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Sound Quality Evaluation of Centralized Drive PMSM Based on Grade Scoring Method
Technical Paper
2017-01-1061
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
Electric vehicle driving permanent magnet synchronous motor has a wide speed range and load changes, with abundant harmonic currents, and its eccentric form is complex, which all result in poor sound quality and abnormal noise problems becoming increasingly prominent. To make a systematic and thorough study of the centralized drive permanent magnet synchronous motor (PMSM) is significant to ameliorate the sound quality and solve noise problems. MATLAB-based modeling technology, SPSS software, and the establishment of sound quality evaluation model for the centralized drive PMSM has a crucial reference value on the research and development of the electric vehicle driving permanent magnet synchronous motor.
As for the sound quality of centralized drive PMSM, firstly, in order to get objective parameter values, evaluation models of objective parameters based on psychological acoustics should be established after the collection of the sound samples. Then, based on grade scoring method, the design of sound quality test and subjective evaluation test software are established to obtain subjective annoyance of these sound samples. Finally, after analyzing the correlation between subjective annoyance of the centralized drive PMSM and objective parameters, cubic regression models with regard to subjective annoyance with A-weighted sound level, loudness and speech intelligibility are also established respectively, in addition to a linear regression model of annoyance with these three parameters. Furthermore, after analyzing the correlation of objective parameters, speech intelligibility effects on subjective annoyance can be explained by the A-weighted sound level in large part. Meanwhile, an evaluation system for sound quality of centralized drive PMSM is implemented.
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Authors
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Citation
Zhai, J. and Conggan, M., "Sound Quality Evaluation of Centralized Drive PMSM Based on Grade Scoring Method," SAE Technical Paper 2017-01-1061, 2017, https://doi.org/10.4271/2017-01-1061.Data Sets - Support Documents
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