Low-Complexity Model Predictive Torque Control Method Without Weighting Factor for Five-Phase PMSM Based on Hysteresis Comparators

Wu, Xuesong; Song, Wensheng; Cheng, Xian-Chao

doi:10.1109/jestpe.2018.2849320

Cited by 64 publications

(23 citation statements)

References 28 publications

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“…From these results, it is important to emphasize that the stator resistance and PM flux linkage variations have a low effect over the diagnostic variables, and their errors can be neglected, indeed [45–47]. Hence, the variation of the stator inductance L has a more important impact, than the uncertainty on the stator resistance R and PM flux linkage ψ r on the fault diagnostic variable χ .…”

Section: Proposed Fault Diagnostics Methods Using Predictive Current Errorsmentioning

confidence: 92%

Open‐switch fault diagnosis in voltage source inverters of PMSM drives using predictive current errors and fuzzy logic approach

Gmati

Jlassi

Khil

et al. 2021

IET Power Electronics

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In critical industrial applications fault diagnosis and fault tolerance are considered key features, in order to ensure the required reliability and availability levels. In this context, this paper proposes a new and effective diagnostic algorithm for power semiconductors opencircuit faults, in three-phase, two-level, voltage-source inverter-fed permanent magnet synchronous machine (PMSM). The proposed method is based on the analysis of the errors between the reference currents and the PMSM stator predictive currents. Hence, for each phase of the PMSM two fault diagnostic variables have been defined, which allow the diagnosis of both single and multiple open-circuit faults. The fuzzy logic approach is applied to the fault diagnostic variables in order to identify the faulty power switches. The method is experimentally validated on a model predictive controlled (MPC) permanent magnet synchronous motor (PMSM) drive, which shows the effectiveness of the fault diagnosis algorithm with a high robustness regarding the operating point and parameter variations of the PMSM drive system. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Proposed Fault Diagnostics Methods Using Predictive Current Errorsmentioning

confidence: 92%

Open‐switch fault diagnosis in voltage source inverters of PMSM drives using predictive current errors and fuzzy logic approach

Gmati

Jlassi

Khil

et al. 2021

IET Power Electronics

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show abstract

“…To eliminate the weighting factor, in [30], voltage vector, which is calculated by using the model of torque and stator flux is used in the cost function. In [31], a virtual vector that is calculated by using the model of motor is used in the cost function to control motor, and two hysteresis comparators are used to determine which virtual vector to use. In [32], new reference stator flux is calculated by using torque and stator flux to eliminate torque in the cost function from the conventional method.…”

Section: Previous Researches To Avoid the Weighting Factormentioning

confidence: 99%

“…In order for (30) and (31) to satisfy (25), must be larger than zero. The three-phase output current flow in the two cases is shown in Fig.…”

Section: B Capacitor Voltage Control Algorithm Using Offset Voltage mentioning

confidence: 99%

Model Predictive Control Method With NP Voltage Balance by Offset Voltage Injection for Three-Phase Three-Level NPC Inverter

2020

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This paper proposes a predictive control method with offset voltage injection for achieving a neutral point (NP) voltage balance of three-phase three-level neutral point clamped (NPC) inverter, without employing a weighting factor. In order to ensure the proper and reliable operation of the NPC inverter, the NP voltage balance should be regulated in addition to the sinusoidal output current. The conventional predictive control methods for NPC has suffered from tedious weighting factor selection. Besides, when the converter's parameters value and control condition changes, it is cumbersome to empirically redesign the weighting factor. Therefore, the proposed predictive control method without the weighting factor can successfully maintain the balance of NP voltage by utilizing an offset voltage, which is determined according to the difference between the upper and lower capacitor voltages. As a result, the proposed algorithm using the offset voltage injection can control the output currents and maintain the balance of NP voltage. Simulation and experiments are presented to prove the validity of the NP voltage balancing of the proposed control method. INDEX TERMS neutral point clamped (NPC) inverter, predictive control method, neutral point (NP) voltage balance, offset voltage injection

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“…In [29–33], Xue et al , Goncalves et al , Wang et al , Gonzalez et al and Wu et al present MPC based on virtual VVs to reduce computational time. A set of virtual VVs are used to replace the traditional VVs.…”

Section: Introductionmentioning

confidence: 99%

Computationally efficient model predictive control of three‐level open‐end winding permanent‐magnet synchronous motor drive

Petkar

Kumar

2020

IET Electric Power Applications

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The model predictive current control (MPCC) is popular and widely used method for permanent‐magnet synchronous motor (PMSM) and the tuning of weighting factor in classical cost function (CF) of MPCC of PMSM is not required. A three‐level inversion‐fed open‐end winding PMSM (OEW‐PMSM) would produce lesser torque and stator flux ripples; however, computation time required for the prediction of control variables is large. This study proposes a control method to three‐level inversion‐fed OEW‐PMSM for reduction of computational time without affecting the performance when compared with conventional MPCC. The proposed method uses a maximum four voltage vectors (VVs) instead of 19 VVs in three‐level conventional MPCC. The reduced VVs decrease the number of predictions and computational time for predictions. CF in terms of voltage is used, thereby eliminating the need to predict the currents and faster execution of algorithm is achieved. A higher sampling rate is possible to achieve using the proposed method; thereby, reducing the steady‐state ripples in developed torque and stator flux, and improving the percentage total harmonic distortion of stator current. The effectiveness of the presented control method is practically verified after comparing its computational time, steady‐state response and dynamic response with that of three‐level conventional MPCC.

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Low-Complexity Model Predictive Torque Control Method Without Weighting Factor for Five-Phase PMSM Based on Hysteresis Comparators

Cited by 64 publications

References 28 publications

Open‐switch fault diagnosis in voltage source inverters of PMSM drives using predictive current errors and fuzzy logic approach

Open‐switch fault diagnosis in voltage source inverters of PMSM drives using predictive current errors and fuzzy logic approach

Model Predictive Control Method With NP Voltage Balance by Offset Voltage Injection for Three-Phase Three-Level NPC Inverter

Computationally efficient model predictive control of three‐level open‐end winding permanent‐magnet synchronous motor drive

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