The paper mainly focuses on analyzing high-performance step-down DC to DC converter based on zero voltage switching with pulse width modulation technique for electric vehicles. In this paper, PI, fuzzy PI, and adaptive network-based fuzzy inference system (ANFIS)control methods are applied to the phase shift full-bridge (PSFB) zero voltage switching (ZVS) converter for auxiliary components in electric vehicles. The robust analysis of three control methods is compared by using the AC small-signal mathematical model. Traditional PI control uses specific mathematical equations with errors and derivatives. Fuzzy PI control utilizes fuzzy logic rules with linguistic variables such as high, medium, and low. ANFIS combines fuzzy logic and neural networks to capture both benefits. The three control designs' switching losses and load changes are analyzed and implemented with the MATLAB/SIMULINK Software platform. From the simulation results, traditional PI control works with 92% efficiency. Fuzzy PI control and ANFIS work with 93% efficiency at full load capacity.
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