Using Hybrid MCDM Methods to Assess Fuel Cell Technology for the Next Generation of Hybrid Power Automobiles

Author:

Huang Chi-Yo, ,Hung Yi-Hsuan,Tzeng Gwo-Hshiung, ,

Abstract

With their huge consumption of petroleum and creation of a large number of pollutants, traditional vehicles have become one of the major creators of pollution in the world. To save energy and reduce carbon dioxide emissions, in recent years national governments have aggressively planned and promoted energy-saving vehicles that use green energy. Thus, hybrid electric vehicles have already become the frontrunners for future vehicles while fuel cells are considered the most suitable energy storage devices for future hybrid electric vehicles. However, various competing fuel cell technologies do exist. Furthermore, very few scholars have tried to investigate how the development of future fuel cells for hybrid electric vehicles can be assessed so that the results can serve as a foundation for the next generation of hybrid electric vehicle developments. Thus, how to assess various fuel cells is one the most critical issues in the designing of hybrid electric vehicles. This research intends to adopt a framework based on Hybrid Multiple-Criteria Decision Making (MCDM) for the assessment of the development in fuel cells for future hybrid electric vehicles. The analytic framework can be used for selecting the most suitable fuel cell technology for future hybrid electric vehicles. The results of the analysis can also be used for designing the next generation of hybrid electric vehicles.

Publisher

Fuji Technology Press Ltd.

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Human-Computer Interaction

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