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A novel energy management for hybrid off-road vehicles without future driving cycles as a priori

Author

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  • Wang, Hong
  • Huang, Yanjun
  • Khajepour, Amir
  • He, Hongwen
  • Cao, Dongpu

Abstract

Hybrid electric tracked bulldozers use engine and ultracapacitor as the power sources for propulsion, and the fuel economy performance highly depend on the coordination of all subsystems. In this paper, a model predictive controller is developed to reduce the fuel consumption of hybrid electric tracked bulldozers. As an optimization-based approach, the model predictive controller usually requires the drive profile to be known a priori. However, in this study, an average concept based model predictive controller is proposed without such knowledge. Simulation results show that a prescient model predictive controller saves approximately 21% more fuel compared to the conventional bulldozer and the average concept based model predictive controller performs similarly to the prescient model predictive controller. Meanwhile, the results of the two model predictive controllers are compared with dynamic programming and rule-based energy management strategy to show the benefit of model predictive controllers. In addition, the robustness of this average concept based model predictive controller is also verified under several disturbed drive cycles. The proposed model predictive controller is independent of powertrain topology such that it can be directly extended to other types of hybrid electric tracked bulldozers, and it provides a way to apply the model predictive controller even though future driving information is unavailable.

Suggested Citation

  • Wang, Hong & Huang, Yanjun & Khajepour, Amir & He, Hongwen & Cao, Dongpu, 2017. "A novel energy management for hybrid off-road vehicles without future driving cycles as a priori," Energy, Elsevier, vol. 133(C), pages 929-940.
    • Handle: RePEc:eee:energy:v:133:y:2017:i:c:p:929-940
    DOI: 10.1016/j.energy.2017.05.172
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    Cited by:

    1. Ju, Fei & Murgovski, Nikolce & Zhuang, Weichao & Hu, Xiaosong & Song, Ziyou & Wang, Liangmo, 2023. "Predictive energy management with engine switching control for hybrid electric vehicle via ADMM," Energy, Elsevier, vol. 263(PE).
    2. Pedrayes, Joaquín F. & Melero, Manuel G. & Cano, José M. & Norniella, Joaquín G. & Orcajo, Gonzalo A. & Cabanas, Manés F. & Rojas, Carlos H., 2019. "Optimization of supercapacitor sizing for high-fluctuating power applications by means of an internal-voltage-based method," Energy, Elsevier, vol. 183(C), pages 504-513.
    3. Li Zhai & Hong Huang & Steven Kavuma, 2017. "Investigation on a Power Coupling Steering System for Dual-Motor Drive Tracked Vehicles Based on Speed Control," Energies, MDPI, vol. 10(8), pages 1-17, August.
    4. 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.
    5. Baodi Zhang & Sheng Guo & Xin Zhang & Qicheng Xue & Lan Teng, 2020. "Adaptive Smoothing Power Following Control Strategy Based on an Optimal Efficiency Map for a Hybrid Electric Tracked Vehicle," Energies, MDPI, vol. 13(8), pages 1-25, April.
    6. Ju, Fei & Zhuang, Weichao & Wang, Liangmo & Zhang, Zhe, 2019. "Optimal sizing and adaptive energy management of a novel four-wheel-drive hybrid powertrain," Energy, Elsevier, vol. 187(C).
    7. Tri Cuong Do & Hoai Vu Anh Truong & Hoang Vu Dao & Cong Minh Ho & Xuan Dinh To & Tri Dung Dang & Kyoung Kwan Ahn, 2019. "Energy Management Strategy of a PEM Fuel Cell Excavator with a Supercapacitor/Battery Hybrid Power Source," Energies, MDPI, vol. 12(22), pages 1-24, November.
    8. 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).
    9. Huang, Yanjun & Wang, Hong & Khajepour, Amir & Li, Bin & Ji, Jie & Zhao, Kegang & Hu, Chuan, 2018. "A review of power management strategies and component sizing methods for hybrid vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 132-144.
    10. Hao, Yunxiao & Quan, Long & Cheng, Hang & Xia, Lianpeng & Ge, Lei & Zhao, Bin, 2018. "Potential energy directly conversion and utilization methods used for heavy duty lifting machinery," Energy, Elsevier, vol. 155(C), pages 242-251.
    11. Wei Zhang & Jixin Wang & Shaofeng Du & Hongfeng Ma & Wenjun Zhao & Haojie Li, 2019. "Energy Management Strategies for Hybrid Construction Machinery: Evolution, Classification, Comparison and Future Trends," Energies, MDPI, vol. 12(10), pages 1-26, May.
    12. Lei, Fei & Gu, Ke & Du, Bin & Xie, Xiaoping, 2017. "Comprehensive global optimization of an implicit constrained multi-physics system for electric vehicles with in-wheel motors," Energy, Elsevier, vol. 139(C), pages 523-534.
    13. Peng, Hui & Wang, Junzheng & Shen, Wei & Shi, Dawei & Huang, Yuan, 2019. "Compound control for energy management of the hybrid ultracapacitor-battery electric drive systems," Energy, Elsevier, vol. 175(C), pages 309-319.
    14. Ma, Fangwu & Yang, Yu & Wang, Jiawei & Liu, Zhenze & Li, Jinhang & Nie, Jiahong & Shen, Yucheng & Wu, Liang, 2019. "Predictive energy-saving optimization based on nonlinear model predictive control for cooperative connected vehicles platoon with V2V communication," Energy, Elsevier, vol. 189(C).
    15. Tian, He & Li, Shengbo Eben & Wang, Xu & Huang, Yong & Tian, Guangyu, 2018. "Data-driven hierarchical control for online energy management of plug-in hybrid electric city bus," Energy, Elsevier, vol. 142(C), pages 55-67.
    16. Wu, Jingda & He, Hongwen & Peng, Jiankun & Li, Yuecheng & Li, Zhanjiang, 2018. "Continuous reinforcement learning of energy management with deep Q network for a power split hybrid electric bus," Applied Energy, Elsevier, vol. 222(C), pages 799-811.
    17. Zhang, Wei & Wang, Jixin & Liu, Yong & Gao, Guangzong & Liang, Siwen & Ma, Hongfeng, 2020. "Reinforcement learning-based intelligent energy management architecture for hybrid construction machinery," Applied Energy, Elsevier, vol. 275(C).
    18. Hong Huang & Li Zhai & Zeda Wang, 2018. "A Power Coupling System for Electric Tracked Vehicles during High-Speed Steering with Optimization-Based Torque Distribution Control," Energies, MDPI, vol. 11(6), pages 1-17, June.

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