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Sound quality can reflect people's subjective auditory feelings; thus, it plays an important role in automobile interior noise evaluation in recent years. Most research focuses on steady-state running conditions. In this paper, automobile vibration and noise transfer paths were measured with the binaural transfer path analysis (BTPA) method under both transient and steady-state running conditions. Then, loudness, sharpness, roughness, and A-weighted sound pressure level were used for studying properties and differences of automobile interior noise among different running conditions. Moreover, an experiment was carried out for the subjects to mark the annoyance of all noise samples. After that, the artificial neural network was applied to create the sound quality model to assess automobile interior noise without subjective experiments. According to the scores and binaural transfer path synthesis(BTPS) results, structural improvement methods were proposed for better sound quality of the automobile.

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