车内声品质评价预测与控制技术研究
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摘要
将汽车声品质作为车内噪声的评价标准，以此为目标指导汽车产品的声学研发设计、声品质优化改进，从而提高车内的声学舒适性，满足消费者的需求，是汽车车内噪声研究的重要内容和发展方向。国内对汽车声品质的研究刚起步，虽然在评价方法和模型建立方面取得了一定成果，但建模方法单一、精度不高，且不能对车内声品质优化改进提供指导。
本文旨在研究车内噪声品质的预测及在实际工程中的应用，为车内声品质改进设计提供技术方法。以主观评价试验结果及心理声学客观参数为基础，通过遗传算法改进BP神经网络，建立汽车声品质的评价模型，并通过权重分析与模型重建，找出对主观评价结果有重要影响的客观参量。采用传递路径合成技术，建立了整车车内噪声合成模型，并结合声品质评价模型建立了虚拟车内声品质预测模型。将试验数据与仿真计算相结合，进行路径贡献量与传递函数分析，找出了对车内声品质有重要影响的噪声来源。在虚拟车内声品质预测模型中，通过修改主要的噪声源的传递路径，模拟实际的改进措施。声品质仿真预测结果说明对主要路径的修改具有良好的效果，为车内声品质优化提供指导。通过对降噪策略和影响因素的研究，提出切实可行的声品质优化方案。试验结果表明，优化后车内烦躁度等级提升，声品质与国外同等级车相差0.5以内，达到满意效果。
With the continuous development of society and economy, vehicle interiornoise gradually become one of the most important indicators to measure thequality of vehicles, and it is become an important factor to evaluate and buying acar. Reducing interior noise to increase acoustic comfort has also become animportant part of the automotive product development design, and the relatedresearches become the hotspot in automotive industry. At present, A-weightedsound level is taken as standard and optimization objective in vehicles interiornoise evaluation study. However, A sound level can not fully reflect the physicalcharacteristics of interior noise and people subjective feeling, simply reduce thecar sound level A method has been unable to meet the demand of passengers.Consumers began to pay attention to sound quality. So creating a comfortable interior acoustic environment and taking sound quality as vehicles interioroptimized design target become an important research and future developmentdirection.
Works in this thesis are based on the projec（t20100361）form Jilin ProvinceScience and Technology Development. In the paper, steady-state interior noisewas focused as research targets, subjective evaluation test was performed forannoyance grade. Based on the subjective and objective evaluation data, a soundquality evaluation model was established by neural network. By weight analysisand model reconstruction, the objective parameters that have importantimplications to subjective evaluation results were found out. Combine thetransmission path synthesis technology with sound quality evaluation mode, avirtual car sound quality equivalent model is established. In the model, mainnoise source that have important influence on sound quality can be identified bytransfer path analysis. In the model, sound quality simulation was preformed by modify the transmission characteristic of the primary path. With the analysisovercome, improvement was applied on original car, and achieved good results.The main contents are as follows:
Firstly, subjective evaluation test was carried out and the objectiveparameters were calculated for interior noise of the steady-state operatingconditions based on the theories of vehicle noise and psychoacoustics. Theobjective parameters as input, the subjective value as output, a GA-BP neuralnetwork was adopted to establish a sound quality evaluation model. Comparedwith BP model, the model convergence rate nearly three times the averageprediction error is reduced by3.29%, and gave good predictions of highcorrelation (0.928) and low error (±8%). It proves that the proposed model hashigh accuracy and effectiveness. Weight analysis and reconstruction modelshowed that loudness, sharpness and roughness are the most influentialparameters in vehicle interior sound quality, other objective parameters have little effect.
Next, with the composing analysis of interior noise, combining the interiornoise model, a vehicle interior noise simulation model based on transfer path analysis is established. In order to improve model accuracy, the m sequencecorrelative identification method of airborne noise transfer function wasproposed, and matrix inverse method was used to calculate excitation ofstructure-born noise. The model prediction spectrum is same as experiments data,the error of A-weighted sound level is less than2.0%, the error of loudnessis less than6.8%, the relative error of sharpness is4.7%, the relative error ofroughness is less than6.0%. This shows that the established synthesis model hashigh prediction accuracy, the synthetic interior noise can reflect the actual carnoise characteristics. Combine noise synthetic model with sound qualityevaluation model, a virtual car sound quality equivalent model was established.In the model, the sound quality as a result of the output and the final destination, the interior noise synthesis model extends to a prediction of sound quality,objective parameters can be calculated and directly to obtain annoyance values.
Then, the contribution of each transmission path is calculated, main noisesource transfer path is identified as rear suspension. In order to simulate designthe sound quality, transfer characteristics of engine rear mounting Z andX-direction paths that have great influence in sound quality are modified inprediction model. The simulation results show that, just take effective noisereduction measures in main noise source path can get good sound qualityimprovement effect. These works provide a guide for sound qualityimprovement.
Finally, the technique of vibration isolation and decrease interior noise areresearch and some situations are applied on real vehicle. The body mountbracket system is optimized to improve stiffness and vibration resistance byfinite element dynamic analysis method. Real vehicle tests show that, applying the improvement on original car, the sound quality is enhanced, andcompared with foreign car the gap is less than0.5. The result verify theeffectiveness of the optimization measures.
