A novel approach for EV charging by combining multi-source inverter (MSI) with a probabilistic neural network (PNN) controller enhances power factor correction (PFC). A SEPIC-PFC converter is implemented, which is a crucial component that helps optimize the charging process and enhance the performance of EV battery system. The functionality of SEPIC-PFC converter is further improved through the incorporation of a proportional integral (PI) controller. By harnessing the energy storage capabilities of supercapacitors, this design mitigates stress on batteries, leading to prolonged battery life and reduced costs. To convert DC voltage to AC voltage and manage power flow, a MSI is employed in the system. Additionally, the MSI is equipped with a PNN controller tailored for EV battery applications. This controller effectively regulates state of charge limit of battery, contributing to the optimization of energy management. Bidirectional DC/DC conversion is facilitated by the integrated PNN controller, enabling enhanced battery charging and discharging. The performance and robustness of the proposed approach is demonstrated through comprehensive simulations conducted in MATLAB/Simulink. The results affirm the effectiveness of proposed control technique. Notably, the incorporation of sufficient training data for PNN controller models ensures accurate and highly precise estimation of SOC. This work underscores the potential of proposed method in achieving efficient and reliable battery charging for electric vehicles. The PNN controller provides fast training, better generalization, and high accuracy than the use of ANN controller, potential approach. It is strong for noise, gives deterministic output, and minimal hyperpieme setting is required.