• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.268-272
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• 1989

To avoid the use of position sensor or flux sensor in a field oriented induction machine drive system, the terminal quantities are often used to estimate the rotor flux. Since the estimation involves the leakage inductance of the machine, the performance of such systems is sensitive to the variations of leakage. Since estimation of the stator flux is independent of the leakage, the steady state performance of the stator flux oriented system is insensitive to the leakage inductance. In this paper, the torque response of stator flux oriented system is compared to that of rotor flux oriented system by digital simulation. And induction motor sensor less speed control by stator flux oriented method is developed. The performance of the speed estimation is showed by digital simulation.

• Proceedings of the KIPE Conference
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• 2001.07a
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• pp.264-267
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• 2001

Direct Torque Control has the fast torque and flux dynamic response as we know. This dynamic performance is realized by the estimation of electromagnetic torque and stator flux linkages. Generally, the stator flux estimation is based on the stator voltage equation. The equation uses a pure integrator. If the equation is used without an encoder in Direct Torque Control, there is the drift problem. It is same to sensorless Stator Flux Orientation Control (SFO). In this paper a programmable low pass filter (LPF) is proposed for solving the problem in Direct Torque Control.

• Journal of Power Electronics
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• v.19 no.3
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• pp.751-760
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• 2019

Since parameter mismatch seriously impacts the efficiency and stability of induction motor drives, it is important to accurately estimate the rotor and stator resistance. This paper introduces a method to directly calculate the rotor flux that is independent of stator and rotor resistance and electrical angle. It is based on obtaining the rotor and stator resistance using the model reference adaptive system (MRAS) method. The method has a lower computation burden and less adaptation time when compared with other rotor resistance estimation methods. This paper builds three coordinate frames to analyze the rotor flux error and rotor resistance error. A number of implementation issues are also considered.

• Journal of the Semiconductor & Display Technology
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• v.14 no.2
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• pp.35-40
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• 2015

This paper presents the sensorless position control of the Permanent Magnet Synchronous Motor (PMSM) using stator flux estimation and Phase Lock Loop (PLL). The field current and the torque current are required in order to perform the vector control of the PMSM. At this time, it is necessary for the torque to know the exact position of the magnetic flux generated by the permanent magnet, because the torque must be applied torque current in the direction orthogonal to the permanent magnet. In general the speed of the PMSM is controlled by using a magnetic position sensor. However, this paper, we estimates the stator flux by using the PLL method without the magnetic position sensor. This method is simple and easy, in addition it has the advantage of a stabile estimation of the rotor. Finally the proposed algorithm was confirmed by experimental results and showed the good performance.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.49 no.1
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• pp.48-53
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• 2000

The novel integration method with programmable high-pass filter is suggested in order to solve the problem of integration for stator flux estimation in a stator flux oriented direct vector controlled induction motor drive system. The dc offset in a pure integrator is eliminated using high-pass filter with fixed time constant, and then time constant of programmable high-pass filter is controlled with a inverter frequency for integration in a wide frequency range, considering phase lag and attenuation due to both the hardware low-pass filter and high-pass filter. The proposed method is verified with the experimental results implemented by 32-bit DSP.

• Proceedings of the KIPE Conference
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• 1997.07a
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• pp.161-165
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• 1997

For high performance ac drives, the speed sensorless vector control and the stator flux orientation concept have received increasing attention. This paper presents a new method of estimation the speed of AC induction machine(IM). To improve the speed estimation characteristics, accurate stator resistance variation is considered. The effectiveness of the proposed method is verified computer simulation.

• Proceedings of the KIPE Conference
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• 2000.07a
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• pp.421-424
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• 2000

Direct Torque Control(DTC) of AC motor has the fast torque and flux dynamic responses even though it has very simple scheme to implement. However DTC do not show good performance at low speed range with conventional open loop stator flux observer when stator resistance varied. So authors proposed nonlinear stator flux obsever in order to flux estimation at low speed and show its simulation results.

• Journal of Power Electronics
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• v.13 no.3
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• pp.369-380
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• 2013

Direct torque control based on space vector modulation (SVM-DTC) protects the DTC transient merits. Furthermore, it creates better quality steady-state performance in a wide speed range. The modified method of DTC using SVM improves the electrical magnitudes of asynchronous machines, such as minimizing the stator current distortions, the stator flux with electromagnetic torque without ripple, the fast response of the rotor speed, and the constant switching frequency. In this paper, the proposed method is based on two new control strategies for direct torque control with space vector modulation. First, fuzzy logic control is used instead of the PI torque and a PI flux controller to minimizing the torque error and to achieve a constant switching frequency. The voltages in the direct and quadratic reference frame ($V_d$, $V_q$) are achieved by fuzzy logic control. In this scheme, the switching capability of the inverter is fully utilized, which improves the system performance. Second, the close loop of stator flux estimation based on the voltage model and a low pass filter is used to counteract the drawbacks in the open loop of the stator flux such as the problems saturation and dc drift. The response of this new control strategy is compared with DTC-SVM. The experimental and simulation results demonstrate that the proposed control topology outperforms the conventional DTC-SVM in terms of system robustness and eliminating the bad outcome of dc-offset.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.4
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• pp.253-263
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• 2002

This paper presents an adaptive feedback linearization control scheme for induction motors using stator fluxes. By using stator flukes as states, overparameterization is prevented and control inputs can be determined straightforwardly unlike in existing schemes. This approach leads to the decrease of the relative degree for the flux modulus and thus yields a simpler control algorithm than the prior results. In this paper. adaptation schemes are suggested to compensate for the variations of stator resistance. rotor resistance and load torque. In particular, the adaptation to the variation of stator resistance with a feedback linearization control is a new trial. In addition, to improve the convergence of rotor resistance estimation, the differences between stator currents and its estimates are used for the parameter adaptation. The simulations show that torque and flux are controlled independently and that the estimates of stator resistance, rotor resistance, and load torque converge to their true values. Actual experiments on a 3.7㎾ induction motor verify the effectiveness of the proposed method.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.550-558
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• 2014

Direct Torque controlled induction motor (DTC-IM) drives use stator resistance of the motor for stator flux estimation. So, stator resistance estimation properly is very important for a stable and effective operation of the induction motor. Stator resistance variations because of changing in temperature make DTC operation difficult mainly at low speed. A method based on artificial neural network (ANN) to estimate the stator resistance online of IM for DTC drive is modeled and verified in this paper. To train the neural network a back propagation algorithm is used. Weight adjustment of neural network is done by back propagating the error signal between measured and estimated stator current. An extensive simulation has been carried out in MATLAB/SIMULINK to prove the efficacy of the proposed stator resistance estimator. The simulation & experimental result reveals that proposed method is able to obtain precise torque and flux control at low speed.