Sensorless direct current brushless motor control system and method

Through the sensorless DC brushless motor control system, motor modeling, state estimation, deep learning and adaptive control technology are used to solve the problem of unstable operation of the motor under different loads and working conditions, and achieve high precision and high stability motor control.

CN120433657APending Publication Date: 2025-08-05SHENZHEN KECHUANGXING MOTOR TECH CO LTD
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Patent Information

Application Number
CN202510620582.1
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-05-14
Publication Date
2025-08-05

AI Technical Summary

Technical Problem

The existing motor control system cannot dynamically adjust the gain parameters in real time, resulting in unstable operation of the motor under different loads and working conditions, serious accumulation of rotor state estimation errors, inaccurate control of phase exchange timing, untimely system response, and unstable performance.

Method used

The sensorless DC brushless motor control system is adopted, including the motor modeling module, the state estimation module, the deep learning prediction module, the filtering fusion module and the adaptive control module. By establishing a dynamic motor model, combining real-time signal and neural network prediction, the rotor state estimation is optimized, and the controller gain parameters are dynamically adjusted to achieve precise control.

Benefits of technology

It realizes efficient and stable operation of the motor under various operating conditions, improves the accuracy of rotor state estimation and control accuracy, avoids performance fluctuations caused by error accumulation and improper phase commutation, and enhances the adaptability and stability of the motor control system.

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Abstract

The invention relates to the technical field of motor control, and discloses a sensorless direct-current brushless motor control system which comprises a motor modeling module, a state estimation module, a deep learning prediction module, a filtering fusion module, a self-adaptive control module and a control execution module. The invention also discloses a sensorless direct current brushless motor control method, which comprises the following steps of: model establishment: constructing an electrical model and a mechanical model for describing the dynamic behavior of the motor so as to obtain a motor operation dynamic model suitable for control calculation; and state estimation: performing preliminary estimation on the rotor position and the rotor speed of the motor by utilizing the running dynamic model and combining current and voltage real-time signals acquired in the running process of the motor. According to the method, high-precision and high-stability control of the motor under different load and operation conditions is realized through adaptive control and rotor state estimation optimization technologies, real-time dynamic adjustment and commutation accuracy of the motor are ensured, and the overall control performance is improved.
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