Research On Multi-mode Active Sound Quality Control For Cabin Interior Noise

Good NVH performance can not only greatly improve passenger driving and riding experience,also can improve the recognition of automobile products and affect consumers’ shopping orientation,for most of the interior Noise control at home and abroad in order to improve the vehicle comfort sound quality for the purpose of reducing the loudness of sound pressure level or low frequency interior Noise value,there is no in-depth analysis to the human ear hearing characteristics and the influence of sound quality for crew auditory feeling.It also ignores the multidimensional characteristics of the passenger’s auditory perception,which cannot meet the needs of the majority of consumers for the sound quality of the car.In view of the above problems,this paper conducts sound quality prediction and active optimization control for interior noise based on two dimensions of comfort and sense of motion.The main research contents are as follows:Taking a domestic SUV as the research object,record the car interior sound samples in uniform speed and acceleration condition.Evaluating in objective and subjective aim at comfort and sport sound quality.subjective The results of subjective and objective evaluation of multidimensional sound quality were analyzed.GA-BP neural network algorithm is used to establish the vehicle sound quality multidimensional nonlinear prediction model.The loudness,sharpness,and roughness of three psychoacoustics parameters as input,the objective evaluation results as output.Based on the active noise equalization algorithm,the order active noise control system is designed,and the corresponding simulation model is established by SIMULINK.Through simulation analysis,the optimal order and convergence factor of the adaptive filter are determined.Aiming at the two sound quality control modes of comfort and sense of motion,the amplitude of sound pressure level is adjusted for each order of noise,and the influence of sound pressure level change of each order of noise on comfort and sense of motion is analyzed,and the system control order under the two sound quality control modes is determined.Different combinations of residual coefficients were used for the simulation control of sound quality in the vehicle.Ga-bp neural network model of residual coefficient and sound quality score was established based on the simulation results.The sound quality score was optimized for the combination of residual coefficients within a certain range to determine the optimal residual coefficient under the two sound quality control modes.Finally,the proposed control system and parameters are verified based on simulation and experiment respectively.The results show that the proposed system can carry out multi-mode active control of vehicle sound quality.