Case study of financial leasing model driven by fuzzy logic control for alternative fuel vehicles operation

Junlin Zhu; Hua Wang; Lin Miao; Zitong Yu; Junlin Zhu; Hua Wang; Lin Miao; Zitong Yu

doi:10.3934/mbe.2023041

Mathematical Biosciences and Engineering

2023, Volume 20, Issue 1: 894-912. doi: 10.3934/mbe.2023041

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Research article

Case study of financial leasing model driven by fuzzy logic control for alternative fuel vehicles operation

1.
School of Metallurgy and Energy Engineering, Kunming University of Science and Technology, China
2.
Yunneng Financial Leasing (Shanghai) Co., Ltd., Shanghai, China

Academic Editor: Hao Wang

Received: 10 August 2022 Revised: 26 September 2022 Accepted: 27 September 2022 Published: 18 October 2022

Over the past decade, the alternative fuel vehicle industry in the world has sprung up with huge speed. For example, the annual output has increased from less than 2000 vehicles to now 3,500,000 vehicles in China. It enjoys more than 50% of the market share worldwide in the global market. A spurt of progress in the alternative fuel vehicle industry has built a foundation for carbon peaking and carbon neutrality goals. Financial leasing has unique advantages which not only can provide guarantees for this industry in many aspects concerning related equipment, systems and infrastructures but also offer financial support for green projects. Nevertheless, financial leasing firms are encountering a string of problems to solve, such as selecting optimal green projects and cooperative businesses, designing transaction structures, and controlling project risks. This study contains several main sections: connecting the incremental alternative fuel vehicle investment and purchase project of a leading regional enterprise; building the structure of the financial leasing project; and analyzing the project leasing property using a fuzzy logic model, the financial structure and the repayment capacity of the project main company so as to comprehensively evaluate the feasibility of the project. This paper aims to provide a reference for future financing of alternative fuel vehicle operation enterprises with a real case study. The case study results show that our introduced fuzzy logic method can obtain the satisfying performance and traffic allocation.
- alternative fuel vehicles,
- financial leasing,
- feasibility study,
- fuzzy logic control
Citation: Junlin Zhu, Hua Wang, Lin Miao, Zitong Yu. Case study of financial leasing model driven by fuzzy logic control for alternative fuel vehicles operation[J]. Mathematical Biosciences and Engineering, 2023, 20(1): 894-912. doi: 10.3934/mbe.2023041

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Abstract

Over the past decade, the alternative fuel vehicle industry in the world has sprung up with huge speed. For example, the annual output has increased from less than 2000 vehicles to now 3,500,000 vehicles in China. It enjoys more than 50% of the market share worldwide in the global market. A spurt of progress in the alternative fuel vehicle industry has built a foundation for carbon peaking and carbon neutrality goals. Financial leasing has unique advantages which not only can provide guarantees for this industry in many aspects concerning related equipment, systems and infrastructures but also offer financial support for green projects. Nevertheless, financial leasing firms are encountering a string of problems to solve, such as selecting optimal green projects and cooperative businesses, designing transaction structures, and controlling project risks. This study contains several main sections: connecting the incremental alternative fuel vehicle investment and purchase project of a leading regional enterprise; building the structure of the financial leasing project; and analyzing the project leasing property using a fuzzy logic model, the financial structure and the repayment capacity of the project main company so as to comprehensively evaluate the feasibility of the project. This paper aims to provide a reference for future financing of alternative fuel vehicle operation enterprises with a real case study. The case study results show that our introduced fuzzy logic method can obtain the satisfying performance and traffic allocation.

References

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