energy management strategies comparison for a parallel full hybrid electric vehicle using Reactivity Controlled Compression Ignition combustion," Applied Energy, Elsevier, vol. 272(C).
    4. Li, Junqiu & Wang, Yihe & Chen, Jianwen & Zhang, Xiaopeng, 2017. "Study on energy management strategy and dynamic modeling for auxiliary power units in range-extended electric vehicles," Applied Energy, Elsevier, vol. 194(C), pages 363-375.
    5. Li, Xunming & Han, Lijin & Liu, Hui & Wang, Weida & Xiang, Changle, 2019. "Real-time optimal energy management strategy for a dual-mode power-split hybrid electric vehicle based on an explicit model predictive control algorithm," Energy, Elsevier, vol. 172(C), pages 1161-1178.
    6. Yuan Qiao & Yizhou Song & Kaisheng Huang, 2019. "A Novel Control Algorithm Design for Hybrid Electric Vehicles Considering Energy Consumption and Emission Performance," Energies, MDPI, vol. 12(14), pages 1-28, July.
    7. Peng, Jiankun & He, Hongwen & Xiong, Rui, 2017. "Rule based energy management strategy for a series–parallel plug-in hybrid electric bus optimized by dynamic programming," Applied Energy, Elsevier, vol. 185(P2), pages 1633-1643.
    8. Song, Ziyou & Hofmann, Heath & Li, Jianqiu & Hou, Jun & Han, Xuebing & Ouyang, Minggao, 2014. "Energy management strategies comparison for electric vehicles with hybrid energy storage system," Applied Energy, Elsevier, vol. 134(C), pages 321-331.
    9. Shabbir, Wassif & Evangelou, Simos A., 2019. "Threshold-changing control strategy for series hybrid electric vehicles," Applied Energy, Elsevier, vol. 235(C), pages 761-775.
    10. Mohagheghi Fard, Soheil & Khajepour, Amir, 2016. "An optimal power management system for a regenerative auxiliary power system for delivery refrigerator trucks," Applied Energy, Elsevier, vol. 169(C), pages 748-756.
    11. Chen, Syuan-Yi & Hung, Yi-Hsuan & Wu, Chien-Hsun & Huang, Siang-Ting, 2015. "Optimal energy management of a hybrid electric powertrain system using improved particle swarm optimization," Applied Energy, Elsevier, vol. 160(C), pages 132-145.
    12. Du, Jiuyu & Chen, Jingfu & Song, Ziyou & Gao, Mingming & Ouyang, Minggao, 2017. "Design method of a power management strategy for variable battery capacities range-extended electric vehicles to improve energy efficiency and cost-effectiveness," Energy, Elsevier, vol. 121(C), pages 32-42.
    13. Chen, Bo-Chiuan & Wu, Yuh-Yih & Tsai, Hsien-Chi, 2014. "Design and analysis of power management strategy for range extended electric vehicle using dynamic programming," Applied Energy, Elsevier, vol. 113(C), pages 1764-1774.
    14. Xu, Bin & Rathod, Dhruvang & Zhang, Darui & Yebi, Adamu & Zhang, Xueyu & Li, Xiaoya & Filipi, Zoran, 2020. "Parametric study on reinforcement learning optimized energy management strategy for a hybrid electric vehicle," Applied Energy, Elsevier, vol. 259(C).
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    2. Omkar Parkar & Benjamin Snyder & Adibuzzaman Rahi & Sohel Anwar, 2023. "Modified Particle Swarm Optimization Based Powertrain Energy Management for Range Extended Electric Vehicle," Energies, MDPI, vol. 16(13), pages 1-21, June.
    3. Diming Lou & Yinghua Zhao & Liang Fang & Yuanzhi Tang & Caihua Zhuang, 2022. "Encoder–Decoder-Based Velocity Prediction Modelling for Passenger Vehicles Coupled with Driving Pattern Recognition," Sustainability, MDPI, vol. 14(17), pages 1-21, August.
    4. Dongwei Yao & Xinwei Lu & Xiangyun Chao & Yongguang Zhang & Junhao Shen & Fanlong Zeng & Ziyan Zhang & Feng Wu, 2023. "Adaptive Equivalent Fuel Consumption Minimization Based Energy Management Strategy for Extended-Range Electric Vehicle," Sustainability, MDPI, vol. 15(5), pages 1-18, March.

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