Traditional square current driving method has deficiencies in muting and efficiency when controlling the brushless DC motor. This paper presents a method of space vector pulse width modulation for BLDCM, which is in five-segment type. A mathematical model of BLDCM, which is in d-q coordinate system, was established. Then, the experimental platform was constructed with the STM32F103 for BLDCM of electric vehicle. And the experiment results verify the properties of little torque ripple, smooth operation and low switching losses. Besides, the system dynamic and static performance is greatly improved, and has strong robustness. The method proposed overcomes the shortcomings of square current driving method in control efficiency and motor noise.
The brushless DC motor control system often adopts the classic PID control, the advantages of which are as follows: simple to control, easy to adjust the parameter and a certain degree of control precision. But it relies on accurate mathematical model. The permanent magnet brushless DC motor control system is a multi-variable and nonlinear. As to the deficiencies of the classic PID control method, this thesis proposes a method called artificial neural network PID adaptive control method, which is based on algebraic algorithm and overcomes the shortcomings such as the slow convergence of BP algorithm, easy to trap in local minimum, and etc.
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