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Active noise control systems have been gaining popularity in the last couple of decades, due to the deficiencies in passive noise abatement techniques. In the future, a novel combination of passive and active noise control techniques may be applied more widely, to better control the interior sound quality of vehicles. In order to maximize the effectiveness of this combined approach, smarter algorithms will be needed for active noise control systems. These algorithms will have to be computationally efficient, with high stability and convergence rates. This will be necessary in order to accurately predict and control the interior noise response of a vehicle. In this study, a critical review of the filtered-x least mean square (FXLMS) algorithm and several other newly proposed algorithms for the active control of vehicle powertrain noise, is performed. The analysis examines the salient features of each algorithm, and compares their system performance.

Gears are essential parts of many precision power and torque transmitting machines. However, the radiated intensive tonal noise due to the gear meshing is highly undesirable and annoying. In very severe cases, the gear vibrations can reduce the life and performance of the power transmitting components. Typical gearbox vibration and sound spectra contain several dominant narrowband tonal signals that are mixed in with a lower level broadband response signals. Hence, the control of mesh response of gearbox housing belongs to the problem of the rejection or cancellation of periodical disturbance. The frequencies of these tonal signals are related to the number of teeth and rotation speed, and highly predictable. Thus, a feedforward control system was normally adopted. In most of existed applications, an accurate reference based on the frequency information of tachometer pulse train signal is required for this kind of control system.

An enhanced, frequency domain filtered-x least mean square (LMS) algorithm is proposed as the basis for an active control system for treating powertrain noise. There are primarily three advantages of this approach: (i) saving of computing time especially for long controller’s filter length; (ii) more accurate estimation of the gradient due to the sample averaging of the whole data block; and (iii) capacity for rapid convergence when the adaptation parameter is correctly adjusted for each frequency bin. Unlike traditional active noise control techniques for suppressing response, the proposed frequency domain FXLMS algorithm is targeted at tuning vehicle interior response in order to achieve a desirable sound quality. The proposed control algorithm is studied numerically by applying the analysis to treat vehicle interior noise represented by either measured or predicted cavity acoustic transfer functions.