Research on Order Analysis Algorithm for Waviness of Electric Vehicle High-Speed Gear Transmission
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Abstract
With the rapid high-speed development of drive motors for electric vehicles, the operating speed of gearboxes has been significantly increased, and gear surface waviness has become a critical factor inducing transmission NVH problems. Aiming at the transmission howling and high-frequency vibration caused by the surface waviness of high-speed gears for electric vehicles, traditional waviness analysis algorithms have obvious deficiencies, including low order resolution, inability to identify ghost orders, and poor amplitude measurement accuracy. To solve the precision detection and quality control problems of high-speed transmission gears, this paper proposes a waviness order recognition algorithm combining Fourier transform and least-squares sinusoidal fitting. Experimental tests and comparative verification prove the engineering applicability of the proposed algorithm. The method effectively compensates for the shortcomings of traditional detection technology, and can provide theoretical basis and engineering support for waviness suppression, machining process optimization and NVH performance improvement of electric vehicle high-speed gear transmission systems.
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