Intelligent control of integrated on-board charger with improved power quality and reduced charging transients.

This paper proposes an intelligent control scheme for a two-stage integrated onboard electric vehicle (EV) battery charger connected to a single-phase household outlet which offers a close to ideal battery charging profile with power factor correction feature. Generally, the front-end AC-DC​ conversion stage is controlled by dual loop proportional-integral (PI) controllers, and tuning their gain constants is a difficult task. Furthermore, to achieve a close to ideal charging profile for an EV battery, the DC-DC conversion stage switches from constant current (CC) and constant voltage (CV) mode after a certain state of charge (SOC) which may lead to discontinuity in the charging current and voltage. This paper attempts to solve these issues by proposing an intelligent control scheme that includes the dynamic estimation of PI controller gain constants as well as provides a seamless mode transfer feature for battery charging. It is achieved by using fuzzy-PI-based control in the AC-DC conversion stage and Bayesian Regularization (BR) algorithm trained artificial neural network (ANN)-based control in the DC-DC conversion stage. The performance of the proposed control scheme is assessed both in steady-state and transient conditions in MATLAB® Simulink environment by comparing it against similar control schemes. The proposed intelligent control approach improves the dynamic response of DC link voltage, offers unity power factor operation and maintains the line current harmonics within IEEE 519 standards even during the switchover from CC to CV charging mode. Also, there is a decrease of 85% in the third harmonic component of the source current, 23.2% improvement in DC link voltage undershoot and 6.5% reduction in DC link voltage overshoot with reduced settling times using the proposed unified control scheme.