There has been a large amount of work on the field of BLDC motor identification, where time domain identification dominates. Meanwhile, the second important issue is the model’s parameters determination method. Therefore, besides the parameters in classic linear model, cogging torque effect is also essential for a practical model as a nonlinear factor, especially for the low speed mode. It is shown in that the cogging torque is the main source of torque ripple in BLDC motor control. In, phase commutation is considered however complexity of mathematical model is greatly enhanced. The system dynamic model structure is the first part of the simulation environment to take into consideration. In this case, to build an accurate mathematical model of the BLDC motor is of greater importance.
If the difference between simulation model and the practical motor plant cannot be ignored, the designed controller in simulation is questionable. There is a desire for algorithm validations when the controller is designed. Control techniques research including torque, speed, and position has been intensively carried out, such as torque control method for torque ripple minimization and sensorless control algorithms for low cost applications.
The BLDC motors, which are used to drive rotor or propeller, pursue abilities of rapid speed response and disturbance reject. Particularly for small-scaled UAVs (Unmanned Aerial Vehicles), the BLDC motor are receiving an increasing number of attentions with the advantages of small size, high power density, and easy control and operation. Introductionīrushless direct current (BLDC) motors are prevailingly used in high performance drive applications such as machine tools, robotics, space crafts, and medical applications, owing to their superior speed-torque characteristics, high efficiency, less maintenance, and wide operating speed range. The proposed identification method is systematically investigated, and the final identified model is validated by experimental results performed on a typical BLDC motor in UAV. Only the availability of experimental data for rotor speed and armature current are required for identification. The methods in time domain are founded on the least squares approximation method and a disturbance observer.
Frequency domain identification techniques and time domain estimation method are combined to obtain the unknown parameters. A practical mathematical model for identification is derived. The aim of this paper is to outline all the steps in a rigorous and simple procedure for system identification of BLDC motor.