IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v239y2022ipas0360544221022015.html
   My bibliography  Save this article

Modelling and experimental validation of an EV torque distribution strategy towards active safety and energy efficiency

Author

Listed:
  • Wei, Hongqian
  • Ai, Qiang
  • Zhao, Wenqiang
  • Zhang, Youtong

Abstract

Electric vehicles (EVs) have promisingly contributed to the decarbonization of the transportation sector. Torque distribution in energy management is vital to enhance EV safety and efficiency; however, its nonlinearity and real-time executability have not been extensively researched. This paper proposes an integrated torque distribution strategy that simultaneously considers vehicle security and dynamic power allocation. In the upper active safety layer, the yaw stability control and active front steering control are coupled to maintain vehicle stability. Additionally, a linear time-varying model predictive controller is developed to address the system nonlinearity and online executability problems. In the lower energy distribution layer, the motor efficiency and dynamic tire-slip power are simultaneously optimized to maintain EV energy conservation. Numerical simulations and hardware experiments are conducted in this study. The results demonstrate that the proposed integrated strategy is superior to other typical torque distribution strategies in terms of reducing the risk of emergent accidents. Moreover, the energy consumption of the powertrain is reduced by 13.4% and 14.2% under the steering and straight driving conditions, respectively. Overall, our study further promotes the practical application of EVs in the future automotive market and lays a solid foundation for intelligent torque distribution in autonomous EVs.

