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An on-line predictive energy management strategy for plug-in hybrid electric vehicles to counter the uncertain prediction of the driving cycle

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  • Chen, Zeyu
  • Xiong, Rui
  • Wang, Chun
  • Cao, Jiayi

Abstract

Predictive energy management could be implemented in real-time with a short period of future driving cycle prediction. However, the completely precise prediction of the future driving cycle remains quite difficult. Two areas of effort have been explored in this study. The first is the implementation of a dynamic-neighborhood particle swarm optimization algorithm in the local optimal energy management strategy of plug-in hybrid electric vehicles based on data from the prediction of the future driving cycle. Second, the influence of an imprecise driving cycle prediction is considered, and then an online correction algorithm is proposed based on the backup control strategy and a fuzzy logic controller. In addition to these efforts, a predictive energy management strategy with an online correction algorithm is finally proposed. Compared with the optimal heuristic method, the presented energy management strategy could reduce the energy by up to 9.7% if the prediction of the future driving cycle is precise. For the situation of imprecise prediction, the online correction algorithm could reduce the deviation from the actual optimal policy by up to 32.39%.

Suggested Citation

  • Chen, Zeyu & Xiong, Rui & Wang, Chun & Cao, Jiayi, 2017. "An on-line predictive energy management strategy for plug-in hybrid electric vehicles to counter the uncertain prediction of the driving cycle," Applied Energy, Elsevier, vol. 185(P2), pages 1663-1672.
    • Handle: RePEc:eee:appene:v:185:y:2017:i:p2:p:1663-1672
    DOI: 10.1016/j.apenergy.2016.01.071
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    References listed on IDEAS

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    1. Zhang, Shuo & Xiong, Rui & Zhang, Chengning, 2015. "Pontryagin’s Minimum Principle-based power management of a dual-motor-driven electric bus," Applied Energy, Elsevier, vol. 159(C), pages 370-380.
    2. 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.
    3. Torres, J.L. & Gonzalez, R. & Gimenez, A. & Lopez, J., 2014. "Energy management strategy for plug-in hybrid electric vehicles. A comparative study," Applied Energy, Elsevier, vol. 113(C), pages 816-824.
    4. Pérez, Laura V. & Pilotta, Elvio A., 2009. "Optimal power split in a hybrid electric vehicle using direct transcription of an optimal control problem," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(6), pages 1959-1970.
    5. Shabbir, Wassif & Evangelou, Simos A., 2014. "Real-time control strategy to maximize hybrid electric vehicle powertrain efficiency," Applied Energy, Elsevier, vol. 135(C), pages 512-522.
    6. 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.
    7. Wang, Jianhui & Liu, Cong & Ton, Dan & Zhou, Yan & Kim, Jinho & Vyas, Anantray, 2011. "Impact of plug-in hybrid electric vehicles on power systems with demand response and wind power," Energy Policy, Elsevier, vol. 39(7), pages 4016-4021, July.
    8. Sun, Fengchun & Xiong, Rui & He, Hongwen, 2016. "A systematic state-of-charge estimation framework for multi-cell battery pack in electric vehicles using bias correction technique," Applied Energy, Elsevier, vol. 162(C), pages 1399-1409.
    9. Green II, Robert C. & Wang, Lingfeng & Alam, Mansoor, 2011. "The impact of plug-in hybrid electric vehicles on distribution networks: A review and outlook," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(1), pages 544-553, January.
    10. Al-Alawi, Baha M. & Bradley, Thomas H., 2013. "Review of hybrid, plug-in hybrid, and electric vehicle market modeling Studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 190-203.
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