Politecnico di Torino (logo)

Forecast Model of Electric Vehicles' Diffusion In Brazil

Joao Guilherme Vidal Moraes Tibau

Forecast Model of Electric Vehicles' Diffusion In Brazil.

Rel. Paolo Claudio Priarone. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Gestionale (Engineering And Management), 2022

PDF (Tesi_di_laurea) - Tesi
Licenza: Creative Commons Attribution Non-commercial No Derivatives.

Download (4MB) | Preview

Sales of electric vehicles are increasing globally and there are at least five main factors driving it: fast changing market, technology evolution, emissions regulations, environmental pressure and decreasing costs. Brazil is experiencing changes in the automotive market, as electric and hybrids reached 1% of total sales for the first time in 2020, rapidly increasing to 1.6% in April, 2021. An adapted Bass Diffusion model with p and q value estimated via literature comparison was produced and applied considering a maximum market of forecasted 30% fleet share of xEVs in 2050 as the baseline. This standard scenario outputted a tipping point of 2030 and 2032 for optimistic and pessimistic cases, reaching market maturity at 2045 and 2048. Simulating different values of annual and purchase tax rates, the decrease in Total Cost of Ownership caused an increase in the final number of Adopters. Inputting a forecast equation for purchasing price evolution over time caused an extreme expansion of the pool of potential adopters. Government incentives' influence on results was studied by combining annual and purchase tax rate deductions, and increase in electric energy is aligned with existing literature. The model presented limitations mainly due to lack of data, nevertheless it provides a panorama on how fast EV technology will penetrate the Brazilian market and the opportunities and challenges it will bring to public and private sectors.

Relators: Paolo Claudio Priarone
Academic year: 2022/23
Publication type: Electronic
Number of Pages: 70
Corso di laurea: Corso di laurea magistrale in Ingegneria Gestionale (Engineering And Management)
Classe di laurea: New organization > Master science > LM-31 - MANAGEMENT ENGINEERING
Aziende collaboratrici: UNSPECIFIED
URI: http://webthesis.biblio.polito.it/id/eprint/25366
Modify record (reserved for operators) Modify record (reserved for operators)