Saliency-Based Permanent Magnet Machine Position Sensorless Drive Using Proposed PWM Injection and Shunt-Based Current Sensing for Position Estimation

Chen, Jyun-You; Yang, Shih-Chin

doi:10.1109/tie.2020.3000088

Cited by 11 publications

(2 citation statements)

References 27 publications

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“…A position and dq-axis mutual inductance estimation method without previous analyses have been proposed [17], [18]. These results showed the position estimation performance increase and high-frequency velocity vibration reduction.…”

Section: Introductionmentioning

confidence: 93%

Position and Cross-Coupling Factors Estimation for Sliding Mode Current Control Based Position-Sensorless Control of IPMSM

Shimamoto

Murakami

2022

IEEE Access

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This paper presents a control method with an estimation method of cross-coupling factors of Interior Permanent Magnet Synchronous Motors (IPMSM) inductance for position-sensorless servo drive systems. The cross-coupling factors are from dq-axis mutual inductance. Conventionally, the cross-coupling factors have been ignored in the IPMSM model and deteriorate control performance. That has caused decreasing robustness and velocity vibration in the low-speed range. Since the cross-coupling factors vary with the rotor position and the current, it is hard to measure them. Therefore, the proposed method utilizes a high-frequency voltage injection method to estimate the cross-coupling factors online. In addition, the proposed current control method utilizes a sliding mode control and voltage disturbance observer based on the voltage equation, including the dq-axis mutual inductance model. The estimated cross-coupling factors are reflected in the proposed current controller instantaneously. Experimental results show that the proposed method considering cross-coupling factors increases the robustness to the disturbance force and reduces the velocity vibration.

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Section: Introductionmentioning

confidence: 93%

Position and Cross-Coupling Factors Estimation for Sliding Mode Current Control Based Position-Sensorless Control of IPMSM

Shimamoto

Murakami

2022

IEEE Access

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“…The two main methods are based on a high frequency signal injection or a fundamental PWM excitation (FPE). The signal injection methods [3]- [12] employ different patterns of high frequency components (sinusoidal, pulsating,...) which are injected, commonly, through the αβ voltages. That voltages, and their corresponding generated currents, are used to observe the rotor angle using a simplified high frequency saliency motor model.…”

Section: Introductionmentioning

confidence: 99%

Zero Speed Sensorless Scheme for Permanent Magnet Synchronous Machine Under Decoupled Sliding-Mode Control

Repecho

Waqar

Biel

et al. 2022

IEEE Trans. Ind. Electron.

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Position estimation at low/zero speed for permanent magnet synchronous machines is commonly achieved with the injection of high frequency signals. This paper presents a new sensorless scheme that accurately observe the rotor angle at low speeds, including standstill condition, without injecting high frequency signals. The algorithm is built upon a previous sliding mode current controller and uses the switching functions slopes inaccuracies produced by the saliency effect to determine the rotor position and speed. Thanks to the equivalent control concept and together with a sliding mode based PLL observer defined by a complex switching function, the algorithm provides both rotor position and speed in a compact form. The paper includes the main working principle and defines the operational range of the proposed scheme. Finally, the feasibility of the method is corroborated through experimental results in sensorless configuration.

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Improvement of low‐speed sensorless control with multi‐layer neural network

Maekawa

Tanaka

2022

Electrical Engineering Japan

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In recent years, there has been an increasing demand for position sensorless control in Permanent Magnet Synchronous Motor (PMSM) drives, and various methods have been studied. Switching noise is a problem in the low‐speed sensorless control method that uses the current slope during PWM. Furthermore, another problem is that the inductance does not appear in a sinusoidal distribution owing to magnetic saturation. In this paper, we improve the sensorless control method that estimates the position from the current slope during PWM, which is greatly affected by switching. Additionally, we build a multi‐layer neural network (NN) that directly estimates the position signals by learning a large amount of current data, and verify the driving results in the low‐speed range when the learned NN is incorporated into real‐time control.

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Saliency-Based Permanent Magnet Machine Position Sensorless Drive Using Proposed PWM Injection and Shunt-Based Current Sensing for Position Estimation

Cited by 11 publications

References 27 publications

Position and Cross-Coupling Factors Estimation for Sliding Mode Current Control Based Position-Sensorless Control of IPMSM

Position and Cross-Coupling Factors Estimation for Sliding Mode Current Control Based Position-Sensorless Control of IPMSM

Zero Speed Sensorless Scheme for Permanent Magnet Synchronous Machine Under Decoupled Sliding-Mode Control

Improvement of low‐speed sensorless control with multi‐layer neural network

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