Riccardo Russo
HEV modelling in GT-Suite environment and control strategy design using Dynamic Programming and ECMS.
Rel. Ezio Spessa, Roberto Finesso, Alessia Musa, Federico Miretti. Politecnico di Torino, Corso di laurea magistrale in Automotive Engineering (Ingegneria Dell'Autoveicolo), 2021
Abstract
Today’s automotive industry is moving toward electrification to comply with the increasingly stringent emission limitations but also to succeed in a market more fuel saving-oriented, in a scenario like the depicted one, hybrid electric vehicles (HEVs) represent a suitable solution to satisfy all these new needs. HEVs allow to exploit benefits of electric vehicles without losing the advantages of conventional internal combustion engine ones, but electrification introduces a major level of complexity in first step design and calibration of the hybrid systems. Numerical simulation becomes then fundamental for designers to be able to estimate which could be the best solution, avoiding time-demanding and expensive experiments; the aim of this thesis work was the design and analysis of vehicle models for simulation, both backward and forward.
The work was divided mainly into two parts, in the first one a backward simulation campaign was carried out using an Optimal design tool, previously developed by other colleagues, based on Matlab code which run over a selected driving cycle different hybrid electric vehicles trying different configurations in terms of geometry and components size; data collected has been then postprocessed and a ranking in terms of emissions and fuel consumption was done for each configuration
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