A unified quantitative analysis of fuel economy for hybrid electric vehicles based on energy flow. (10th April 2021)

• Record Type: Journal Article
• Authors: Zeng, Xiaohua; Qian, Qifeng; Chen, Hongxu; Song, Dafeng; Li, Guanghan
• Is Part Of: Journal of cleaner production. Volume 292(2021)
• Publication Date: 2021-04-10
• Subjects: Hybrid electric vehicles -- Fuel consumption -- Theoretical quantitative analysis -- Average comprehensive transmission efficiency -- Fuel-saving contribution rate; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2021.126040
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: 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.