Optimized maximum power point tracking for PV fed hybrid DC-DC converter-based BLDC motor driven electric vehicles

Bridging Photovoltaic (PV) energy generation with Electric Vehicle (EV) technology is an essential development in the modern quest for energy sustainability and advanced transportation methods. Consequently, this research focuses on enhancing efficient power utilization in PV-based EVs through the application of a novel Modified Boost-Luo DC-DC converter and a Chaotic Genetic Algorithm -based Maximum Power Point Tracking system. The Modified Boost-Luo converter provides a high voltage conversion ratio by incorporating a Voltage Multiplier Cell (VMC) and Three-Winding Coupled Inductor (3WCL) into its circuit configuration. The augmented PV output from Modified Boost-Luo converter is directed to the Brushless DC (BLDC) motor of the EV through a three-phase Voltage Source Inverter (3ΦVSI). Moreover, speed regulation in the BLDC motor is achieved using a Proportional–Integral (PI) controller. A distinctive feature of the proposed system involves the storage of surplus PV-generated power in a battery, interconnected to the DC-link via a bidirectional converter. In instances of PV power unavailability, the BLDC motor seamlessly taps into the stored energy in the battery for continued operation. The proposed approach is evaluated through both MATLAB simulation and laboratory prototype implementation, showcasing its potential to advance EV technology.