Study On Sound Quality Of The Door-slamming Of Passenger Cars

With the development of vehicle industry and the improvement of people’s livingstandard, the customer’s requirement for the comfort of the car is improved. As one ofthe main factors of automobile quality, noise has attracted more and more attention. Inrecent years, people has found that the traditional noise control cannot meet themarket demand, so the research and application of sound quality has become a focusin the field of noise control, and is attracted more and more attention by the carcompanies. Sound quality has become the important factors of productcompetitiveness.The sound of door-slamming has not only the characteristics of noise, but alsothe characteristics of quality. The customer’s first impression of a car not only camefrom the appearance of a car, but also came from the sound quality of door-slamming.If the sound quality of door-slamming is poor, the car will be given up by customersand the competition ability of the enterprise will be influenced directly. Therefore, theresearch of the sound quality of door-slamming is one of the important contents invehicle quality. The dissertation sponsored by the project “Yue Sheng Program” andthe independent innovation capabilities of high-level car construction in China. Thesound quality prediction model, the sound quality evaluation parameters and thesound quality optimization methods of door-slamming were studied in thisdissertation.The main research contents of this dissertation were(1) Aiming at the problem that the precision of the sound quality predictionmodel of door-slamming is poor, EMD (Empirical Mode Decomposition) method wasintroduced to predict the sound quality of door-slamming. Based on EMD, BP (BackPropagation) neural network prediction model and SVM (support vector machines)prediction model were established. Furthermore, Critical Band WaveletDecomposition was also introduced to predict the sound quality of door-slamming.Based on Critical Band Wavelet Decomposition, BP (Back Propagation) neuralnetwork prediction model and SVM (support vector machines) prediction model wereestablished. The comparative analysis has been done between the traditionalprediction model based on psychology parameters and the new prediction model basedon time-frequency analysis methods. (2) Aiming at the problem that the existed sound quality evaluation parameterscannot evaluate the sound quality of door-slamming fully and accurately, thetime-frequency analysis methods were introduced into the objective evaluation ofsound quality of door-slamming. The characteristics of the sound quality wereextracted by time-frequency analysis methods, and based on it new sound qualityevaluation parameters were established. Two new sound metrics called S ound Metricbased on Pseudo Wigner-Ville Distribution (SMPWVD) and Sound Metric based onCritical Band Wavelet Decomposition (SWCBWD) were developed. The comparativeanalysis of the correlation coefficients between the subjective sound qualityperformance value of door-slamming and SMPWVD or SMPWVD has been done.(3) Aiming at the problem that the sound quality of door-slamming can’t beanalyzed without actual vehicles, the explicit finite element method widely used invehicle safety impact analysis was introduced into the analysis of door-slamming. Bycombining the explicit finite element method with the experimental design methodand the response surface method, an approximation model of door-slammingoptimization was established. To reduce the vibration energy of door-slamming, theapproximate model was optimized by using the genetic algorithm. The simulation andexperimental results before and after optimization verified that the sound quality ofdoor-slamming of the optimized model was improved. Furthermore, the soundradiation simulation model of the door system was established. By comparing thesound pressure and traditional sound quality evaluation parameters (loudness,sharpness) of the sound radiation simulation model before and after the optimization,the sound quality of door-slamming of the optimized model was improved. Based onthe objective and subjective evaluation experiments, the loudness, sharpness,SMPWVD, SMCBWD and the subjective sound quality preference of the car beforemodified (OTS3), the modified car (OTS4) and a benchmarking car was test andanalyzed.This dissertation made in-depth researches on the sound quality prediction model,the sound quality evaluation parameters and the sound quality optimization methodsof door-slamming. The new prediction model based on time-frequency analysismethods was established. The prediction precision of the new prediction model wasimproved compared with the traditional prediction model. Two new sound metricscalled SMPWVD and SWCBWD which can provide the accurate and effectiveevaluation parameters were developed. What’s more, the sound quality optimizationprocess of door-slamming was established. By optimizing the energy of door-slamming, the sound quality of door-slamming was improved. The researchresults of this dissertation can provide the effective way to predict, evaluate andimprove the sound quality, and have an important theoretical significance andapplication value.