Extended Kalman Filter Based State and Parameter Estimation Method for a Buck Converter Operating in a Wide Load Range

The vast majority of buck converter modeling and control studies rely on the assumption that load resistance operates near a nominal value. Accordingly, controller and estimator designs in literature are mainly centered around the assumed nominal load resistance. In this paper, we approach the problem from a different perspective. We propose an hybrid Extended Kalman Filter (EKF) based state, parameter (load resistance), and operation mode estimator for the buck converter topology. The proposed estimation procedure can operate in both Continuous Conduction Mode (CCM) and Discontinuous Conduction Mode (DCM). Through extensive modeling and simulation studies, we show that the algorithm can predict the operation mode effectively and estimate the states and unknown load resistance accurately. We believe that our state and parameter estimation approach can guide the development of more robust and high-performance voltage control policies for the buck converter and other DC/DC converter topologies.