Journal of Next Generation Technology
An International Open Access multi-disciplinary Journal in Science, Technology, and Sustainability
e-ISSN : 2583-021X
PSO-Based Optimal PI Controller Tuning for Two-Stage EV Battery Charger Using High-Gain Buck-Boost PFC Converter
Electric vehicle charger, bridgeless buck-boost converter, power factor correction, isolated Cuk converter, Particle Swarm Optimization, PI controller tuning, harmonic reduction
Abstract
The rapid growth of electric vehicle adoption has increased the demand for efficient, compact, and intelligent onboard charging systems. Conventional battery chargers suffer from poor power factor, high total harmonic distortion (THD), reduced efficiency, and complex control implementation under varying operating conditions. This paper presents a two-stage electric vehicle battery charger employing a bridgeless high-gain buck-boost power factor correction (PFC) AC-DC converter at the front-end and an isolated Cuk DC-DC converter at the back-end. The front-end converter operates in discontinuous conduction mode (DCM) to achieve inherent power factor correction with simplified control architecture and reduced sensor requirement. The isolated Cuk converter performs constant current and constant voltage battery charging with reduced ripple and galvanic isolation. Mathematical modelling of the converter stages is carried out using volt-second balance and state-space analysis. To improve the dynamic response of the charger, Particle Swarm Optimization (PSO) based optimal PI controller tuning is implemented for DC-link voltage regulation and charging control loops. The proposed charger is validated in MATLAB/Simulink under steady-state and dynamic operating conditions. Simulation results demonstrate near unity power factor operation, reduced source current THD, stable DC-link voltage regulation, improved transient response, and enhanced charger efficiency. Comparative analysis confirms that the PSO optimized controller significantly improves harmonic performance, settling time, overshoot, and efficiency compared to conventional PI controllers.
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