Model-based temperature estimation of power electronics systems

This paper proposes a method for accurate temperature estimation of thermally-aware power electronics systems. The duality between electrical systems and thermal systems was considered for thermal modeling. High dimensional thermal models present a challenge for online estimation. Therefore, the complexity of the thermal network was reduced by applying a structure-preserving model order reduction technique. An optimal number and placement of temperature sensors were used in a Kalman filter to accurately estimate the dynamic spatial thermal behavior of the system. The optimal number of temperature sensors was found by comparing the actual values of the states obtained from the thermal model to the estimated values of the states obtained from the Kalman filter. The optimal placement of temperature sensors was found by maximizing the trace of the observability Gramian. Simulation and experimental results validate the approach on a prototype inverter.