Design and Analysis of New Bidirectional Conductive Charger for Electric Vehicle Application

Abstract

As environmental pollution has profound impacts on both the environment and newlinepeople, it has become a major global concern in the modern age. Transportation newlineand industry are collaborating to address several of issues, including the depletion newlineof fossil fuels, the expense of fuel, and the long-term advantages of environmentally newlinefriendly technology. As Electric Vehicle (EV)s gain popularity, it is anticipated newlinethat the transportation and electric utilities sectors will become more integrated. newlineOn Board Charger (OBC) are being used in EVs more and more because of their newlinedesign and installation related cost effectiveness. Bidirectional power ow is also newlinegaining traction in the automotive industry due to EVs capacity to feed energy newlineback into the grid. Dual Active Bridge (DAB) widely adopted for OBCs and other applications because of the key abilities: Zero Voltage Switching (ZVS), power transfer bidirectional and wide voltage gain ratio. Although DAB has numerous significant advantages, its non-linear behavior necessitates the use of complex control strategies. One of the main challenges of control and modulation systems is achieving stability and efficiency under uncertainties. In this thesis the main objective is to propose an enhanced PI controller focussing over improved transient performance by minimising performance indices such as Integral Absolute Error (IAE), Integral Square Error (ISE), Integral Time Absolute Error (ITAE). They provide insight into how well the controller is minimising error and ensuring system stability. Among these indices, by minimising ITAE, the controller is incentivized to quickly correct errors early in the response, reducing long-term errors and settling time. This results in a faster, more stable system that reaches its desired voltage level efficiently. Various controllers like Fractional Order PI (FOPI), Tilt-Integral Derivative (TID), Fuzzy logic based PI (PIFLC) and Adaptive Neuro Fuzzy Inference (ANFIS-PI) and Harris Hawk Optimisation (HHO-PI) based control schemes are studied...