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Evaluation of a Modified Equivalent Fuel-Consumption Minimization Strategy Considering Engine Start Frequency and Battery Parameters for a Plugin Hybrid Two-Wheeler

Author

Listed:
  • Naga Kavitha Kommuri

    (WMG, University of Warwick, Coventry CV4 7AL, UK)

  • Andrew McGordon

    (WMG, University of Warwick, Coventry CV4 7AL, UK)

  • Antony Allen

    (WMG, University of Warwick, Coventry CV4 7AL, UK)

  • Dinh Quang Truong

    (WMG, University of Warwick, Coventry CV4 7AL, UK)

Abstract

An appropriate energy management strategy is essential to enhance the performance of hybrid electric vehicles. A novel modified equivalent fuel-consumption minimization strategy (ECMS) is developed considering the engine operating point deviation from the optimum operating line. This paper focuses on an all-inclusive evaluation of this modified ECMS with other state-of-art energy management strategies concerning battery ageing, engine switching along with fuel economy and charge sustenance. The simulation-based results of a hybrid two-wheeler concept are analysed, which shows that the modified ECMS offers the highest benefit compared to rule-based controllers concerning fuel economy and reduction in engine switching events. However, the improvement in fuel economy using modified ECMS has significant negative potential effects on critical battery parameters influencing battery ageing. The results are analysed and found consistent for two different drive cycles and three different powertrain component configurations. The results show a significant reduction in fuel consumption of up to 21.18% and a reduction in engine switching events of up to 55% with modified ECMS when compared with rule-based strategies. However, there is a significant increase in battery temperature by 31% and battery throughput by 378%, which plays a major role in accelerating battery ageing. This paper emphasizes the need to consider battery-ageing parameters along with other control objectives for a robust assessment of energy management strategies. This study helps in laying down a foundation for future improvements in energy management development and it also aids in establishing a basis for comparing energy management controllers.

Suggested Citation

  • Naga Kavitha Kommuri & Andrew McGordon & Antony Allen & Dinh Quang Truong, 2020. "Evaluation of a Modified Equivalent Fuel-Consumption Minimization Strategy Considering Engine Start Frequency and Battery Parameters for a Plugin Hybrid Two-Wheeler," Energies, MDPI, vol. 13(12), pages 1-26, June.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:12:p:3122-:d:372344
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    References listed on IDEAS

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    1. Dian Wang & Yun Bao & Jianjun Shi, 2017. "Online Lithium-Ion Battery Internal Resistance Measurement Application in State-of-Charge Estimation Using the Extended Kalman Filter," Energies, MDPI, vol. 10(9), pages 1-11, August.
    2. Yuping Zeng & Yang Cai & Guiyue Kou & Wei Gao & Datong Qin, 2018. "Energy Management for Plug-In Hybrid Electric Vehicle Based on Adaptive Simplified-ECMS," Sustainability, MDPI, vol. 10(6), pages 1-24, June.
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    Citations

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    Cited by:

    1. Chen, Zhihang & Liu, Yonggang & Zhang, Yuanjian & Lei, Zhenzhen & Chen, Zheng & Li, Guang, 2022. "A neural network-based ECMS for optimized energy management of plug-in hybrid electric vehicles," Energy, Elsevier, vol. 243(C).
    2. Chen, Z. & Liu, Y. & Ye, M. & Zhang, Y. & Chen, Z. & Li, G., 2021. "A survey on key techniques and development perspectives of equivalent consumption minimisation strategy for hybrid electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    3. Xueliang Li & Xinyu Kang & Xin Ba & Zengxiong Peng & Shujun Yang & Zhifu Zhao, 2022. "A Design Methodology for Dual-Mode Electro-Mechanical Transmission Scheme Based on Jointing Characteristics," Energies, MDPI, vol. 15(15), pages 1-15, July.
    4. Naga Kavitha Kommuri & Andrew McGordon & Antony Allen & Dinh Quang Truong, 2022. "A Novel Adaptive Equivalence Fuel Consumption Minimisation Strategy for a Hybrid Electric Two-Wheeler," Energies, MDPI, vol. 15(9), pages 1-19, April.

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