| Popis: |
As a key component of traction converter, DC-link capacitor plays a key role in stabilizing DC side voltage. However, when a DC-link capacitor is exposed to high temperature and high pressure for a long time, its equivalent series resistance(ESR) will gradually increase, and the capacitor will gradually fail to meet the functional requirements, thus affecting the reliability of the converter. Adopting different maintenance strategies according to the health state of capacitors can improve the safety and maintainability of a traction system. This paper proposes a parameter identification method based on the pre-charging process for traction converter. An identification model of the DC-link capacitor is established based on the equivalent circuit of DC-link capacitor, and voltage and current signals in the pre-charging process are used to estimate parameter. In order to improve the reliability of the estimation, different from the traditional parameter identification algorithm based on gradient descent, the genetic algorithm is used to search for the optimal value in the range of health parameter and estimate the real parameter. Simulation under different noise conditions and physical experiments by performing the pre-charging process of the traction converter were carried out, and both the identification errors were less than 3%. The effectiveness of the proposed method is verified by simulation and physical experiments. |
