This paper investigates the development of a maximum efficiency point tracking (MEPT) algorithm tailored for wireless charging systems in electric vehicles (EVs). With the growing emphasis on environmental sustainability, EVs are increasingly prevalent in the automotive industry. However, conventional wired charging methods face limitations such as cable entanglement and connector degradation, which hinder user convenience and system reliability. Wireless charging technology, based on electromagnetic induction and magnetic resonance, offers a promising alternative that is both safe and convenient. The central objective of this study is to enhance the efficiency of energy transfer in wireless charging systems. To achieve this, the paper provides a comprehensive review of efficiency tracking algorithms, ranging from early fixed-parameter strategies to advanced adaptive techniques such as sliding mode variable structure control and machine learning-based approaches. Additionally, the authors present a detailed model of the wireless charging system, encompassing its architecture, compensation topology, and impedance regulation circuit. Based on the derived efficiency expression, a mutual inductance estimation method is proposed, followed by the development of the MEPT algorithm. Simulation results demonstrate the algorithm’s capability to accurately track the maximum efficiency point under varying mutual inductance conditions, thereby facilitating more efficient and practical wireless charging solutions for EV applications.