4.7 Article

A uni fi ed quantitative analysis of fuel economy for hybrid electric vehicles based on energy fl ow

Journal

JOURNAL OF CLEANER PRODUCTION
Volume 292, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2021.126040

Keywords

Hybrid electric vehicles; Fuel consumption; Theoretical quantitative analysis; Average comprehensive transmission; efficiency; Fuel-saving contribution rate

Funding

  1. National Key Research and Development Program of China [2018YFB0105900]

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This paper focuses on analyzing the impact of energy-saving factors on fuel consumption for hybrid electric vehicles, introducing the concepts of average comprehensive transmission efficiency and fuel-saving contribution rate. The comparison between theoretical and simulation models shows remarkable consistency.
Analyzing the impact of energy-saving factors on fuel consumption for hybrid electric vehicles (HEVs) is essential to revealing their inherent energy-saving mechanisms, and it is a significant reference for exploring the energy-saving potential and the direction of optimization calibration. This paper focuses on a unified quantitative exploration of the factors affecting the fuel economy. First, the coupling characteristics in energy conversion and losses are investigated based on energy flows, and a concept of average comprehensive transmission efficiency (ACTE) is defined. Second, a novel theoretical fuel consumption model is developed and the fuel-saving contribution rate (FSCR) is proposed, achieving the purpose of decoupling analysis of the fundamental fuel consumption impact factor. Finally, to verify the analysis method proposed in this paper, the results are compared between simulation and theoretical calculations on three typical hybrid electric buses, including parallel, series/parallel, and power-split HEVs. The comparison results demonstrate that the developed theoretical model has remarkable consistency with the simulation model. Furthermore, specific analyses of different impact factors are conducted, quantitatively deepening the understanding of factors affecting fuel economy and quickly facilitating the future economic performance prediction of new-generation HEVs. (c) 2021 Elsevier Ltd. All rights reserved.

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