Fardriver controller self learning and setting скачать в хорошем качестве

Fardriver controller self learning and setting

The self-learning function of the remote drive controller is an intelligent parameter matching technology, which is mainly used in scenarios such as electric vehicles and industrial motors. By automatically identifying motor parameters and optimizing control algorithms, the controller and motor can be quickly matched to improve system operation efficiency and stability. The core role of the self-learning function 1. Automatic parameter identification Through self-learning, the controller can automatically detect the key parameters of the motor, such as: Phase sequence (the wiring sequence of the motor winding) Resistance/inductance (affecting current control) Back EMF waveform (affecting the accuracy of the sensorless algorithm) Hall sensor position (for angle calibration of Hall motors) 2. Dynamic matching control parameters According to the motor characteristics, automatically generate optimized PID control parameters (proportional, integral, differential) to improve response speed and stability. 3. Fault prediction Detect abnormalities in the motor or line (such as phase loss, Hall signal error), and warn of potential problems in advance.