Publicado

2019-01-01

Continuous Estimation of Speed and Torque of Induction Motors Using the Unscented Kalman Filter under Voltage Sag

La estimación continúa de la velocidad y torque de un motor de inducción usando el filtro de Kalman sin perfume bajo huecos de tensión

DOI:

https://doi.org/10.15446/dyna.v86n208.65567

Palabras clave:

Unscented Kalman filter, Extended Kalman filter, Sensorless control, Induction motor, Induction motor parameter estimation (en)

Autores/as

Due to sensor limitations in some applications, induction motors state estimators are widely used in industries. One of the most powerful tools available for estimation is the Kalman filter. In this paper, unscented Kalman filter (UKF) and extended Kalman filter (EKF) is used to estimate the speed and torque of an induction motor. In the UKF algorithm, three types of unscented transformation (UT): basic, general and spherical types are presented and compared. It will be shown that the spherical UKF presents good estimation performance. Speed and torque Estimation approach is applied at both steady state conditions and at the time of sudden and rapid change in the motor input voltage. It will be shown that, EKF cannot trace the motor speed at the time of a large disturbance. Finally, experimental validation is presented to show the effectiveness of UKF for continuous estimation of torque and speed of induction motors.

Como se veía las limitaciones en los sensores en algunas aplicaciones, los motores asíncronos estimadores de estado ya son ampliamente utilizados en las industrias. Una de las herramientas disponibles y más potentes es el filtro de Kalman. En el presente artículo el Filtro de Kalman Unscented (UKF en siglas en inglés) y el Filtro de Kalman Extendido(EKF) se usan para estimación de la velocidad y el par motor o torque de un motor de inducción. En el algoritmo de UKF, hay 3 tipos de la transformación “unscented” que son presentados y comparados: Basica, general y esférica. Se muestra en ese artículo que el UKF esférico presentará una buena estimación. En materia de la estimación de la velocidad y el par motor, que son aplicados tanto en condiciones que están en estado estacionario como en los cambios repentinos y rápidos en el voltaje de entrada del motor. Y además va a mostrar que el EKF no es capaz de rastrear la velocidad del motor en el momento cuando hay una larga perturbación. Por último, la validación experimental es presentada para mostrar la eficacia del UKF de forma continua en la estimación del par motor y la velocidad de los motores asíncronos.

Referencias

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Cómo citar

IEEE

[1]
A. Darvishi y A. Doroudi, «Continuous Estimation of Speed and Torque of Induction Motors Using the Unscented Kalman Filter under Voltage Sag», DYNA, vol. 86, n.º 208, pp. 37–45, ene. 2019.

ACM

[1]
Darvishi, A. y Doroudi, A. 2019. Continuous Estimation of Speed and Torque of Induction Motors Using the Unscented Kalman Filter under Voltage Sag. DYNA. 86, 208 (ene. 2019), 37–45. DOI:https://doi.org/10.15446/dyna.v86n208.65567.

ACS

(1)
Darvishi, A.; Doroudi, A. Continuous Estimation of Speed and Torque of Induction Motors Using the Unscented Kalman Filter under Voltage Sag. DYNA 2019, 86, 37-45.

APA

Darvishi, A. & Doroudi, A. (2019). Continuous Estimation of Speed and Torque of Induction Motors Using the Unscented Kalman Filter under Voltage Sag. DYNA, 86(208), 37–45. https://doi.org/10.15446/dyna.v86n208.65567

ABNT

DARVISHI, A.; DOROUDI, A. Continuous Estimation of Speed and Torque of Induction Motors Using the Unscented Kalman Filter under Voltage Sag. DYNA, [S. l.], v. 86, n. 208, p. 37–45, 2019. DOI: 10.15446/dyna.v86n208.65567. Disponível em: https://revistas.unal.edu.co/index.php/dyna/article/view/65567. Acesso em: 24 mar. 2026.

Chicago

Darvishi, Amin, y Aref Doroudi. 2019. «Continuous Estimation of Speed and Torque of Induction Motors Using the Unscented Kalman Filter under Voltage Sag». DYNA 86 (208):37-45. https://doi.org/10.15446/dyna.v86n208.65567.

Harvard

Darvishi, A. y Doroudi, A. (2019) «Continuous Estimation of Speed and Torque of Induction Motors Using the Unscented Kalman Filter under Voltage Sag», DYNA, 86(208), pp. 37–45. doi: 10.15446/dyna.v86n208.65567.

MLA

Darvishi, A., y A. Doroudi. «Continuous Estimation of Speed and Torque of Induction Motors Using the Unscented Kalman Filter under Voltage Sag». DYNA, vol. 86, n.º 208, enero de 2019, pp. 37-45, doi:10.15446/dyna.v86n208.65567.

Turabian

Darvishi, Amin, y Aref Doroudi. «Continuous Estimation of Speed and Torque of Induction Motors Using the Unscented Kalman Filter under Voltage Sag». DYNA 86, no. 208 (enero 1, 2019): 37–45. Accedido marzo 24, 2026. https://revistas.unal.edu.co/index.php/dyna/article/view/65567.

Vancouver

1.
Darvishi A, Doroudi A. Continuous Estimation of Speed and Torque of Induction Motors Using the Unscented Kalman Filter under Voltage Sag. DYNA [Internet]. 1 de enero de 2019 [citado 24 de marzo de 2026];86(208):37-45. Disponible en: https://revistas.unal.edu.co/index.php/dyna/article/view/65567

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CrossRef citations1

1. Peng Yu, Shunli Wang, Chunmei Yu, Cong Jiang, Weihao Shi. (2022). An adaptive fractional‐order extended Kalman filtering for state of charge estimation of high‐capacity lithium‐ion battery. International Journal of Energy Research, 46(4), p.4869. https://doi.org/10.1002/er.7480.

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