Recognition And Optimization Of Light Bus Noise In Full Frequency Range

With the continuous development of social science and technology and the increasing improvement of people’s living standards,the choice of travel tools does not only refer to the power,stability,and economy of the vehicle,but pay more attention to the ride quality of the vehicle.The ride comfort of a vehicle is generally measured by NVH.The NVH performance of a car often determines the quality of the vehicle.For light-duty passenger vehicles such as passenger-centric transportation vehicles,the occupants often take up to several hours,which puts forward higher requirements for the ride comfort of light-duty passenger vehicles.Therefore,it is of great significance to carry out the optimization and control of the full-frequency noise of light passenger vehicles.In the process of identifying low-frequency noise sources in the car based on the transmission path analysis,in order to reduce the influence of OPAX’s interference noise during the signal acquisition process and to improve the analysis accuracy,an optimized OPAX method based on adaptive variational modal decomposition and Bhattacharyya distance is proposed.Considering that the multi-scale fuzzy entropy can better characterize the unsteady complex signal,it is used as the fitness function;the simulated annealing particle swarm algorithm is used to carry out the signal adaptive variational modal decomposition,and finally the original signal and decomposition are calculated by the Bhattacharyya distance The similarity of the signal probability density function is screened in the relevant modal to achieve signal denoising.The results show that the signal-to-noise ratio of the OPAX calculated value after optimization is improved by 71.2%,the root mean square error is reduced by 66.9%,and the error at the peak frequency is controlled within 5%.Finally,a method is proposed to identify the main noise frequency by using the coherent power spectrum to determine the lowfrequency noise source of the vehicle.In the process of identifying mid-and high-frequency noise in the vehicle based on the statistical energy method,a statistical energy analysis model of the entire vehicle is established on the basis of the structural equivalent sub-models of the front wall and the floor.In the statistical energy analysis model,the noise contribution degree of the three target points in the car is analyzed.The analysis results show that the noise in the car is mainly caused by direct sound and transmitted sound,which accounts for up to70%.In the mid-and high-frequency noise optimization process,optimization is carried out from two aspects of direct sound and transmitted sound.According to the analysis results,the noise is reduced by adding EVA material for the transmitted sound at each position.According to the noise optimization scheme proposed by the low frequency and high frequency of the vehicle,the corresponding improvement and optimization are carried out on the actual vehicle,and the optimization results are verified through the actual vehicle test.The experimental results show that the noise value of the three target points in the vehicle has the original 76.98 d B,76.13 d B,76.93 d B down to 70.34 d B,69.84 d B,69.82 d B.The noise reduction effect is significant.