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Development of a Multi-Architecture and Multi-Application Hybrid Vehicle Design and Management Tool

Author

Listed:
  • Shiyu Gan

    (DRIVE EA 1859, Univ. Bourgogne Franche Comté, F58027 Nevers, France)

  • Daniela Chrenko

    (Femto-ST, UMR 6174, CNRS, Univ. Bourgogne Franche-Comte, F90010 Belfort, France)

  • Alan Kéromnès

    (DRIVE EA 1859, Univ. Bourgogne Franche Comté, F58027 Nevers, France)

  • Luis Le Moyne

    (DRIVE EA 1859, Univ. Bourgogne Franche Comté, F58027 Nevers, France)

Abstract

Hybrid electric vehicles (HEVs) are very promising sustainable mobility solutions. Series, parallel and series-parallel (SP) seem to be three most promising architectures among the multitude of hybrid architectures, and it is possible to find them in a multi-applications such as the motorcycles, family-cars, hybrid city busses and sport cars. It is import to have a well configured model in order to develop the different control strategies (CsTs) for each application. Therefore, a multi-architecture/multi-application (MAMA) approach capable of identifying the most energy efficient hybrid architecture considering both the dimensions of key components: electric motor (EM), battery, internal combustion engine (ICE) and the optimal control is presented. Basis of the model is the energetic macroscopic representation (EMR), which has been combined with object oriented programming (OOP) in order to enhance its modularity and reuse capabilities. The obtained results show, that different hybrid architectures are most adapted for different applications. Moreover, the robustness of the results using real time control algorithms are studied, showing that CsT matters. The obtained results contribute to simplify and harmonize the design of hybrid solutions for multiple applications.

Suggested Citation

  • Shiyu Gan & Daniela Chrenko & Alan Kéromnès & Luis Le Moyne, 2018. "Development of a Multi-Architecture and Multi-Application Hybrid Vehicle Design and Management Tool," Energies, MDPI, vol. 11(11), pages 1-19, November.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:11:p:3185-:d:183400
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    References listed on IDEAS

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    1. Zhang, Pei & Yan, Fuwu & Du, Changqing, 2015. "A comprehensive analysis of energy management strategies for hybrid electric vehicles based on bibliometrics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 88-104.
    2. Finesso, Roberto & Spessa, Ezio & Venditti, Mattia, 2014. "Layout design and energetic analysis of a complex diesel parallel hybrid electric vehicle," Applied Energy, Elsevier, vol. 134(C), pages 573-588.
    3. Cipek, Mihael & Pavković, Danijel & Petrić, Joško, 2013. "A control-oriented simulation model of a power-split hybrid electric vehicle," Applied Energy, Elsevier, vol. 101(C), pages 121-133.
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    1. García, Antonio & Monsalve-Serrano, Javier & Martinez-Boggio, Santiago & Gaillard, Patrick, 2021. "Impact of the hybrid electric architecture on the performance and emissions of a delivery truck with a dual-fuel RCCI engine," Applied Energy, Elsevier, vol. 301(C).
    2. García, Antonio & Carlucci, Paolo & Monsalve-Serrano, Javier & Valletta, Andrea & Martínez-Boggio, Santiago, 2021. "Energy management optimization for a power-split hybrid in a dual-mode RCCI-CDC engine," Applied Energy, Elsevier, vol. 302(C).
    3. Javier Solano & Diego Jimenez & Adrian Ilinca, 2020. "A Modular Simulation Testbed for Energy Management in AC/DC Microgrids," Energies, MDPI, vol. 13(16), pages 1-23, August.

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