
The inductance model used in traditional sensorless control methods for switched reluctance machines (SRMs) exhibits high-order harmonics. The precision of the motor may be impacted by the buildup of rotor estimate errors caused by these harmonics. To address this issue, this paper proposes a novel method for SRMs that employs a hybrid algorithm combining an enhanced second-order generalized integrator (SOGI)-based frequency-locked loop (FLL) and an active disturbance rejection control (ADRC)-based phase-locked loop (PLL). This approach involves coordinate transformation and parameter identification to reconstruct the motor inductance model. Rotor position errors are calculated using the unsaturated inductance difference method. In order to enhance the accuracy of motor position estimation, a hybrid algorithm is employed to efficiently filter out harmonic errors and mitigate the tremor effect caused by the rotor position differential algorithm. This hybrid algorithm enables the estimate of the motor’s speed and rotor position. A sensorless control simulation model was developed using a 12/8 pole SRM to assess the motor’s performance under varying load conditions. Based on the results obtained, it is established that the application of this method can accurately estimate the rotor’s position and rotational speed and thus improve the performance of position sensorless control. Ultimately, a prototype system for a switched reluctance motor was created, and the effectiveness and feasibility of the proposed control technique were confirmed through experimental validation. This presents an innovative approach to engineering practice.
second-order generalized integrator, active disturbance rejection control, switched reluctance motor, inductive model reconstruction, speed and position estimation
second-order generalized integrator, active disturbance rejection control, switched reluctance motor, inductive model reconstruction, speed and position estimation
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