scholarly journals Sensorless interior permanent magnet synchronous motor control with rotational inertia adjustment

2017 ◽  
Vol 9 (1) ◽  
pp. 168781401668474 ◽  
Author(s):  
Yongle Mao ◽  
Jiaqiang Yang ◽  
Dejun Yin ◽  
Yangsheng Chen

Mechanical model is generally required in high dynamic sensorless motor control schemes for zero phase lag estimation of rotor position and speed. However, the rotational inertia uncertainty will cause dynamic estimation errors, eventually resulting in performance deterioration of the sensorless control system. Therefore, this article proposes a high dynamic performance sensorless control strategy with online adjustment of the rotational inertia. Based on a synthetic back electromotive force model, the voltage equation of interior permanent magnet synchronous motor is transformed to that of an equivalent non-salient permanent magnet synchronous motor. Then, an extended nonlinear observer is designed for interior permanent magnet synchronous motor in the stator-fixed coordinate frame, with rotor position, speed and load torque simultaneously estimated. The effect of inaccurate rotational inertia on the estimation of rotor position and speed is investigated, and a novel rotational inertia adjustment approach that employs the gradient descent algorithm is proposed to suppress the dynamic estimation errors. The effectiveness of the proposed control strategy is demonstrated by experimental tests.

2012 ◽  
Vol 150 ◽  
pp. 100-104
Author(s):  
Tao Zhang ◽  
Wei Ni ◽  
Hui Ping Zhang ◽  
Sha Sha Wu

When the permanent magnet synchronous motor is operated at a low speed. The rotor position and speed are very difficult to estimate using the extended flux or back EMF method. A novel modified current slope estimating method is used to estimate the rotor position and speed in low speed in this paper. The mathematical models of an interior permanent magnet synchronous motor (IPMSM) are deduced. The basic principle of modified current slope method is introduced. The simulation control system is built based on Matlab and a TMS320LF2407 digital signal processor is used to execute the rotor position and speed estimation. The experimental and simulation results have shown that the rotor position and speed can be accurately estimated in a low-speed operating region.


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