• 제목/요약/키워드: Motor Parameter Estimation

검색결과 252건 처리시간 0.02초

Dynamic-Simulation을 통한 영구자석형 횡자속 회전기의 인덕턴스 추정 (Inductance Estimation of Permanent Magnet Type Transverse Flux Rotating Motor Using Dynamic-Simulation)

  • 김광운;김지원;정연호;이지영;강도현;장정환
    • 전기학회논문지
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    • 제59권4호
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    • pp.722-727
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    • 2010
  • This paper presents Dynamic-Simulation to estimate the inductance of a permanent magnet type transverse flux rotating motor by applying the real-time parameter estimation theory. As transverse flux rotating motor has the complex structure, it can be happen to some errors between real value and designed one with respect to the inductance. To reduce this kinds of errors, the real-time parameter estimation theory was applied to dynamic-simulation. And then, By comparing the estimated inductance and designed one, it is realized that the real-time parameter estimation theory can be applied in the permanent magnet type transverse flux rotating motor.

RLS알고리즘을 이용한 스텝 모터의 파라미터 추정 (Parameter Estimation for Step Motor using RLS Algorithm)

  • 연태준;김동민
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1999년도 하계학술대회 논문집 B
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    • pp.785-787
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    • 1999
  • In this paper, recursive least square algorithm is presented to estimate the parameters of step motor under low-speed operation. Parameter estimation is important for compensating the input current by calculating the ratio of the motor torque constant and detent torque constant that causes torque-ripple in low-speed applications. On-line parameter estimation process is a preliminary procedure to apply step motor to adaptive control. Computer simulation shows that the estimated parameters converge in finite time.

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On-line Parameter Estimation of Interior Permanent Magnet Synchronous Motor using an Extended Kalman Filter

  • Sim, Hyun-Woo;Lee, June-Seok;Lee, Kyo-Beum
    • Journal of Electrical Engineering and Technology
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    • 제9권2호
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    • pp.600-608
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    • 2014
  • This paper presents estimation of d-axis and q-axis inductance of an interior permanent magnet synchronous motor (IPMSM) by using an extended Kalman filter (EKF). The EKF is widely used for control applications including the motor sensorless control and parameter estimation. The motor parameters can be changed by temperature and air-gap flux. In particular, the variation of the inductance affects torque characteristics like the maximum torque per ampere (MTPA) control. Therefore, by estimating the parameters, it is possible to improve the torque characteristics of the motor. The performance of the proposed estimator is verified by simulations and experimental results based on an 11kW PMSM drive system.

A Study on Sensorless Control of Transverse Flux Rotating Motor Based on MRAS with Parameter Estimation

  • Kim, Ji-Won;Kim, Kwang-Woon;Kisck, Dragos Ovidiu;Kang, Do-Hyun;Chang, Jung-Hwan;Kim, Jang-Mok
    • Journal of Power Electronics
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    • 제11권6호
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    • pp.864-869
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    • 2011
  • This paper presents a sensorless control and parameter estimation strategies for a Transverse Flux Rotating Motor (TFRM). The proposed sensorless control method is based on a Model Reference Adaptive System (MRAS) to estimate the stator flux. Parameter estimation theory is also applied into the sensorless control method to estimate motor parameters, such as inductances. The effectiveness of the proposed methods is verified by some simulations and experiments.

Parameter Estimation of Three-Phase Induction Motor by Using Genetic Algorithm

  • Jangjit, Seesak;Laohachai, Panthep
    • Journal of Electrical Engineering and Technology
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    • 제4권3호
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    • pp.360-364
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    • 2009
  • This paper suggests the techniques in determining the values of the steady-state equivalent circuit parameters of a three-phase induction machine using genetic algorithm. The parameter estimation procedure is based on the steady-state phase current versus slip and input power versus slip characteristics. The propose estimation algorithm is of non-linear kind based on selection in genetic algorithm. The machine parameters are obtained as the solution of a minimization of objective function by genetic algorithm. Simulation shows good performance of the propose procedures.

새로운 유도전동기의 파라미터 추정에 관한 연구 (A Study on the New Parameter Estimation of Induction Motor)

  • 이동국;오세진;김종수;김경호;김성환
    • 한국마린엔지니어링학회:학술대회논문집
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    • 한국마린엔지니어링학회 2005년도 후기학술대회논문집
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    • pp.47-48
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    • 2005
  • This paper describes how an Artificial Neural Network(ANN) can be employed to improve a speed estimation in a vector controlled induction motor drive. The system uses the ANN to estimate changes in the motor resistance, which enable the sensorless speed control method to work more accurately. Flux Observer is used for speed estimation in this system. Obviously the accuracy of the speed control of motor is dependent upon how well the parameters of the induction machine are known. These parameters vary with the operating conditions of the motor; both stator resistance(Rs) and rotor resistance(Rr) change with temperature, while the stator leakage inductance varies with load. This paper proposes a parameter compensation technique using artificial neural network for accurate speed estimation of induction motor and simulation results confirm the validity of the proposed scheme.

