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Optimal comfortability control of hybrid electric powertrains in acceleration mode

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Abstract

This paper presents a control design approach for optimizing the comfortability of hybrid electric powertrains in acceleration mode. A parallel hybrid electric vehicle powertrain system with two motors and a single turbo-charged engine is considered. In acceleration mode, it is assumed that the desired acceleration rate cannot be satisfied by using the electrical motor individually. The first challenge is managing the combustion engine to assist power generation and power split such that the system satisfies comfortability, and the second challenge is modeling the comfortability (e.g., analytically describing the human feeling). This paper exploits a black-box module typically used in the automotive industry to quantitatively evaluate comfortability. A genetic algorithm is applied to find the optimum power split and gear schedule that can improve the comfortability evaluated by the module in acceleration mode. The simulation results conducted on a simulator with a practical background demonstrate the significance of the proposed design approach.

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Acknowledgements

The work of the third author was supported by National Natural Science Foundation of China (Grant No. 61973053). The authors would like to thank Toyota Motor Corporation, Japan, for technical support.

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Authors and Affiliations

  1. Department of Engineering and Applied Sciences, Sophia University, Tokyo, 102-8554, Japan

    Bo Zhang, Yahui Zhang & Tielong Shen

  2. College of Mechanical and Electronic Engineering, Dalian Minzu University, Dalian, 116600, China

    Jiangyan Zhang

Authors
  1. Bo Zhang
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  2. Yahui Zhang
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  3. Jiangyan Zhang
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  4. Tielong Shen
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Corresponding author

Correspondence to Bo Zhang.

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Zhang, B., Zhang, Y., Zhang, J. et al. Optimal comfortability control of hybrid electric powertrains in acceleration mode. Sci. China Inf. Sci. 64, 172201 (2021). https://doi.org/10.1007/s11432-020-2912-2

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  • DOI: https://doi.org/10.1007/s11432-020-2912-2

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