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Robust energy management of plug-in hybrid electric bus considering the uncertainties of driving cycles and vehicle mass

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  • Shangguan, Jinyong
  • Guo, Hongqiang
  • Yue, Ming

Abstract

This paper proposes a robust energy management for plug-in hybrid electric buses (PHEBs) considering the uncertainties of driving cycles and vehicle mass. The goal is to improve the fuel economy of PHEB while weakening the sensitivity of Pontryagin’s minimum principle (PMP)-based energy management to driving conditions. Considering that the PMP can be controlled by constant, a robust co-state sequence of PMP is designed based on the Taguchi robust design, where the quality characteristic of fuel consumption is taken as smaller-the-better characteristic. Taking the sampled noise factors composed of driving cycles and stochastic vehicle mass into account, a reliable verification structure is constructed to verify the robustness of designed co-state sequence based on the Monte Carlo simulation. Combining the robust co-state sequence and charge sustaining control mode, a robust PMP control strategy is proposed for the optimal control of PHEB and the over-discharge protection of battery. The simulation results demonstrate that the proposed energy management strategy is effective, and is robust against the uncertainties. Compared with the rule-based energy management, the fuel economy can be averagely improved by 29.32%.

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  • 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).
    • Handle: RePEc:eee:energy:v:203:y:2020:i:c:s0360544220309439
    DOI: 10.1016/j.energy.2020.117836
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    References listed on IDEAS

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    5. Coppitters, Diederik & De Paepe, Ward & Contino, Francesco, 2020. "Robust design optimization and stochastic performance analysis of a grid-connected photovoltaic system with battery storage and hydrogen storage," Energy, Elsevier, vol. 213(C).
    6. 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).
    7. Penghui Qiang & Peng Wu & Tao Pan & Huaiquan Zang, 2022. "Real-Time Energy Management Strategy Based on Driving Conditions Using a Feature Fusion Extreme Learning Machine," Energies, MDPI, vol. 15(12), pages 1-22, June.
    8. Dapai Shi & Junjie Guo & Kangjie Liu & Qingling Cai & Zhenghong Wang & Xudong Qu, 2023. "Research on an Improved Rule-Based Energy Management Strategy Enlightened by the DP Optimization Results," Sustainability, MDPI, vol. 15(13), pages 1-13, July.
    9. Vamsi Krishna Reddy, Aala Kalananda & Venkata Lakshmi Narayana, Komanapalli, 2022. "Meta-heuristics optimization in electric vehicles -an extensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    10. García, Antonio & Monsalve-Serrano, Javier & Lago Sari, Rafael & Tripathi, Shashwat, 2022. "Pathways to achieve future CO2 emission reduction targets for bus transit networks," Energy, Elsevier, vol. 244(PB).

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