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Brushless DC Motor의 제어 파라미터 추정과 안정도향상 (The Parameter Estimation and Stability Improvement of the Brushless DC Motor)

  • 김철진;임태빈
    • 대한전기학회논문지:전기기기및에너지변환시스템부문B
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    • 제48권3호
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    • pp.131-138
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    • 1999
  • Generally, the digital controller has many advantages such as high precision, robustness to electrical noise, capability of flexible programming and fast response to the load variation. In this study, we have established proper mathematical equivalent model of Brushless DC (BLDC) motor and estimated the motor parameter by means of the back-emf measurement as being the step input to the controlled target BLDC motor. And the validity of proposed estimation method is confirmed by the test result of step response. As well, we have designed the reasonable digital controller as a consequence of the root locus method which is obtained from the open-loop transfer function of BLDC motor with hall sensor, and the determination of control gain for variable speed control. Here, revised Ziegler-Nichols tuning method is applied for the proper digital gain establishment, and the system stability is verified by the frequency domain analysis with Bode-plot and experimentation.

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Speed and Flux Estimation for an Induction Motor Using a Parameter Estimation Technique

  • Lee Gil-Su;Lee Dong-Hyun;Yoon Tae-Woong;Lee Kyo-Beum;Song Joong-Ho;Choy Ick
    • International Journal of Control, Automation, and Systems
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    • 제3권1호
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    • pp.79-86
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    • 2005
  • In this paper, an estimator scheme for the rotor speed and flux of an induction motor is proposed on the basis of a fourth-order electrical model. It is assumed that only the stator currents and voltages are measurable, and that the stator currents are bounded. There are a number of common terms in the motor dynamics, and this is utilized to find a simple error model involving some auxiliary variables. Using this error model, the state estimation problem is converted into a parameter estimation problem assuming that the rotor speed is constant. Some stability properties are given on the basis of Lyapunov analysis. In addition, the rotor resistance, which varies with the motor temperature, can also be estimated within the same framework. The effectiveness of the proposed scheme is demonstrated through computer simulations and experiments.

Accuracy Enhancement of Parameter Estimation and Sensorless Algorithms Based on Current Shaping

  • Kim, Jin-Woong;Ha, Jung-Ik
    • Journal of Power Electronics
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    • 제16권1호
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    • pp.1-8
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    • 2016
  • Dead time is typically incorporated in voltage source inverter systems to prevent short circuit cases. However, dead time causes an error between the output voltage and reference voltage. Hence, voltage equation-based algorithms, such as motor parameter estimation and back electromotive force (EMF)-based sensorless algorithms, are prone to estimation errors. Several dead-time compensation methods have been developed to reduce output voltage errors. However, voltage errors are still common in zero current crossing areas, and an effect of the error is much worse in a low speed region. Therefore, employing voltage equation-based algorithms in low speed regions is difficult. This study analyzes the conventional dead-time compensation method and output voltage errors in low speed operation areas. A current shaping method that can reduce output voltage errors is also proposed. Experimental results prove that the proposed method reduces voltage errors and improves the accuracy of the parameter estimation method and the performance of the back EMF-based sensorless algorithm.

신경회로망을 이용한 유도전동기의 파라미터 보상 (The Parameter Compensation Technique of Induction Motor by Neural Network)

  • 김종수;오세진;김성환
    • Journal of Advanced Marine Engineering and Technology
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    • 제30권1호
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    • pp.169-175
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    • 2006
  • This paper describes how an Artificial Neural Network(ANN) can be employed to improve a speed estimation in a vector controlled induction motor drive. The system uses the ANN to estimate changes in the motor resistance, which enable the sensorless speed control method to work more accurately. Flux Observer is used for speed estimation in this system. Obviously the accuracy of the speed control of motor is dependent upon how well the parameters of the induction machine are known. These parameters vary with the operating conditions of the motor; both stator resistance(Rs) and rotor resistance(Rr) change with temperature, while the stator leakage inductance varies with load. This paper proposes a parameter compensation technique using artificial neural network for accurate speed estimation of induction motor and simulation results confirm the validity of the proposed scheme.