A Capacitance Estimation Method for DC-Link Capacitors Based on Pre-Charging Model and Noise Evaluation

DC-link capacitor is one of the significant parts of traction converters. Due to the impact of electrical stress, high temperature and humidity, its capacitance degrades faster than expected. Accurate capacitance estimation is critical to the condition monitoring of DC-link capacitors, which is also the basis of online capacitor life prediction. Currently, there is a big challenge for capacitor capacitance estimation in railway applications. The noise fluctuation of the voltage sensor may be nearly equal to that of ripple voltage, leading to the considerable errors of the existing capacitor condition monitoring methods. Therefore, a capacitance estimation method based on precharging model and noise evaluation is proposed in this article. The capacitance is estimated by improved recursive extended least square. The influence of the noise can be effectively reduced and both the calculation accuracy and convergence speed can be well guaranteed through an independent noise estimation model. The proposed method has good immunity in a certain range of signal-noise ratio or signal bias. It shows good performance in experiments.