Improved method for automotive vibration level testing based on signal feature extraction

Abstract

In order to improve the precision and reliability of the objective evaluation of vehicle vibration, a multi-condition drivability test is designed based on the GB/T4970-2009 standard. The three-axis vibration and acceleration data in the speed range of 30–120 km/h are collected from urban roads, national highways, and motorways. Combined with the improved empirical modal decomposition (EMD) method, a vibration signal optimization strategy with dynamic frequency band adjustment and double threshold screening is proposed. The empirical modal decomposition algorithm solves the problem of modal aliasing, establishes a speed-based frequency band adjustment mechanism and a suspension intrinsic frequency model, and constructs a dual-threshold filtering mechanism with instantaneous frequency probability density (≥85%) and energy entropy criterion, which effectively separates the driver operation from the noise interference. Compared with various improvement methods, the EMD dynamic dual-threshold method has the best correction effect, and the correction error of the integrated weighted acceleration root mean square value is reduced to 0.191%. The method breaks through the severe limitations of the traditional test conditions and provides a highly robust analysis framework for vehicle vibration comfort evaluation.