The Research Of Car Interior Noise Based On Statistical Energy Analysis

Recently, due to the possession of vehicle in China sharply increasing, many problemsabout cars’ noise and vibration have emerged. Traditional numerical calculation methods, Suchas boundary element method and finite element method, have obtained a great success invibration module. But it has significant limits on noise application. Statistical Energy Analysisuses relationship of energy to evaluate dynamics, SPL and acoustic radiation of the complexstructures, which applies to the problems with high module density modal. Based on practicalresults of existing, it turns to be a useful method for noise emulation analysis.The paper’s description has statistics energy analysis method of analysis thought and keyelements, from vehicles design aspects of application angle departure combines domestic someliterature, made using statistics energy analysis method for auxiliary design process in the earlyclass within acoustic forecast of envisaged. This paper has systematically explained how to usestatistical energy analysis software to establish a FAW-Volkswagen Auto SEA2B-Class vehiclemodel, which is divided into several model subsystems. For SEA modal parameters such asdensity, loss factor, coupling loss factor of different structure types, this paper simplifies a seriesof theoretical formulas, uses Matlab to calculate modal density and loss factor. For the couplingloss factor, Auto SEA2can directly provide theoretical values.Post-process car interior noise data is obtained by the pavement test to get vibrationacceleration. Get the point source excitation on vehicle suspension from the literature andcalculate the pressure data with CFD. Load these excitations into the model, analyze thecalculation results and get system-related acoustic response data. Compare experimental data andsimulation results. The result gets a good degree of agreement. It turns out that the SEA modelworks accurately and efficiently.Based on the dominating energy flow by the analyzing of result, it proposes some effectivemeasures to achieve the acoustic noise reduction. Using orthogonal optimization and graycorrelation analysis method, optimize the subsystems which have larger noise contribution to theacoustic cavities. And it can distinctly depress the SPL of the cab.