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Energy active adjustment and bidirectional transfer management strategy of the electro-hydrostatic hydraulic hybrid powertrain for battery bus

Author

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  • Liu, Huanlong
  • Chen, Guanpeng
  • Li, Dafa
  • Wang, Jiawei
  • Zhou, Jianyi

Abstract

The electro-hydrostatic hydraulic hybrid (EH3) powertrain has unique advantages in efficient recovery and utilization of energy. However, it also faces severe challenges in the decision-making of active adjustment and bidirectional transfer between multiple energy sources under the influence of driving pattern. Taking battery buses as the object, the power and energy-saving characteristics of EH3 powertrain under the control of driving pattern recognition (DPR) and fuzzy logic rules (FLR) are studied in this paper. The control ideas of active adjustment and bidirectional transfer of electric power and hydraulic power guided by the results of DPR are proposed. Firstly, the driving patterns and velocity in the actual driving scene is tested, and the data is divided into multiple short driving cycles through a rolling time window. Secondly, the K-means clustering algorithm is used to classify the obtained short driving cycles. The classification results are used as samples to train and test the Learning Vector Quantization neural network (LVQ-NN) to realize online recognition and prediction of driving patterns. Finally, the FLR controller is introduced to process multiple input variables, and the results of DPR and FLR are integrated to realize the active adjustment and bidirectional transfer of electric motor (EM) and variable pump/motor. The simulation results show that compared with the traditional control strategies, energy management strategy (EMS) based on DPR and FLR can effectively realize the intelligent adjustment and transfer of energy between composite power sources, and significantly improve the driving range and service life of the battery.

Suggested Citation

  • Liu, Huanlong & Chen, Guanpeng & Li, Dafa & Wang, Jiawei & Zhou, Jianyi, 2021. "Energy active adjustment and bidirectional transfer management strategy of the electro-hydrostatic hydraulic hybrid powertrain for battery bus," Energy, Elsevier, vol. 230(C).
    • Handle: RePEc:eee:energy:v:230:y:2021:i:c:s0360544221010422
    DOI: 10.1016/j.energy.2021.120794
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    References listed on IDEAS

