4 results about "Flux observer" patented technology

An optimization method for BLDC non-inductive low-speed starting based on IF starting and flux estimation, comprising the following steps: step one: establishing a BLDC motor electrical model, and obtaining relevant parameters for building a current double closed loop model through the BLDC motor electrical model; step two: based on the simulink simulation software, building a current double closed loop model of d and q axes; step three: based on the current double closed loop model built in step two, realizing IF open loop low-speed starting and acceleration of the BLDC motor; step four: constructing a discrete nonlinear flux observer, and online estimating the flux to obtain the rotor electric angle_ref and the equivalent back electromotive force component; step five: according to the equivalent back electromotive force component, online following and correcting the open loop electric angle. The present application can realize quick and undisturbed switching from open loop starting to non-inductive closed loop control, thereby significantly improving the starting success rate and operation stability of the BLDC motor under low-speed working conditions.

System and method for sensorless control of an induction motor are disclosed. A flux observer estimates a rotor flux based on stator voltage and current measurement. A low frequency signal injection module generates a flux estimation error signal at low motor speed, while a baseline observer generates a model based flux estimation error signal at medium to high motor speed. A switching mechanism selects between these error signal based on motor condition. A proportional integral regulator and integrator process the selected error signal to estimate rotor speed. A lead compensator adjusts phase during transitions to ensure stability, with a switching signal generator activating the LFSI module when stator frequency falls below a predefined threshold. This control system provides rotor flux and speed estimation across a full range of motor speed by adaptively switching between observers based on operating conditions.

The application discloses a kind of high-reliability motor improved deadbeat torque control digital implementation methods, belong to motor drive control technical field.It includes the following steps: construct stator flux oriented coordinate system, acquisition motor signal and establish five-phase fault-tolerant motor model;Full-order Luenberger current observer is constructed to carry out delay compensation and state prediction to five-phase current;Hybrid flux observer is constructed, and integral drift of voltage model is corrected by closed-loop compensation, and the amplitude and phase angle of stator flux are obtained;Deadbeat control is carried out in MT coordinate system, and the simplified linear relationship between electromagnetic torque and load angle is established, and the reference voltage vector is linearly solved;The reference voltage is transformed back to the stationary coordinate system, and the switching signal is generated by using adjacent four-vector space vector pulse width modulation to drive the motor.The application can significantly improve the control performance of five-phase motor under normal operation of control system and the system stability under parameter mismatch, and has important significance for strengthening the reliability and stability of multiphase electric drive system.

The application discloses a permanent magnet synchronous motor flux linkage observer parameter compensation method based on an improved hybrid beluga optimization algorithm, proposes a customized improved HBWO algorithm for a flux linkage observation scene, and realizes 3-dimensional compensation factors through the algorithm. Firstly, the harmonic compensation factor is used for harmonic cancellation of the shaft voltage signal, and high-frequency interference in the electric signal is suppressed. Secondly, the resistance compensation factor is used for dynamic correction of the stator resistance parameter, and resistance drift caused by motor temperature change is adapted. Thirdly, the inductance compensation factor is used for real-time updating of the stator inductance parameter, and inductance change caused by load fluctuation is matched. The optimization factor is embedded into an error preprocessing link and a parameter correction link of the flux linkage observer, noise reduction of the observer input signal and adaptive updating of core parameters are realized. Compared with the prior art, the application effectively improves the precision and stability of the flux linkage observer, and is suitable for high-precision control scenes of the permanent magnet synchronous motor under the conditions of medium and high speed and variable load.