ANFIS-based electric vehicle permanent magnet synchronous motor fault classification method

A permanent magnet synchronous motor, electric vehicle technology, applied in motor generator testing, measuring electricity, measuring electrical variables, etc., can solve problems such as rotor eccentricity fault, rotor bearing fault, drive motor shutdown and so on
CN106291354AInactive Publication Date: 2017-01-04HOHAI UNIV
4 Cites 9 Cited by

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
HOHAI UNIV
Publication Date
2017-01-04
Estimated Expiration
Not applicable · inactive patent

Smart Images

  • Figure 1
    Figure 1
  • Figure 2
    Figure 2
  • Figure 3
    Figure 3
Patent Text Reader

Abstract

The invention discloses an ANFIS-based electric vehicle permanent magnet synchronous motor fault classification method. The method comprises the following steps: faults are classified, and a training sample set is built through acquiring various fault data; and an adaptive neural fuzzy inference system is built, winding current in the fault data for various fault types in the electric vehicle permanent magnet synchronous motor serves as an input, one output is given for each fault type, a membership function for the input and the output is selected, system training target errors are set, a hybrid learning algorithm is used for training parameters of the membership function, and thus, input membership function parameters and output membership function parameters in the adaptive neural fuzzy inference system are thus determined. Through diagnosing the faults of the permanent magnet synchronous motor, experimental data are obtained, the experimental data are inputted to the adaptive neural fuzzy inference system, a diagnosis result is obtained, and a fault type is determined according to the diagnosis result, and thus, fault classification is completed. Strong-operability, high-efficiency, economic and high-accuracy diagnosis is realized.
Need to check novelty before this filing date? Find Prior Art

Description

technical field

[0001] The invention relates to a fault classification method, in particular to a fault classification method for permanent magnet synchronous motors of electric vehicles based on ANFIS, and belongs to the field of state detection and fault diagnosis of driving motors. Background technique

[0002] The driving motor is the core equipment of electric vehicles and the source of power for vehicles. Its reliability directly affects the driving safety of electric vehicles. Compared with traditional electrically excited motors, permanent magnet synchronous motors meet the best application indicators for electric vehicle drive motors because of their high efficiency, light weight, small size, compact structure, reliable operation and low noise. The best choice for motors, not only that, but its application range is extremely wide, covering almost every field of aerospace, military industry, automobile industry, industrial and agricultural production and daily life. ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More