    as
    1. Chen, Zeyu & Xiong, Rui & Cao, Jiayi, 2016. "Particle swarm optimization-based optimal power management of plug-in hybrid electric vehicles considering uncertain driving conditions," Energy, Elsevier, vol. 96(C), pages 197-208.
    2. Duhr, Pol & Christodoulou, Grigorios & Balerna, Camillo & Salazar, Mauro & Cerofolini, Alberto & Onder, Christopher H., 2021. "Time-optimal gearshift and energy management strategies for a hybrid electric race car," Applied Energy, Elsevier, vol. 282(PA).
    3. Shangguan, Jinyong & Guo, Hongqiang & Yue, Ming, 2020. "Robust energy management of plug-in hybrid electric bus considering the uncertainties of driving cycles and vehicle mass," Energy, Elsevier, vol. 203(C).
    4. Geng, Wenran & Lou, Diming & Wang, Chen & Zhang, Tong, 2020. "A cascaded energy management optimization method of multimode power-split hybrid electric vehicles," Energy, Elsevier, vol. 199(C).
    5. Guo, Qiuyi & Zhao, Zhiguo & Shen, Peihong & Zhan, Xiaowen & Li, Jingwei, 2019. "Adaptive optimal control based on driving style recognition for plug-in hybrid electric vehicle," Energy, Elsevier, vol. 186(C).
    6. Yu, Huilong & Tarsitano, Davide & Hu, Xiaosong & Cheli, Federico, 2016. "Real time energy management strategy for a fast charging electric urban bus powered by hybrid energy storage system," Energy, Elsevier, vol. 112(C), pages 322-331.
    7. Zhou, Quan & Li, Ji & Shuai, Bin & Williams, Huw & He, Yinglong & Li, Ziyang & Xu, Hongming & Yan, Fuwu, 2019. "Multi-step reinforcement learning for model-free predictive energy management of an electrified off-highway vehicle," Applied Energy, Elsevier, vol. 255(C).
    8. Wang, Feng & Zhang, Jian & Xu, Xing & Cai, Yingfeng & Zhou, Zhiguang & Sun, Xiaoqiang, 2019. "A comprehensive dynamic efficiency-enhanced energy management strategy for plug-in hybrid electric vehicles," Applied Energy, Elsevier, vol. 247(C), pages 657-669.
    9. Boyle, James & Littler, Timothy & Foley, Aoife, 2020. "Battery energy storage system state-of-charge management to ensure availability of frequency regulating services from wind farms," Renewable Energy, Elsevier, vol. 160(C), pages 1119-1135.
    10. Tian, Xiang & Cai, Yingfeng & Sun, Xiaodong & Zhu, Zhen & Xu, Yiqiang, 2019. "An adaptive ECMS with driving style recognition for energy optimization of parallel hybrid electric buses," Energy, Elsevier, vol. 189(C).
    11. Wang, Yue & Zeng, Xiaohua & Song, Dafeng & Yang, Nannan, 2019. "Optimal rule design methodology for energy management strategy of a power-split hybrid electric bus," Energy, Elsevier, vol. 185(C), pages 1086-1099.
    12. Liu, Huanlong & Chen, Guanpeng & Xie, Chixin & Li, Dafa & Wang, Jiawei & Li, Shun, 2020. "Research on energy-saving characteristics of battery-powered electric-hydrostatic hydraulic hybrid rail vehicles," Energy, Elsevier, vol. 205(C).
    13. Han, Xuefeng & He, Hongwen & Wu, Jingda & Peng, Jiankun & Li, Yuecheng, 2019. "Energy management based on reinforcement learning with double deep Q-learning for a hybrid electric tracked vehicle," Applied Energy, Elsevier, vol. 254(C).
    14. Wang, Yujie & Sun, Zhendong & Li, Xiyun & Yang, Xiaoyu & Chen, Zonghai, 2019. "A comparative study of power allocation strategies used in fuel cell and ultracapacitor hybrid systems," Energy, Elsevier, vol. 189(C).
    15. Du, Guodong & Zou, Yuan & Zhang, Xudong & Kong, Zehui & Wu, Jinlong & He, Dingbo, 2019. "Intelligent energy management for hybrid electric tracked vehicles using online reinforcement learning," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    16. Wang, Yue & Zeng, Xiaohua & Song, Dafeng, 2020. "Hierarchical optimal intelligent energy management strategy for a power-split hybrid electric bus based on driving information," Energy, Elsevier, vol. 199(C).
    17. Ruan, Jiageng & Song, Qiang & Yang, Weiwei, 2019. "The application of hybrid energy storage system with electrified continuously variable transmission in battery electric vehicle," Energy, Elsevier, vol. 183(C), pages 315-330.
    18. Song, Ziyou & Hou, Jun & Xu, Shaobing & Ouyang, Minggao & Li, Jianqiu, 2017. "The influence of driving cycle characteristics on the integrated optimization of hybrid energy storage system for electric city buses," Energy, Elsevier, vol. 135(C), pages 91-100.
    19. Khairy Sayed & Ahmed Kassem & Hedra Saleeb & Ali S. Alghamdi & Ahmed G. Abo-Khalil, 2020. "Energy-Saving of Battery Electric Vehicle Powertrain and Efficiency Improvement during Different Standard Driving Cycles," Sustainability, MDPI, vol. 12(24), pages 1-26, December.
    20. Zhou, Yang & Ravey, Alexandre & Péra, Marie-Cecile, 2020. "Multi-mode predictive energy management for fuel cell hybrid electric vehicles using Markov driving pattern recognizer," Applied Energy, Elsevier, vol. 258(C).
    21. Yang, Jibin & Xu, Xiaohui & Peng, Yiqiang & Zhang, Jiye & Song, Pengyun, 2019. "Modeling and optimal energy management strategy for a catenary-battery-ultracapacitor based hybrid tramway," Energy, Elsevier, vol. 183(C), pages 1123-1135.
    22. Hu, Jie & Liu, Di & Du, Changqing & Yan, Fuwu & Lv, Chen, 2020. "Intelligent energy management strategy of hybrid energy storage system for electric vehicle based on driving pattern recognition," Energy, Elsevier, vol. 198(C).
    23. Zhang, Fengqi & Hu, Xiaosong & Langari, Reza & Wang, Lihua & Cui, Yahui & Pang, Hui, 2021. "Adaptive energy management in automated hybrid electric vehicles with flexible torque request," Energy, Elsevier, vol. 214(C).
    24. Wu, Yuankai & Tan, Huachun & Peng, Jiankun & Zhang, Hailong & He, Hongwen, 2019. "Deep reinforcement learning of energy management with continuous control strategy and traffic information for a series-parallel plug-in hybrid electric bus," Applied Energy, Elsevier, vol. 247(C), pages 454-466.
    25. Yu, Wei & Wang, Ruochen, 2019. "Development and performance evaluation of a comprehensive automotive energy recovery system with a refined energy management strategy," Energy, Elsevier, vol. 189(C).
    26. Li, Yuecheng & He, Hongwen & Khajepour, Amir & Wang, Hong & Peng, Jiankun, 2019. "Energy management for a power-split hybrid electric bus via deep reinforcement learning with terrain information," Applied Energy, Elsevier, vol. 255(C).
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