A Reliable Device Parameter Extraction Scheme for Physics-Based IGBT Models

Abstract

The physics-based IGBT models have been proved to be very effective in accurately simulating the voltage, current, and carrier dynamics. However, the biggest challenge for those promising models is lack of detailed IGBT device parameters, which chip manufacturers generally seldom reveal. To extract precise and robust device parameters, a novel parameter extraction scheme based on the particle swarm optimization (PSO) algorithm is proposed in this article. The state-of-the-art Fourier-series-based (FSB) IGBT model is used to ensure the accuracy of the parameter extraction scheme. In the proposed scheme, IGBT parameters are simultaneously extracted by IGBT static and dynamic characteristic curves to account for global interaction between all those IGBT parameters during parameter optimization. The experiment is carried out to verify the proposed parameter extraction scheme. It should be noteworthy that only an experimental switching waveform under an arbitrary operating condition is required to implement global searching for the optimal parameters by our proposed scheme. The output characteristic curves and the switching waveforms of the FSB model under different operating conditions using the proposed parameter extraction scheme are in good agreement with the experimental waveforms. Results confirm the effectiveness and usefulness of the obtained device parameters by the randomly selected operating condition. Finally, the global sensitivity analysis is introduced to further demonstrate the reliability of the proposed parameter extraction scheme.