[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.


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    Title :

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


    Contributors:
    Zhongya MAO (author) / Yong WANG (author) / Lingxiao LI (author) / Zongyan WANG (author)


    Publication date :

    2024




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




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