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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.

With the increasing development in automotive industry, finite element (FE) analysis with model bias prediction has been used more and more widely in the fields of chassis design, body weight reduction optimization and some components development, which reduced the development cycles and enhanced analysis accuracy significantly. However, in the simulation process of plastic fuel tank system, there is few study of model validation or verification, which results that non-risky design decisions cannot be enhanced due to too much consuming time. In this study, to correct the discrepancy and uncertainty of the simulated finite element model, Bayesian inference-based method is employed, to quantify model uncertainty and evaluate the simulated results based on collected data from real mechanical tests of plastic fuel tanks and FE simulations under the same boundary conditions.

Beamforming techniques are widely used today in aeroacoustic wind tunnels to identify wind noise sources generated by interaction between incoming flow and the test object. In this study, a planar spiral microphone array with 120 channels was set out-of-flow at 1:1 aeroacoustic wind tunnel of Shanghai Automotive Wind Tunnel Center (SAWTC) to test exterior wind noise sources of a production car. Simultaneously, 2 reference microphones were set in vehicle interior to record potential sound source signal near the left side view mirror triangle and the signal of driver’s ear position synchronously. In addition, a spherical array with 48 channels was set inside the vehicle to identify interior noise sources synchronously as well. With different correlation methods and an advanced algorithm CLEAN-SC, the ranking of contributions of vehicle exterior wind noise sources to interested interior noise locations was accomplished.