Efficient and reliable charging of lithium-ion batteries remains a critical challenge due to their sensitivity to overcharge and over-discharge, which can significantly reduce lifetime and safety. Traditional fast-charging techniques often rely on high current injection to achieve rapid charging, but require precise control to avoid damaging the cells. To address this challenge, intelligent control strategies have been increasingly explored. In this paper, a fuzzy-logic-based charging controller is developed to regulate the charging current according to the estimated State of Charge (SOC). The SOC is estimated using an Extended Kalman Filter (EKF), where a radial-basis function neural network (RBFNN) is employed to model the nonlinear battery dynamics. This hybrid approach enables accurate SOC tracking under dynamic operating conditions while maintaining computational efficiency. The proposed controller is implemented and experimentally validated on a lithium-ion battery with a capacity of 1.5 Ah, demonstrating high charging speed and robust performance with a good accuracy.