A Multi-Parameter Joint Identification Method for IPT Systems Based on Particle Swarm Optimization

In wireless power transfer systems, to achieve communication-free control on output, the front-end typically estimates unknown parameters such as mutual inductance and load parameters by monitoring the electrical features on the primary side in real-time. However, manufacturing variations and component aging can cause parameter drift in the secondary-side compensating components, which affects the accuracy of real-time parameter estimation. To address this issue, an offline identification of the secondary-side compensating component parameters is required before system operation. Therefore, a multi-parameter joint offline identification method is proposed. First, the basic conditions for multi-parameter identification are analyzed, then a joint identification model is developed, and finally the particle swarm optimization algorithm is then used to estimate seven unknown parameters, including mutual inductance, load, and secondary-side compensating components. Simulation result verified that the proposed method can accurately estimate all unknown parameters in the system. However, the identification process is time-consuming and is thus only applicable for offline identification.