EPE Association: EPE 2003 - Topic 07e: Estimation Techniques

EPE 2003 - Topic 07e: Estimation Techniques
You are here: EPE Documents > 01 - EPE & EPE ECCE Conference Proceedings > EPE 2003 - Conference > EPE 2003 - Topic 07: MEASUREMENTS AND SENSORS > EPE 2003 - Topic 07e: Estimation Techniques

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   Estimation of magnetic flux at low frequencies
By E. Etien; L. Rambault [View]
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Abstract: This paper deals with the use of hysteresis modeling in order to estimate the flux in a magnetic circuit at low frequencies.The cycle stationarity in low frequencies is shown and a closed loop method is presented to model it. Experimental results are proposed in the case of an single phase transformer.

   A boot-strap estimator for joint flux and parameters online identification for vector controlled induction motor drives
By V. Leite; R. Araújo; D. Freitas [View]
[Download]

Abstract: This paper presents a new approach for joint rotor flux and electrical parameters on-line identification in vector controlled high-performance induction motor drives based on a boot-strap estimator that uses a reduced order extended Kalman filter for rotor flux components and rotor parameters estimation and a recursive prediction error method for stator parameters estimation. Within the prediction error method some approaches are used and compared that affect both the adaptation gain and the direction in which the updates of stator parameters are made. The induction motor model structures are described in the rotor reference frame in order to reduce the computational effort by using a higher sampling time interval.

   Towards a sensorless current and temperature monitoring in MOSFET-based H-bridge
By C. Buttay; D. Bergogne; H. Morel; B. Allard; R. Ehlinger; P. Bevilacqua [View]
[Download]

Abstract: This paper describes a method to extract internal temperature and drain current values of a MOS transistor by proceeding to voltages acquisitions only. Two current and temperature dependant voltages are measured: the drain-to-source voltage when the MOSFET is in the linear state, and the body diode forward voltage drop when freewheeling. Analytical expression are proposed to estimate temperature and current values from the voltages measurements. The method is then implemented in a microcontroller to achieve a low cost monitoring system. Accuracy of the system is verified, and confidence maps over the full working range of the devices are given. An application to chip-to-ambient thermal impedance measurement using the estimator and a calorimeter is proposed.

   Sensitivity analysis of state variable estimators of two-mass drive system
By T. Or³owska-Kowalska; K. Szabat [View]
[Download]

Abstract: The paper deals with the comparison of two estimation methods for torsional torque, load speed and disturbance torque reconstruction based on the Luenberger observer and Kalman filter for two-mass drive system. Estimation errors caused by the drive parameter changes were checked and compared. Due to a lack of analytical methods for gain matrices design for such estimators, parameters of both estimators were optimised using the same genetic-gradient algorithm and the same optimisation index. Such procedure has enabled the detailed comparison of results obtained for these two state estimators, based on simulation and experimental tests.

   Input preprocessing in tapped delay neural architecture for induction motor speed estimation
By L. M. Grzesiak; B. Beliczynski; B. Ufnalski [View]
[Download]

Abstract: Tapped delay neural architecture with input preprocessing for induction motor speed estimation is analysed. We start with a typical set of easily measurable electrical signals and demonstrate that a nonlinear input peprocessing is needed with possibly more outputs than inputs. When sufficiently many linearly independant variables are generated through that preprocessing, one may reduce number of delays in this architecture even to zero. Laboratory results are reported.

   Real-time thermal monitoring of an induction machine by an extended Kalman filter using electrical and thermal models
By E. Foulon; L. Loron; F. Auger [View]
[Download]

Abstract: This paper presents a real-time temperature monitoring technique for the induction machine. The proposed method is based on the estimation of the stator and rotor electrical resistances by an extended Kalman filter. To avoid the observability problems of the electrical model, we propose to add a thermal model of the machine. An instrumented test board is presented and the difficulties of the identification of the thermal model are discussed. The first experimental results show the efficiency of the extended Kalman filter when the sensitivity of the stator and rotor resistances is sufficient (low speed and high torque). They also show the necessity to use an adequate thermal model to increase the accuracy of the temperature estimations.

   Induction machine parameter estimation errors due to model uncertainties
By E. Laroche; S. Moreau [View]
[Download]

Abstract: Validating an identification procedure requires that, for the selected model and the selected measurement campaign, parameter estimation errors remain low. In this paper is applied a method for evaluating parameter estimation errors of an induction machine due to modelling uncertainties, in the case of a dynamical identification procedure. The study covers the cases of magnetic saturation, iron loss and inverter effects such as PWM and dead-times, in the case of a 4-parameter dynamical model. Several trajectories are considered, allowing evaluating their effects on estimation errors.

