基于物理信息神经网络的IPT系统多参数与线圈偏移联合估计

In inductive power transfer (IPT) systems, real-time perception of mutual inductance and load parameters is critical for regulating operating states and monitoring system conditions. This article proposes a physics-informed neural network (PINN)-based multiparameter joint identification method. By embedding physical constraints of impedance angle-mutual inductance-load relationships as domain know...