Suggested Citation

  • Wei, Hongqian & Ai, Qiang & Zhao, Wenqiang & Zhang, Youtong, 2022. "Modelling and experimental validation of an EV torque distribution strategy towards active safety and energy efficiency," Energy, Elsevier, vol. 239(PA).
  • Handle: RePEc:eee:energy:v:239:y:2022:i:pa:s0360544221022015
    DOI: 10.1016/j.energy.2021.121953
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544221022015
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2021.121953?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Deng, Huifan & Zhao, Youqun & Feng, Shilin & Wang, Qiuwei & Zhang, Chenxi & Lin, Fen, 2021. "Torque vectoring algorithm based on mechanical elastic electric wheels with consideration of the stability and economy," Energy, Elsevier, vol. 219(C).
    2. Wu, Yitao & Zhang, Yuanjian & Li, Guang & Shen, Jiangwei & Chen, Zheng & Liu, Yonggang, 2020. "A predictive energy management strategy for multi-mode plug-in hybrid electric vehicles based on multi neural networks," Energy, Elsevier, vol. 208(C).
    3. Guo, Ningyuan & Zhang, Xudong & Zou, Yuan & Guo, Lingxiong & Du, Guodong, 2021. "Real-time predictive energy management of plug-in hybrid electric vehicles for coordination of fuel economy and battery degradation," Energy, Elsevier, vol. 214(C).
    4. Li, Zhenhe & Khajepour, Amir & Song, Jinchun, 2019. "A comprehensive review of the key technologies for pure electric vehicles," Energy, Elsevier, vol. 182(C), pages 824-839.
    5. He, Hongwen & Wang, Chen & Jia, Hui & Cui, Xing, 2020. "An intelligent braking system composed single-pedal and multi-objective optimization neural network braking control strategies for electric vehicle," Applied Energy, Elsevier, vol. 259(C).
    6. Li, Tianyu & Liu, Huiying & Wang, Hui & Yao, Yongming, 2020. "Hierarchical predictive control-based economic energy management for fuel cell hybrid construction vehicles," Energy, Elsevier, vol. 198(C).
    7. Cao, Yangsen & Sha, Aimin & Liu, Zhuangzhuang & Luan, Bo & Li, Jiarong & Jiang, Wei, 2020. "Electric energy output model of a piezoelectric transducer for pavement application under vehicle load excitation," Energy, Elsevier, vol. 211(C).
    8. Han, Zhongliang & Xu, Nan & Chen, Hong & Huang, Yanjun & Zhao, Bin, 2018. "Energy-efficient control of electric vehicles based on linear quadratic regulator and phase plane analysis," Applied Energy, Elsevier, vol. 213(C), pages 639-657.
    9. Hu, Xiao & Wang, Ping & Hu, Yunfeng & Chen, Hong, 2020. "A stability-guaranteed and energy-conserving torque distribution strategy for electric vehicles under extreme conditions," Applied Energy, Elsevier, vol. 259(C).
    10. Zhou, Wei & Chen, Yaoqi & Zhai, Haoran & Zhang, Weigang, 2021. "Predictive energy management for a plug-in hybrid electric vehicle using driving profile segmentation and energy-based analytical SoC planning," Energy, Elsevier, vol. 220(C).
    11. Zhou, Jianhao & Xue, Siwu & Xue, Yuan & Liao, Yuhui & Liu, Jun & Zhao, Wanzhong, 2021. "A novel energy management strategy of hybrid electric vehicle via an improved TD3 deep reinforcement learning," Energy, Elsevier, vol. 224(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chen, Guanpeng & Jiang, Yue & Tang, Yuanjiang & Xu, Xiaojun, 2023. "Pitch stability control of variable wheelbase 6WID unmanned ground vehicle considering tire slip energy loss and energy-saving suspension control," Energy, Elsevier, vol. 264(C).
    2. Fan, Likang & Wang, Yufei & Wei, Hongqian & Zhang, Youtong & Zheng, Pengyu & Huang, Tianyi & Li, Wei, 2022. "A GA-based online real-time optimized energy management strategy for plug-in hybrid electric vehicles," Energy, Elsevier, vol. 241(C).
    3. Sun, Lingyun & Yin, Jiemin & Bilal, Ahmad Raza, 2023. "Green financing and wind power energy generation: Empirical insights from China," Renewable Energy, Elsevier, vol. 206(C), pages 820-827.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Deng, Huifan & Zhao, Youqun & Feng, Shilin & Wang, Qiuwei & Zhang, Chenxi & Lin, Fen, 2021. "Torque vectoring algorithm based on mechanical elastic electric wheels with consideration of the stability and economy," Energy, Elsevier, vol. 219(C).
    2. Wei, Hongqian & Zhang, Nan & Liang, Jun & Ai, Qiang & Zhao, Wenqiang & Huang, Tianyi & Zhang, Youtong, 2022. "Deep reinforcement learning based direct torque control strategy for distributed drive electric vehicles considering active safety and energy saving performance," Energy, Elsevier, vol. 238(PB).
    3. Liu, Yonggang & Wu, Yitao & Wang, Xiangyu & Li, Liang & Zhang, Yuanjian & Chen, Zheng, 2023. "Energy management for hybrid electric vehicles based on imitation reinforcement learning," Energy, Elsevier, vol. 263(PC).
