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Energy management of mild hybrid vehicles exploiting ADAS sensor information.
Rel. Andrea Tonoli, Sanjarbek Ruzimov. Politecnico di Torino, Corso di laurea magistrale in Automotive Engineering (Ingegneria Dell'Autoveicolo), 2021
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Abstract
Electric vehicles are viewed as the most effective ways of reducing emissions. They have a big issue of autonomy. Recovering kinetic and potential energy is an effective method to extend their driving range. The purpose of this thesis is to integrate the ADAS sensor information in the energy management system of a 48 mild hybrid to minimise fuel consumption. Previous researches have focused on developing connected and automated vehicle systems, mostly for safety reason. A case study is undertaken using data from a common hybrid commercial vehicle 2.3 l diesel. The proposed strategy and numerical analysis have been verified by the NEDC driving cycle under the MATLAB/Simulink software environment.
The simulator was already available in the LIM-Mechatronics Laboratory group of Politecnico di Torino
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