A soft-computing robotic shift for a hybrid vehicle

In the present paper we present a control system of robotic shift in hybrid vehicles that utilizes fussy logic as well as optimization techniques (genetic algorithms) aimed at improving, with the automatic choice of the shifting, the objective-functions previously chosen (minimum consumption, suitable dynamic performances). Following the working out of a model in Simulink environment, which is suitable for the simulation of the behavior of a hybrid vehicle equipped with different shifts (manual, robotic, robotic fussy-logic) we carried out tests in a virtual lab and compared the results with those obtained with models previously built by others (CRF) that had been validated on real vehicles. The results of the simulations have shown, on the one hand, the validity of the robotic shift relative to the manual shift, and, on the other hand, the effectiveness of the application of soft-computing for the development of the robotic shift relative to a vehicle equipped with a traditional robotic shift, in which the logic of shifting is managed by static maps