In this thesis, a sound quality prediction model and a virtual car soundquality equivalent model are established. The research gives an integratedtechnique of vehicle sound quality prediction, evaluation and control and have ahigh theoretical significance and a good prospect.
本文旨在研究车内噪声品质的预测及在实际工程中的应用，为车内声品质改进设计提供技术方法。以主观评价试验结果及心理声学客观参数为基础，通过遗传算法改进BP神经网络，建立汽车声品质的评价模型，并通过权重分析与模型重建，找出对主观评价结果有重要影响的客观参量。采用传递路径合成技术，建立了整车车内噪声合成模型，并结合声品质评价模型建立了虚拟车内声品质预测模型。将试验数据与仿真计算相结合，进行路径贡献量与传递函数分析，找出了对车内声品质有重要影响的噪声来源。在虚拟车内声品质预测模型中，通过修改主要的噪声源的传递路径，模拟实际的改进措施。声品质仿真预测结果说明对主要路径的修改具有良好的效果，为车内声品质优化提供指导。通过对降噪策略和影响因素的研究，提出切实可行的声品质优化方案。试验结果表明，优化后车内烦躁度等级提升，声品质与国外同等级车相差0.5以内，达到满意效果。
With the continuous development of society and economy, vehicle interiornoise gradually become one of the most important indicators to measure thequality of vehicles, and it is become an important factor to evaluate and buying acar. Reducing interior noise to increase acoustic comfort has also become animportant part of the automotive product development design, and the relatedresearches become the hotspot in automotive industry. At present, A-weightedsound level is taken as standard and optimization objective in vehicles interiornoise evaluation study. However, A sound level can not fully reflect the physicalcharacteristics of interior noise and people subjective feeling, simply reduce thecar sound level A method has been unable to meet the demand of passengers.Consumers began to pay attention to sound quality. So creating a comfortable interior acoustic environment and taking sound quality as vehicles interioroptimized design target become an important research and future developmentdirection.
Works in this thesis are based on the projec（t20100361）form Jilin ProvinceScience and Technology Development. In the paper, steady-state interior noisewas focused as research targets, subjective evaluation test was performed forannoyance grade. Based on the subjective and objective evaluation data, a soundquality evaluation model was established by neural network. By weight analysisand model reconstruction, the objective parameters that have importantimplications to subjective evaluation results were found out. Combine thetransmission path synthesis technology with sound quality evaluation mode, avirtual car sound quality equivalent model is established. In the model, mainnoise source that have important influence on sound quality can be identified bytransfer path analysis. In the model, sound quality simulation was preformed by modify the transmission characteristic of the primary path. With the analysisovercome, improvement was applied on original car, and achieved good results.The main contents are as follows:
Firstly, subjective evaluation test was carried out and the objectiveparameters were calculated for interior noise of the steady-state operatingconditions based on the theories of vehicle noise and psychoacoustics. Theobjective parameters as input, the subjective value as output, a GA-BP neuralnetwork was adopted to establish a sound quality evaluation model. Comparedwith BP model, the model convergence rate nearly three times the averageprediction error is reduced by3.29%, and gave good predictions of highcorrelation (0.928) and low error (±8%). It proves that the proposed model hashigh accuracy and effectiveness. Weight analysis and reconstruction modelshowed that loudness, sharpness and roughness are the most influentialparameters in vehicle interior sound quality, other objective parameters have little effect.
Next, with the composing analysis of interior noise, combining the interiornoise model, a vehicle interior noise simulation model based on transfer path analysis is established. In order to improve model accuracy, the m sequencecorrelative identification method of airborne noise transfer function wasproposed, and matrix inverse method was used to calculate excitation ofstructure-born noise. The model prediction spectrum is same as experiments data,the error of A-weighted sound level is less than2.0%, the error of loudnessis less than6.8%, the relative error of sharpness is4.7%, the relative error ofroughness is less than6.0%. This shows that the established synthesis model hashigh prediction accuracy, the synthetic interior noise can reflect the actual carnoise characteristics. Combine noise synthetic model with sound qualityevaluation model, a virtual car sound quality equivalent model was established.In the model, the sound quality as a result of the output and the final destination, the interior noise synthesis model extends to a prediction of sound quality,objective parameters can be calculated and directly to obtain annoyance values.
Then, the contribution of each transmission path is calculated, main noisesource transfer path is identified as rear suspension. In order to simulate designthe sound quality, transfer characteristics of engine rear mounting Z andX-direction paths that have great influence in sound quality are modified inprediction model. The simulation results show that, just take effective noisereduction measures in main noise source path can get good sound qualityimprovement effect. These works provide a guide for sound qualityimprovement.
Finally, the technique of vibration isolation and decrease interior noise areresearch and some situations are applied on real vehicle. The body mountbracket system is optimized to improve stiffness and vibration resistance byfinite element dynamic analysis method. Real vehicle tests show that, applying the improvement on original car, the sound quality is enhanced, andcompared with foreign car the gap is less than0.5. The result verify theeffectiveness of the optimization measures.
In this thesis, a sound quality prediction model and a virtual car soundquality equivalent model are established. The research gives an integratedtechnique of vehicle sound quality prediction, evaluation and control and have ahigh theoretical significance and a good prospect.
引文
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