Permanent Magnet Brushless DC Motor Speed Control And Parameter Identification

The permanent magnet brushless DC motor has small size, low noise, large torque and many other advantages. In the small and medium power motor the brush DC motor can not match with them.Therefore, today the permanent magnet brushless DC motor has been widely used in the medical, household appliances, automotive industry. In this paper, a study of the permanent magnet brushless DC motor based on these advantages. This article is based on the the elderly electric scooter experimental platform for studying the permanent magnet brushless DC motor control system and the motor model parameters. Designed according to the characteristics of the brushless DC motor, brushless motor control system solutions. System program through the external size of the accelerator, the treated judgments motor state and respond accordingly to achieve the purpose of control. According to the data collected using recursive least squares method to identify the model parameters.The control system’s main chip is the ST micro controller in this article,mainly work as follows:According to the working principle of the permanent magnet brushless DC motor, the functionality required by the actual design in accordance with the objectives to be achieved under the overall control scheme.(1) According to the design of system hardware circuit design and component selection. The hardware circuit includes:a power supply circuit, inverter bridge circuit, the power tube drive circuit, the Hall signal acquisition circuit and over-current protection circuit. Draw the corresponding schematic and PCB diagram, and hardware circuit and system board.(2) In STVD platform software development and debugging. The software is developed in accordance with the modular thinking, including motor state transition module, motor commutation module, the speed regulator module. (3) Joint commissioning of the control system hardware and software, to achieve the desired objectives. Derive the mathematical model of the motor, the motor parameter identification using recursive least squares method.