Selection of Electric Vehicles for the Needs of Sustainable Transport under Conditions of Uncertainty—A Comparative Study on Fuzzy MCDA Methods

All over the world, including Poland, authorities are taking steps to increase consumer interest in electric vehicles and sustainable transport as a way to reduce environmental pollution. For this reason, the electric vehicle market is dynamically and constantly developing, more and more modern vehi...

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Autor principal:	Paweł Ziemba
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	sustainable transport electric vehicles multi-criteria decision aid fuzzy set uncertainty Monte Carlo method Technology T
Acceso en línea:	https://doaj.org/article/9c218c0600bc4363ba77c1b0ee85d497
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spelling	oai:doaj.org-article:9c218c0600bc4363ba77c1b0ee85d4972021-11-25T17:28:45ZSelection of Electric Vehicles for the Needs of Sustainable Transport under Conditions of Uncertainty—A Comparative Study on Fuzzy MCDA Methods10.3390/en142277861996-1073https://doaj.org/article/9c218c0600bc4363ba77c1b0ee85d4972021-11-01T00:00:00Zhttps://www.mdpi.com/1996-1073/14/22/7786https://doaj.org/toc/1996-1073All over the world, including Poland, authorities are taking steps to increase consumer interest in electric vehicles and sustainable transport as a way to reduce environmental pollution. For this reason, the electric vehicle market is dynamically and constantly developing, more and more modern vehicles are introduced to it, and purchases are often subsidized by the government. The aim of the article is to analyse the A–C segments of the Polish electric vehicle market and to recommend the most attractive vehicle from the perspective of sustainable transport. The aim of the research was achieved with the use of three multi-criteria decision aid (MCDA) methods, which deal well with the uncertainty and imprecision of data that occur in the case of many different parameters of electric vehicles. In particular, the following methods were used: the fuzzy technique for order of preference by similarity to ideal solution (TOPSIS), the fuzzy simple additive weighting (SAW) method, and the new easy approach to fuzzy preference ranking organization method for enrichment evaluation II (NEAT F-PROMETHEE II). Electric vehicle rankings obtained using each method were compared and verified by stochastic analysis. The conducted analyses and comparisons allowed us to identify the most interesting electric vehicles, which currently appear to be the Volkswagen ID.3 Pro S and Nissan LEAF e+.Paweł ZiembaMDPI AGarticlesustainable transportelectric vehiclesmulti-criteria decision aidfuzzy setuncertaintyMonte Carlo methodTechnologyTENEnergies, Vol 14, Iss 7786, p 7786 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	sustainable transport electric vehicles multi-criteria decision aid fuzzy set uncertainty Monte Carlo method Technology T
spellingShingle	sustainable transport electric vehicles multi-criteria decision aid fuzzy set uncertainty Monte Carlo method Technology T Paweł Ziemba Selection of Electric Vehicles for the Needs of Sustainable Transport under Conditions of Uncertainty—A Comparative Study on Fuzzy MCDA Methods
description	All over the world, including Poland, authorities are taking steps to increase consumer interest in electric vehicles and sustainable transport as a way to reduce environmental pollution. For this reason, the electric vehicle market is dynamically and constantly developing, more and more modern vehicles are introduced to it, and purchases are often subsidized by the government. The aim of the article is to analyse the A–C segments of the Polish electric vehicle market and to recommend the most attractive vehicle from the perspective of sustainable transport. The aim of the research was achieved with the use of three multi-criteria decision aid (MCDA) methods, which deal well with the uncertainty and imprecision of data that occur in the case of many different parameters of electric vehicles. In particular, the following methods were used: the fuzzy technique for order of preference by similarity to ideal solution (TOPSIS), the fuzzy simple additive weighting (SAW) method, and the new easy approach to fuzzy preference ranking organization method for enrichment evaluation II (NEAT F-PROMETHEE II). Electric vehicle rankings obtained using each method were compared and verified by stochastic analysis. The conducted analyses and comparisons allowed us to identify the most interesting electric vehicles, which currently appear to be the Volkswagen ID.3 Pro S and Nissan LEAF e+.
format	article
author	Paweł Ziemba
author_facet	Paweł Ziemba
author_sort	Paweł Ziemba
title	Selection of Electric Vehicles for the Needs of Sustainable Transport under Conditions of Uncertainty—A Comparative Study on Fuzzy MCDA Methods
title_short	Selection of Electric Vehicles for the Needs of Sustainable Transport under Conditions of Uncertainty—A Comparative Study on Fuzzy MCDA Methods
title_full	Selection of Electric Vehicles for the Needs of Sustainable Transport under Conditions of Uncertainty—A Comparative Study on Fuzzy MCDA Methods
title_fullStr	Selection of Electric Vehicles for the Needs of Sustainable Transport under Conditions of Uncertainty—A Comparative Study on Fuzzy MCDA Methods
title_full_unstemmed	Selection of Electric Vehicles for the Needs of Sustainable Transport under Conditions of Uncertainty—A Comparative Study on Fuzzy MCDA Methods
title_sort	selection of electric vehicles for the needs of sustainable transport under conditions of uncertainty—a comparative study on fuzzy mcda methods
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/9c218c0600bc4363ba77c1b0ee85d497
work_keys_str_mv	AT pawełziemba selectionofelectricvehiclesfortheneedsofsustainabletransportunderconditionsofuncertaintyacomparativestudyonfuzzymcdamethods
_version_	1718412300404129792

Selection of Electric Vehicles for the Needs of Sustainable Transport under Conditions of Uncertainty—A Comparative Study on Fuzzy MCDA Methods

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