Design and performance analysis of an iterative flux sliding-mode observer for the sensorless control of PMSM drives

Ye, Shuaichen

doi:10.1016/j.isatra.2019.04.009

Cited by 43 publications

(12 citation statements)

References 32 publications

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“…At present, the interior PMSM is used widely in industrial engineering. Many automotive companies such as Daimler, Toyota, and BYD have widely applied interior PMSM to their electric automobile [3,4].…”

Section: Introductionmentioning

confidence: 99%

Optimization Analysis of Automotive Asymmetric Magnetic Pole Permanent Magnet Motor by Taguchi Method

Zhang

Shi

Liu

et al. 2021

International Journal of Rotating Machinery

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In order to improve the air-gap flux density of the permanent magnet synchronous motor and reduce the cogging torque, a novel structure with asymmetric magnetic poles for automobile was proposed. Based on the characteristics of the parallel magnetic circuit, the magnetic flux path diagram is established. And the equivalent magnetic circuit model is established by the equivalent magnetic circuit method. The Taguchi method is used to be a multiobjective optimization algorithm. The total harmonic distortion of the air-gap flux density is the first optimization goal. The second and third optimization goals are the cogging torque and the average of output torque, respectively. And the torque ripple is a constraint condition. The optimized parameter combination is obtained by the Taguchi method. Finite element simulation analysis and prototype test are carried out for the optimized motor structure. The results show that the total harmonic distortion of air-gap flux density is reduced by 36.7% comparing with the initial structure. The cogging torque is reduced by 26.0%. And the average output torque is increased by 4.8%.

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Section: Introductionmentioning

confidence: 99%

Optimization Analysis of Automotive Asymmetric Magnetic Pole Permanent Magnet Motor by Taguchi Method

Zhang

Shi

Liu

et al. 2021

International Journal of Rotating Machinery

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“…7,8 And the sliding mode observer is also used well for estimation due to its simplicity and good stability. [9][10][11][12] In the methods using the model the accuracy of estimation is related to the accuracy of the model. Therefore, the schemes to carry out the online parameter estimation 13,14 and adaptive algorithm 15,16 are studied.…”

Section: Introductionmentioning

confidence: 99%

Sensorless vector control of permanent magnetic synchronous motor with parameter error compensation

Pak

Kang

2021

Int Trans Electr Energ Syst

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The position sensorless vector control of permanent magnetic synchronous motor is the method that implements the vector control by estimating the rotor position from the motor model in the basis of the voltage and the current signal of the motor without measuring the motor position directly. The sensorless vector control is divided into two methods: estimating the rotor position based on the stationary reference frame and rotational reference frame. This article presents the research results of more improved estimation performance by combining these two methods. First, we estimate the rotor position by using the open-loop estimation algorithm based on the stationary reference frame, evaluate the estimation error based on the model from the rotational reference frame and compensate the estimate in a feedback way with differences from the current measurements. At the same time, we also take the parameter errors included in the model into account. This article performed the experiment for the parameter identification and for the sensorless vector control, and demonstrated its effectiveness.

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“…However, these methods are not applicable for non-linear estimation systems. In order to overcome this drawback, several observers were presented in the previously reported works [12][13][14][15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Position and Speed Estimation of PMSM Based on Extended Kalman Filter Tuned by Biogeography-Based-Optimization

Allaoui¹,

Laamari²,

Chafaa³

et al. 2021

JESA

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In a sensorless control of PMSM based on Extended Kalman Filter (EKF), the correct selection of system and measurement noise covariance has a great influence on the estimation performances of the filter. In fact, it is extremely difficult to find their optimal values by trial and error method. Therefore, the main contribution of this work is to prove the efficiency of Biogeography-Based-Optimization (BBO) technique to obtain the optimal noise covariance matrices Q and R. The BBO and EKF combination gives a BBO-EKF algorithm, which allows to estimate all the state variables of PMSM drive particularly, the rotor position and speed. In this paper, three evolutionary algorithms namely Particle Swarm Optimization (PSO), genetic algorithms (GAs) and BBO are used to get the best Q and R of EKF. Simulations tests performed in Matlab Simulink environment show excellent performance of BBO-EKF compared to GAs-EKF and PSO-EKF approaches either in resolution or in convergence speed.

show abstract

Design and performance analysis of an iterative flux sliding-mode observer for the sensorless control of PMSM drives

Cited by 43 publications

References 32 publications

Optimization Analysis of Automotive Asymmetric Magnetic Pole Permanent Magnet Motor by Taguchi Method

Optimization Analysis of Automotive Asymmetric Magnetic Pole Permanent Magnet Motor by Taguchi Method

Sensorless vector control of permanent magnetic synchronous motor with parameter error compensation

Position and Speed Estimation of PMSM Based on Extended Kalman Filter Tuned by Biogeography-Based-Optimization

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