Harmonic Detection and Suppression Method for High-speed Maglev Trains Based on Adaline Algorithm

Abstract

[Objective] In order to reduce the impact of high-speed maglev harmonics on traction network, and to ensure the normal operation of high-speed maglev trains, it is necessary to study the harmonic characteristics of the high-speed maglev traction power suppl system, and the corresponding harmonic suppression methods. [Method] The composition of the high-speed maglev traction power supply system is studied, the dual three-phase half-controlled 12-pulse multiple rectifier circuit and its harmonics are theoretically analyzed and simulated. Based on the principle of the Adaline neural network algorithm and the harmonic characteristics of high-speed maglev trains, a high-speed maglev harmonic detection model based on Adaline is constructed. A harmonic compensation control strategy is used to generate compensating signal of current with equal magnitude but opposite direction to the detected harmonics, for harmonic suppression of the system distorted currents. [Result & Conclusion] Simulation results indicate that before adopting the harmonic detection and suppression method based on Adaline algorithm, the harmonic distortion rate is 11.16%. After applying this method, the content of each harmonic decreases significantly, and the harmonic distortion rate decreases to 1.41%. The research results demonstrate that the proposed harmonic detection and suppression method can effectively reduce harmonic distortion, thereby improving the stability and operational efficiency of the traction power supply system.

Keywords

• high-speed maglev
• harmonic detection and suppression
• adaline algorithm