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• W3164811905 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. The work would be focused on studying the control system and its optimisation. In this perspective, the knowledge of a short-range horizon such as that coming from the ADAS sensors has contributed to optimising the e-powertrain components' usage to start the regenerative braking in a condition that allows recovering all possible energy. These results provided evidence of more EM power contribution before the deceleration with a total reduction of 7,52% of fuel consumption. It can be concluded from the results that a good control strategy supported by ADAS technology aims to handle the energy management problem for a hybrid vehicle. A further extension of this work could incorporate future traffic conditions into the long forecast horizon." @default.
• W3164811905 created "2021-06-07" @default.
• W3164811905 creator A5012597691 @default.
• W3164811905 date "2021-03-31" @default.
• W3164811905 modified "2023-09-27" @default.
• W3164811905 title "Energy management of mild hybrid vehicles exploiting ADAS sensor information" @default.
• W3164811905 hasPublicationYear "2021" @default.
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