EPE 2003 - Topic 07e: Estimation Techniques
You are here: EPE Documents > 01 - EPE & EPE ECCE Conference Proceedings > EPE 2003 - Conference > EPE 2003 - Topic 07: MEASUREMENTS AND SENSORS > EPE 2003 - Topic 07e: Estimation Techniques
	[return to parent folder]

	Estimation of magnetic flux at low frequencies By E. Etien; L. Rambault	[View] [Download]
Abstract: This paper deals with the use of hysteresis modeling in order to estimate the flux in a magnetic circuit at low frequencies.The cycle stationarity in low frequencies is shown and a closed loop method is presented to model it. Experimental results are proposed in the case of an single phase transformer.

	A boot-strap estimator for joint flux and parameters online identification for vector controlled induction motor drives By V. Leite; R. Araújo; D. Freitas	[View] [Download]
Abstract: This paper presents a new approach for joint rotor flux and electrical parameters on-line identification in vector controlled high-performance induction motor drives based on a boot-strap estimator that uses a reduced order extended Kalman filter for rotor flux components and rotor parameters estimation and a recursive prediction error method for stator parameters estimation. Within the prediction error method some approaches are used and compared that affect both the adaptation gain and the direction in which the updates of stator parameters are made. The induction motor model structures are described in the rotor reference frame in order to reduce the computational effort by using a higher sampling time interval.

	Towards a sensorless current and temperature monitoring in MOSFET-based H-bridge By C. Buttay; D. Bergogne; H. Morel; B. Allard; R. Ehlinger; P. Bevilacqua	[View] [Download]
Abstract: This paper describes a method to extract internal temperature and drain current values of a MOS transistor by proceeding to voltages acquisitions only. Two current and temperature dependant voltages are measured: the drain-to-source voltage when the MOSFET is in the linear state, and the body diode forward voltage drop when freewheeling. Analytical expression are proposed to estimate temperature and current values from the voltages measurements. The method is then implemented in a microcontroller to achieve a low cost monitoring system. Accuracy of the system is verified, and confidence maps over the full working range of the devices are given. An application to chip-to-ambient thermal impedance measurement using the estimator and a calorimeter is proposed.

	Sensitivity analysis of state variable estimators of two-mass drive system By T. Or³owska-Kowalska; K. Szabat	[View] [Download]
Abstract: The paper deals with the comparison of two estimation methods for torsional torque, load speed and disturbance torque reconstruction based on the Luenberger observer and Kalman filter for two-mass drive system. Estimation errors caused by the drive parameter changes were checked and compared. Due to a lack of analytical methods for gain matrices design for such estimators, parameters of both estimators were optimised using the same genetic-gradient algorithm and the same optimisation index. Such procedure has enabled the detailed comparison of results obtained for these two state estimators, based on simulation and experimental tests.

	Input preprocessing in tapped delay neural architecture for induction motor speed estimation By L. M. Grzesiak; B. Beliczynski; B. Ufnalski	[View] [Download]
Abstract: Tapped delay neural architecture with input preprocessing for induction motor speed estimation is analysed. We start with a typical set of easily measurable electrical signals and demonstrate that a nonlinear input peprocessing is needed with possibly more outputs than inputs. When sufficiently many linearly independant variables are generated through that preprocessing, one may reduce number of delays in this architecture even to zero. Laboratory results are reported.

	Real-time thermal monitoring of an induction machine by an extended Kalman filter using electrical and thermal models By E. Foulon; L. Loron; F. Auger	[View] [Download]
Abstract: This paper presents a real-time temperature monitoring technique for the induction machine. The proposed method is based on the estimation of the stator and rotor electrical resistances by an extended Kalman filter. To avoid the observability problems of the electrical model, we propose to add a thermal model of the machine. An instrumented test board is presented and the difficulties of the identification of the thermal model are discussed. The first experimental results show the efficiency of the extended Kalman filter when the sensitivity of the stator and rotor resistances is sufficient (low speed and high torque). They also show the necessity to use an adequate thermal model to increase the accuracy of the temperature estimations.

	Induction machine parameter estimation errors due to model uncertainties By E. Laroche; S. Moreau	[View] [Download]
Abstract: Validating an identification procedure requires that, for the selected model and the selected measurement campaign, parameter estimation errors remain low. In this paper is applied a method for evaluating parameter estimation errors of an induction machine due to modelling uncertainties, in the case of a dynamical identification procedure. The study covers the cases of magnetic saturation, iron loss and inverter effects such as PWM and dead-times, in the case of a 4-parameter dynamical model. Several trajectories are considered, allowing evaluating their effects on estimation errors.