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Blended Power Management Strategy Using Pattern Recognition for a Plug-in Hybrid Electric Vehicle

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Abstract

The dual power source of a plug-in hybrid electric vehicle (PHEV) requires a high level control strategy in order to establish a power split decision that will minimize fuel consumption while taking full advantage of the embedded source of electrical energy. Literature shows that the optimal control of the power split is greatly influenced by the future trip to be made and that blended strategies are more appropriate regarding battery usage throughout a trip. This paper proposes a blended strategy for a PHEV which uses a driving pattern recognition scheme that allows control adaptation in real-time regarding current driving conditions.

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Acknowledgments

The authors wish to thank the BRP Corporation and the Automotive Partnership Canada (APC) for supporting and funding this work.

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Authors and Affiliations

  1. Centre de Technologies Avancées, Université de Sherbrooke, Sherbrooke, Canada

    Nicolas Denis

  2. Département de Génie Électrique et Génie Informatique, Université de Sherbrooke, Sherbrooke, Canada

    Maxime R. Dubois & Renaud Dubé

  3. Département de Génie Mécanique, Université de Sherbrooke, Sherbrooke, Canada

    Alain Desrochers

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  1. Nicolas Denis
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  2. Maxime R. Dubois
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  3. Renaud Dubé
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  4. Alain Desrochers
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Correspondence to Nicolas Denis.

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Denis, N., Dubois, M.R., Dubé, R. et al. Blended Power Management Strategy Using Pattern Recognition for a Plug-in Hybrid Electric Vehicle. Int. J. ITS Res. 14, 101–114 (2016). https://doi.org/10.1007/s13177-014-0106-z

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  • DOI: https://doi.org/10.1007/s13177-014-0106-z

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