An Adaptive Integrated Power Conversion System for Traction and Charging of Electric Vehicles

In recent decades, the rise in global warming and depletion of fossil fuels have accelerated the research in more environmentally friendly and sustainable means of mobility options. Electric vehicles (EVs) can significantly contribute to this with their potential to curtail fossil fuel usage and their exceptional flexible performance. This paper presents an adaptive integrated power conversion system (IPCS) that could replace the conventional requirement of separate power converters. The proposed system is made to operate for two modes of operation, during battery charging and for electric propulsion. This integrated system incorporates a dual active bridge (DAB) bidirectional dc-dc converter and a dc-ac voltage source inverter (VSI) cascaded together, which shares common power circuits. This system configuration helps in reducing the number of switches and bulk of the power conversion system in EVs. An artificial intelligence (AI) controller based on the artificial neural network (ANN) is incorporated for the speed control of the three-phase induction motor (IM) by constant V/f control for traction operation. The network training is performed using the backpropagation method and Levenberg–Marquardt (LM) algorithm. The system is validated using MATLAB Simulink and the results are presented for two modes of operation.