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Predictive Model for Battery Electric Vehicles (BEVs) market shares: an application to the future diffusion in the European 5 major Markets

Gabriele Pollicino

Predictive Model for Battery Electric Vehicles (BEVs) market shares: an application to the future diffusion in the European 5 major Markets.

Rel. Anna Corinna Cagliano, Paolo Mario Coeli, Salvatore Letizia. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Gestionale, 2023

Abstract:

The following document aims to address one of the most relevant and current challenges in the field of sustainable mobility that is the prediction of future market shares of Battery Electric Vehicles (BEVs). The thesis work focuses on the design of two models that can support the company “Stellantis” in the difficult activity of estimating the future market shares of BEVs which, today even more than before want and must, due to increasingly stringent regulations, gain market share thus confronting traditional Internal Combustion Engine Vehicles (ICEV). The paper offers a comprehensive analysis of current conditions in the automotive sector with a focus on the five major European countries, which are the area of the study. Thus, consumer characteristics that are found to be different among the five countries are analyzed with a detailed vision of the transition to sustainable mobility for each. The first proposed model is based on research and detailed analysis of socio-economic parameters that impact BEV diffusion. Using historical data and trends for each country, this approach provides insight into how variables such as per capita income, availability of charging infrastructure, and government policies influence the transition to electric vehicles. Through a study of these parameters, carried out through research and in-depth analysis, future trends for each are obtained, and through these, using a nonlinear regression model, it is possible to obtain the trend of future BEV market shares in the five largest European countries. Then a second model, based on the output obtained from the first predictive model, is proposed to forecast future trends in BEVs in each country with detail also by segment, thus body type and size, and by price class. It proves valuable and useful because it allows a specific automotive brand to analyze the current and future situation in its target market, defined by the segment and price positioning of the vehicles it produces. Together, these two models can be a comprehensive tool for policy makers, automotive industries and all those stakeholders interested in planning and developing sustainable mobility strategies. The work done demonstrates the importance of a multidimensional, data-driven approach to understanding and predicting the evolution of the BEV market, thus helping to promote a transition to a more sustainable, low-carbon future in the European automotive industry.

Relatori: Anna Corinna Cagliano, Paolo Mario Coeli, Salvatore Letizia
Anno accademico: 2023/24
Tipo di pubblicazione: Elettronica
Numero di pagine: 134
Informazioni aggiuntive: Tesi secretata. Fulltext non presente
Soggetti:
Corso di laurea: Corso di laurea magistrale in Ingegneria Gestionale
Classe di laurea: Nuovo ordinamento > Laurea magistrale > LM-31 - INGEGNERIA GESTIONALE
Aziende collaboratrici: STELLANTIS EUROPE SPA
URI: http://webthesis.biblio.polito.it/id/eprint/28304
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