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Research on innovative plug-in hybrid electric vehicle comprehensive energy consumption evaluation method based on statistic energy consumption.
Chen, Xinbo; Zhong, Jian; Sha, Feng; Zhong, Zaimin.
Afiliação
  • Chen X; School of Automotive Studies, 12476Tongji University, Shanghai, China.
  • Zhong J; School of Automotive Studies, 12476Tongji University, Shanghai, China.
  • Sha F; School of Automotive Studies, 12476Tongji University, Shanghai, China.
  • Zhong Z; School of Automotive Studies, 12476Tongji University, Shanghai, China.
Sci Prog ; 104(4): 368504211050284, 2021 Oct.
Article em En | MEDLINE | ID: mdl-34723673
ABSTRACT
The plug-in hybrid electric vehicle not only has the advantages of low emissions from electric vehicles, but also takes advantage of the high specific energy and high specific power of petroleum fuels, which can significantly improve the emissions and fuel economy of traditional vehicles. Studying its comprehensive energy consumption evaluation method is an important part of analyzing the economics of plug-in hybrid electric vehicles. This paper first puts forward the concept of statistical energy consumption and then proposes an innovative calculation method of plug-in hybrid electric vehicle energy consumption based on statistical energy consumption by referring to and analyzing the energy consumption test regulations of the United States, the European Union, and China. Given the two use case assumptions of charge depleting mode priority and charge sustaining mode only, considering the fuel consumption and the energy consumption that converts electrical energy consumption to fuel consumption, the probability density function of travel mileage distribution and energy consumption is derived. Finally, the interpretation and analysis of statistical energy consumption evaluation results are carried out.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article