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Door latch closure noise has contribution on sound quality of vehicle door slam sound. This paper focuses on the modelling of sound quality for door latch closure sound. 24 various latch closure sound samples were recorded to be evaluated subjectively. A novel Dynamic Paired Comparison Method (DPCM) was introduced for subjective evaluation. By eliminating the redundant comparison pairs the DPCM dramatically reduced the evaluation work load comparing to the traditional Paired Comparison Method (PCM). Correlation between subjective evaluation results and psychoacoustic metrics was analyzed to find out the most relevant metrics as inputs for the subsequent prediction model. Besides, the shudder effect induced by multi-impact of latch components during closing movement was also found strongly affecting the subjective perception of door latch closure sound.

On the study of reducing the disturbance on driver’s attention induced by low frequency vehicle interior stationary noise, a subjective evaluation is firstly carried out by means of rank rating method which introduces Distraction Level (DL) as evaluation index. A visual-finger response test is developed to help evaluating members better recognize the Distraction Level during the evaluation. A non-linear back propagation artificial neural network (BPANN) is then modeled for the prediction of subjective Distraction Level, in which linear sound pressure RMS amplitudes of five Critical Band Rates (CBRs) from 20 to 500Hz are selected as inputs of the model. These inputs comprise an input vector of BPANN. Furthermore, active noise equalization (ANE) on DL is realized based on Filtered-x Least Mean Square (FxLMS) algorithm that controls the gain coefficients of inputs of trained BPANN.