Develpment Of Comprehensive Diagnostic Testbed For EV Permanent Magnet Synchronous Motor

Permanent magnet synchronous motor(PMSM)is widely used in the drive system of electric vehicles because of its high efficiency,high power density and wide speed range.Datadriven method is widely used in condition monitoring and fault diagnosis of PMSM,but the lack of prior data,especially under working conditions,has been the main obstacle to the fault diagnosis modeling of PMSM.The existing electric vehicle drive motor test bench mostly focuses on the motor power test,and the state parameters that can be obtained are not only limited in type but also low in sampling rate.Therefore,it is necessary to develop a test bench capable of simultaneously collecting multi-sensor characteristic signals in different states of an electric vehicle drive motor.Firstly,in view of the shortcomings of the current electric vehicle drive motor test bench,the hardware selection and system construction of the test bench were carried out.Providing accurate load to the motor under test is the precondition of realizing the simulation of typical working conditions.Therefore,a ABB converter with direct torque control(DTC)function drives AC variable frequency motor as the load exerting device of the test bed.NI cRIO-9030 controller,NI 9220 and NI 9234 acquisition module provide hardware basis for high-speed synchronous acquisition of multi-sensor characteristic signals.In order to reduce the energy consumption of the test-bed,the energy recovery device is integrated into the test-bed.Secondly,the test bench was programmed based on the Lab Virtual Instrument Integration Environment(LabVIEW).The Modbus bus and PID control algorithm are used to realize the constant speed control of the motor under test,and the realization method of the typical working condition simulation of the tested motor is proposed.Different types of motor faults can be clearly reflected in different characteristic signals.Based on this characteristic,high-speed synchronous acquisition of multi-channel characteristic signals of current,temperature,speed,torque and vibration of the motor under test is completed,which provides data basis for the operation of the diagnosis algorithm.Finally,the fault diagnosis method of permanent magnet synchronous motor is studied based on local mean decomposition(LMD)and support vector data description(SVDD)theory.The acquisition of a priori data in different fault modes of PMSM is completed by simulation and experiment.The fault diagnosis model of LMD-SVDD is established and the accuracy of the model is verified.The research and development of this test platform can provide a good data foundation for the establishment of electric vehicle drive motor health assessment and fault diagnosis model,and effectively promote the research on the reliability,safety and energy efficiency of electric vehicle drive motor.At the same time,the diagnostic model constructed It can quickly and accurately diagnose different fault types and facilitate the repair and maintenance of electric vehicle drive motors.