Intelligent control of new Static Converter Structures For Vehicular Applications

Abstract

This thesis aims to address the limited driving range and high costs of electric vehicles by developing a control strategy to extend their autonomy, especially in the Algerian context. The study focuses on the modeling and control of an electric vehicle containing an electric motor powered by two energy sources. The primary energy source consists in the fuel cell and the secondary source comprises the battery with static power converters (chopper and two-level voltage inverter). A simulation tests have been conducted on a PMSM to test the performance of the power management strategy with the use of a Z-source inverter. Another series of simulation tests have also been carried out on a permanent magnet DC motor controlled by PI control and genetic algorithm based optimized PI control with the use of a four-quadrant DC-DC converter. The latter was then exploited on an experimental realization of a four-quadrant DC-DC along with bidirectional DC-DC buck-boost converter in the propulsion chain of an electric vehicle based on a permanent magnet DC motor powered by a battery. The obtained performances show that the proposed system leads to a better energy management of an electric vehicle and exhibits ideal control in different operating conditions, mainly in nominal operation in the presence of a load torque and even in case of battery failure. The entire system was experimentally tested using two microcontrollers and the results were comprehensively analyzed and demonstrated to be highly satisfactory.