Improving the Efficiency of Electric Rolling Stock Operation Through the Use of Adaptive Filtering Methods for High Harmonic Current Components in Traction Drive Systems

Abstract

The aim of this work is to investigate the efficiency of various adaptive filtering methods for higher harmonic components of stator currents in a vector-controlled traction drive system to improve the operation efficiency of electric rolling stock. The set goal was achieved by implementing an adaptive filtering block into the basic vector control system, which sequentially employs various adaptive filtering methods. The first harmonic component of stator currents was proposed to be used as the desired signal. An algorithm for determining the first harmonic component under conditions of varying supply voltage frequency was developed. Based on the simulation results, filtration efficiency metrics were established, indicating that the Wiener filter is the most effective for filtering higher harmonic components of stator currents. The most significant results include the algorithm for determining the first harmonic component of the stator phase current and the determination of an adaptive filtering algorithm with the highest convergence rate. The importance of these results lies in identifying the most effective adaptive filtering algorithm for traction drive operation, taking into account the operating modes of electric rolling stock. This will help reduce losses from higher harmonic components in the traction drive and, consequently, increase its energy efficiency.