Observer-Based Online Parameter Identification of Series-Series Tuned Inductive Power Transfer System

Recently, many studies have investigated controller design methodologies for inductive power transfer (IPT) systems, relying on preidentified circuit parameters for determining controller gains. However, controllers based on such parameters are vulnerable to identification errors. Additionally, IPT systems exhibit unpredictable mutual inductances depending on coil alignments, necessitating a parameter identification process to enhance system reliability. This article proposes observer-based, online parameter identification methods for series-series tuned IPT (SS-IPT) systems. Self-inductances of transmitter and receiver coils, load resistance, and mutual inductance are identified using disturbance observers and rotating reference frame circuit models of the SS-IPT system. The proposed self-inductance and load resistance observers feature identification bandwidths of 500 Hz, whereas the mutual inductance observer has an estimation bandwidth of 50 Hz, concluding the parameter identification processes within 10 ms. Moreover, the proposed observers demonstrate robustness to initial parameter errors. Given their reliance on measured states and observers, the proposed parameter identification methods are suitable for dynamic IPT systems. The effectiveness of these observer-based parameter identification methods is assessed through a comparison of theoretical and simulated frequency responses, as well as simulated and experimental time-domain responses.