Cascade ESO-Based Control for Power Converter of Dynamic Wireless EV Charging System Subject to Uncertainty and Sensor Noise

This article develops an advanced disturbance observer for power converters in dynamic wireless charging (DWC) systems of electric vehicles (EVs). DWC technology emerges as a potential solution to alleviate EVs’ range anxiety. However, each power converter within the DWC system encounters multisource uncertainties and high-frequency sensor noise in practical engineering applications. This article introduces an improved control approach based on the extended state observer (ESO) for power converters in DWC systems to enhance output regulation performance. Specifically, this study analyzes the complex disturbances and unknown uncertainties, integrating them into a lumped uncertainty model. A novel cascade architecture for ESO is devised to effectively estimate these uncertainties, followed by formulating a state error feedback control (SEFC) law using the estimated information. Subsequently, stability analyses verify the uniform boundedness of all state errors. Finally, simulation and experimental results demonstrate the efficacy of the designed control approach in enhancing the output regulation performance of power converters within DWC systems. Notably, this approach breaks the trade-off between control performance and noise immunity faced by conventional large-gain observer-based controllers without introducing additional control modules or sensors.