    4. Sun, Wenjing & Zou, Yuan & Zhang, Xudong & Guo, Ningyuan & Zhang, Bin & Du, Guodong, 2022. "High robustness energy management strategy of hybrid electric vehicle based on improved soft actor-critic deep reinforcement learning," Energy, Elsevier, vol. 258(C).
    5. Iqbal, Mehroze & Laurent, Julien & Benmouna, Amel & Becherif, Mohamed & Ramadan, Haitham S. & Claude, Frederic, 2022. "Ageing-aware load following control for composite-cost optimal energy management of fuel cell hybrid electric vehicle," Energy, Elsevier, vol. 254(PA).
    6. Chen, Zheng & Gu, Hongji & Shen, Shiquan & Shen, Jiangwei, 2022. "Energy management strategy for power-split plug-in hybrid electric vehicle based on MPC and double Q-learning," Energy, Elsevier, vol. 245(C).
    7. Mokesioluwa Fanoro & Mladen Božanić & Saurabh Sinha, 2022. "A Review of the Impact of Battery Degradation on Energy Management Systems with a Special Emphasis on Electric Vehicles," Energies, MDPI, vol. 15(16), pages 1-29, August.
    8. Yang, Chao & Sun, Tonglin & Wang, Weida & Li, Ying & Zhang, Yuhang & Zha, Mingjun, 2024. "Regenerative braking system development and perspectives for electric vehicles: An overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 198(C).
    9. Dong, Peng & Zhao, Junwei & Liu, Xuewu & Wu, Jian & Xu, Xiangyang & Liu, Yanfang & Wang, Shuhan & Guo, Wei, 2022. "Practical application of energy management strategy for hybrid electric vehicles based on intelligent and connected technologies: Development stages, challenges, and future trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).
    10. Guo, Xiaokai & Yan, Xianguo & Chen, Zhi & Meng, Zhiyu, 2022. "Research on energy management strategy of heavy-duty fuel cell hybrid vehicles based on dueling-double-deep Q-network," Energy, Elsevier, vol. 260(C).
    11. Lin, Xinyou & Li, Yalong & Zhang, Guangji, 2022. "Bi-objective optimization strategy of energy consumption and shift shock based driving cycle-aware bias coefficients for a novel dual-motor electric vehicle," Energy, Elsevier, vol. 249(C).
    12. Zhang, Hao & Fan, Qinhao & Liu, Shang & Li, Shengbo Eben & Huang, Jin & Wang, Zhi, 2021. "Hierarchical energy management strategy for plug-in hybrid electric powertrain integrated with dual-mode combustion engine," Applied Energy, Elsevier, vol. 304(C).
    13. Guo, Ningyuan & Zhang, Wencan & Li, Junqiu & Chen, Zheng & Li, Jianwei & Sun, Chao, 2024. "Predictive energy management of fuel cell plug-in hybrid electric vehicles: A co-state boundaries-oriented PMP optimization approach," Applied Energy, Elsevier, vol. 362(C).
    14. Xu, Tao & Zhao, Youqun & Deng, Huifan & Guo, Shuo & Li, Danyang & Lin, Fen, 2023. "Integrated optimal control of distributed in-wheel motor drive electric vehicle in consideration of the stability and economy," Energy, Elsevier, vol. 282(C).
    15. Md. Sazal Miah & Molla Shahadat Hossain Lipu & Sheikh Tanzim Meraj & Kamrul Hasan & Shaheer Ansari & Taskin Jamal & Hasan Masrur & Rajvikram Madurai Elavarasan & Aini Hussain, 2021. "Optimized Energy Management Schemes for Electric Vehicle Applications: A Bibliometric Analysis towards Future Trends," Sustainability, MDPI, vol. 13(22), pages 1-38, November.
    16. İnci, Mustafa & Büyük, Mehmet & Demir, Mehmet Hakan & İlbey, Göktürk, 2021. "A review and research on fuel cell electric vehicles: Topologies, power electronic converters, energy management methods, technical challenges, marketing and future aspects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    17. Zhao, Li & Ke, Hanchen & Li, Yuqi & Chen, Yong, 2023. "Research on personalized charging strategy of electric bus under time-varying constraints," Energy, Elsevier, vol. 276(C).
    18. Ren, Xiaoxia & Ye, Jinze & Xie, Liping & Lin, Xinyou, 2024. "Battery longevity-conscious energy management predictive control strategy optimized by using deep reinforcement learning algorithm for a fuel cell hybrid electric vehicle," Energy, Elsevier, vol. 286(C).
    19. Zhou, Wei & Cai, Xuan & Chen, Yaoqi & Li, Junqiu & Peng, Xiaoyan, 2022. "Decoding the optimal charge depletion behavior in energy domain for predictive energy management of series plug-in hybrid electric vehicle," Applied Energy, Elsevier, vol. 316(C).
    20. Xie, Yunkun & Li, Yangyang & Zhao, Zhichao & Dong, Hao & Wang, Shuqian & Liu, Jingping & Guan, Jinhuan & Duan, Xiongbo, 2020. "Microsimulation of electric vehicle energy consumption and driving range," Applied Energy, Elsevier, vol. 267(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:239:y:2022:i:pa:s0360544221022015. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.