Delayless partial subband update algorithm for feed-forward active road noise control system in pure electric vehicles

Abstract

Road noise is one of the dominant noise sources in pure electric vehicles. Active control for road noise is an attractive solution since this technique is suitable for controlling low-frequency noise. Feed-forward active road noise control (ARNC) systems utilize lots of reference signals and corresponding adaptive filters, and the control performance usually improves as the number of reference signals increases. To reduce the computational cost of ARNC systems so that more reference signals can be processed, we introduce the delayless subband structure into ARNC system and a delayless partial update subband with weighted reference signal normalized filtered-x least mean square (DPUS-WRS-NFxLMS) algorithm is proposed in this paper. Based on the traditional delayless subband algorithm, a partial subband update strategy is proposed to reduce the computational cost. Furthermore, the weighted reference signal is introduced for each subband filter. In this way, a modified vector is designed to assign different weights to different reference signal samples so that the convergence performance can be improved and the round-off error can be reduced. In addition, an adjustment strategy for the step size and reference signal weights is designed to make the algorithm have a better balance between the convergence rate and steady-state behavior. Finally, a purely time-delayed secondary path is constructed as the estimated secondary path to avoid the negative impact of the magnitude-frequency characteristics of the actual secondary path. The simulation results prove that the proposed algorithm achieves better control results than the traditional algorithms with lower computational complexity.