Research on ANE Algorithm for Sound Quality Control of Vehicle Interior Noise

Abstract

To Improve the weakness of the traditional active noise control system was not able to optionally control different frequency band noises and was easy to be disturbed by random disturbance, this paper proposed an adaptive active sound quality control(AASQC) method which used the active noise equalization(ANE) theory and FELMS algorithm as a kernel. The AASQC method can effectively solve the problem of disturbance in transmission bands by introducing and adjusting gain coefficient to implement the controllable cancellation of noises. Under Matlab/Simulink software environment, the AASQC algorithm was compared with the traditional adaptive active noise control algorithm FXLMS. The simulation results showed that the AASQC algorithm described above was of good stability and robustness in active sound quality control, and sound quality could be improved remarkably.

Sound Quality Control Based on CEEMD Blind Source Separation and FELMS Algorithm

“…Occasionally, sounds with a higher SPL are more pleasant than ones with a lower SPL. Based on such a phenomenon, researchers have put forward the concept of sound quality and psychological parameters [6,7]. Jiang et al summarized seven algorithms of sound quality control and application scenarios [8], and a machine learning algorithm was applied to the sound quality control [9][10][11][12][13].…”

Multiple target sound quality balance for hybrid electric powertrain noise

“…The relationship between the physical parameters of technical sounds and the auditory perception is also currently one of the spotlights of the automotive industry [22]. The possibility for tailoring the residual powertrain noise to provide the driver and passengers with relevant auditory information on the operation regime of the vehicle [23][24][25][26][27], or even for enhancing customer perceptions [28,29] of, e.g. vehicle quality, powerfulness, sportiveness, luxury, reliability quietness, among others [30], also enables the manufacturers to boost their products with unique and distinctive sound marks [31][32][33][34][35][36].…”

“…In particular, the noise emitted by hybrid electric powertrains, which is structure borne and measured at a number of relevant locations in the vehicle cabin, is tackled through an innovative multichannel distributed algorithm that delivers independent-zone active sound profiling [49]. Contrary to current active noise equalization (ANE) [24,25,[27][28][29] and active sound quality control (ASQC) strategies [26,32,33,36,39,50,51], where the improvement of the soundscape comes as a mere e↵ect of applying a few operation modes, e.g. cancellation, reduction, or amplification, the proposed methodology features a multi-objective optimization stage, which provides the NVH specialist with a variety of optimal solutions, given in terms of amplitude levels that should be attained in the sound, so as to provide the passengers with the exact, desired SQ levels.…”

Sound quality driven active control of periodic disturbance for hybrid vehicles

“…The relationship between the physical parameters of technical sounds and the human auditory perception is also currently one of the spotlights of the automotive industry (BRIZON; MEDEIROS, 2012). The possibility for tailoring the residual powertrain noise to provide the driver and passengers with relevant auditory information on the operation regime of the vehicle (KUO et al, 1997;DIEGO et al, 2004;GONZÁLEZ et al, 2006;KUO et al, 2007;WANG et al, 2010), or even for enhancing customer perceptions (GONZÁLEZ et al, 2003;REES;ELLIOTT, 2006) of, e.g. vehicle quality, powerfulness, sportiveness, luxury, reliability, quietness, among others (JAY, 2007), also allows the manufacturers to boost their products with unique and distinctive sound marks (FASTL, 2005;KUO et al, 2008;OLIVEIRA et al, 2010;CHEONG, 2010;WANG et al, 2013;MOSQUERA-SÁNCHEZ;OLIVEIRA, 2014b).…”