Fault analysis and elimination of motor sensors in pure electric vehicles
DOI:
https://doi.org/10.54097/kka2wq45Keywords:
Motor sensor; CNN algorithm; Signal simulation method; thermistor.Abstract
Sensor as the main component of the motor drive system is to ensure its stable and reliable operation of the core components, so to drive the system's normal operation must learn how to analyse and diagnose the motor sensor fault accurately. This paper first introduces different fault classification and basic diagnosis methods, uses the CNN algorithm to collect sensor information, and uses matrix, dot product and other mathematical operations to make deep diagnosis. The sensor's real-time working status and accurate fault feedback can be obtained. CNN algorithm is fully suitable for the research and application of motor sensor fault diagnosis and can provide the basis for fault diagnosis according to the change of its own operating data parameters, and achieve efficient analysis and elimination of existing faults, to a certain extent, it can provide reference for the replacement of motor sensors and provide analysis for personnel engaged in related diagnosis industries.
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