Francesco Nicola Mangieri
Development of a Lithium-ion battery predictive model for electrified powertrains.
Rel. Federico Millo, Luciano Rolando. Politecnico di Torino, Corso di laurea magistrale in Automotive Engineering (Ingegneria Dell'Autoveicolo), 2023
Abstract
Battery electric vehicles (BEVs), represent one of the valuable solutions to shift toward more sustainable mobility thanks to their high efficiency and to the possibility of using renewable energy for battery recharge. As a result, their market share has been growing in the last few years, with reference to the transportation of goods as well as people. Nevertheless, one of the major challenges for BEVs is still to ensure a sufficient range, allowing them to travel ever longer routes with a single recharge. In this sense, the creation of a reliable model is of primary importance to optimize the battery pack and to simulate its performance also in extreme ambient conditions.
In such a framework, this master thesis, realized in collaboration with FPT Industrial S.p.A., has the purpose of creating, in the commercial software GT-AutoLion, the electrochemical model of a Li-Ion battery pack
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