Model Predictive Current Control for PMSM Drives With Calculation Delay Compensation

Zhuang, Yujia; Du, Quankai; Huang, Wenjie; Wang, Zhixin; Wang, Rongkun

doi:10.1109/cieec54735.2022.9846144

Cited by 2 publications

(2 citation statements)

References 13 publications

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“…2) Evaluation of the percental speed gain: An overview of the calculated time lags according to (15) is provided in table IV. For a speed of 1000 rpm, the determined lags and TABLE III: The mean (µ), standard deviation (σ), signal-to-noise ratio (SN R), and the min/max instantaneous value of the error signal ϵ resulting from the difference between the estimated and measured load angles for a torque jump at different speeds depending on the used comb filter.…”

Section: B Validation Of the Influence Of The Comb Filter M-factor On...mentioning

confidence: 99%

“…On the other hand, the observer-based methods do not require additional investment in hardware and function well starting from mid-speed range but become unstable and thus less reliable at lower speeds [14]. Moreover, to control the motor dynamically enough, difficultto-estimate application-dependent parameters such as damping and inertia are required, which complicates the applicability [15], [8]. As summarized by [8], both control principles remain vulnerable to external disturbances despite continuous efforts to improve control performance.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic Load Angle Estimation Through an Angular Domain GDFT Filter for Optimal Energetic BLDC Control

Ceulemans

Viaene

Steckel

et al. 2022

IEEE/ASME Trans. Mechatron.

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These days, BLDC motors are increasingly used to drive speed-controlled applications (e.g., drones, air compressors, etc.) thanks to their high power density, good torque inertia ratio, and their simple square wave commutation principle. However, with growing attention towards energy usage, a more efficient sinusoidal current wave is favored over the classical square wave profile. Nevertheless, changing the waveform to absent the silence phase implicates that simple control principles (e.g., hallsensors or back-EMF tracing) are no longer functional, and a more advanced sensorless solution is required. Earlier, an innovative sensorless load-angle-based controller was suggested with the potential to overcome all restrictions concerning stateof-the-art sensorless control. One of the proposed estimator's fundamental building blocks is a sliding discrete Fourier filter (SDFT), requiring both a signal with a fixed base frequency and a full signal period of samples before updating completely. Both requirements severely limit the application field. This paper presents an enhanced load angle estimator that can estimate the load angle 66% faster on average and without quality deterioration, regardless of the rotor speed. Both speed and accuracy of the estimated load angle are validated based on BLDC-measurements, confirming the potential and revealing possible further estimation lag decreases if a limited estimation quality regression is allowed.

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Section: B Validation Of the Influence Of The Comb Filter M-factor On...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dynamic Load Angle Estimation Through an Angular Domain GDFT Filter for Optimal Energetic BLDC Control

Ceulemans

Viaene

Steckel

et al. 2022

IEEE/ASME Trans. Mechatron.

View full text Add to dashboard Cite

show abstract

Predictive Current Control for Permanent Magnet Synchronous Motor Based on Delay Compensation and Parameter Identification

Gu,

Bu,

Dong

2023

2023 26th International Conference on Electrical Machines and Systems (ICEMS)

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Model Predictive Current Control for PMSM Drives With Calculation Delay Compensation

Cited by 2 publications

References 13 publications

Dynamic Load Angle Estimation Through an Angular Domain GDFT Filter for Optimal Energetic BLDC Control

Dynamic Load Angle Estimation Through an Angular Domain GDFT Filter for Optimal Energetic BLDC Control

Predictive Current Control for Permanent Magnet Synchronous Motor Based on Delay Compensation and Parameter Identification

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