Current Sensor Fault-Tolerant Control for Speed-Sensorless Induction Motor Drives Based on the SEPLL Current Reconstruction Scheme

Zuo, Yun; Ge, Xinglai; Chang, Yu; Chen, Yuexuan; Xie, Dong; Wang, Huimin; Woldegiorgis, Abebe Teklu

doi:10.1109/tia.2022.3204733

Cited by 18 publications

(11 citation statements)

References 36 publications

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“…Based on LO equations, the amplitude of the second current vector based on the virtual current signal and the amplitude of the third current vector based on the reference speed are calculated by (10)…”

Section: Fault-tolerant Controlmentioning

confidence: 99%

Fault-Tolerant Control Based on Current Space Vectors against Total Sensor Failures

Tran,

Kuchar,

Sotola

et al. 2024

Sensors

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This paper proposes a fault-tolerant control (FTC) strategy using the current space vectors to diagnose sensor failures and enhance the sustained operation of a field-oriented (FO) controlled induction motor drive (IMD). Three space vectors are established for the sensor fault diagnosis technique, including one converted from the measured currents and the other two calculated from the current estimation technique, respectively, measured and with reference speeds. A mixed mathematical model using three space vectors and their components is proposed to accurately determine the fault condition of each sensor in the motor drive. After determining the operating status of each sensor, if the sensor signal is in good condition, the feedback signal to the controller will be the measured signal; otherwise, the estimated signal will be used instead of the failed signal. Failure states of the various sensors were simulated to check the effectiveness of the proposed technique in the Matlab/Simulink environment. The simulation results are positive: the IMD system applying the proposed FTC technique accurately detected the failed sensor and maintained stability during the operation.

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Section: Fault-tolerant Controlmentioning

confidence: 99%

Fault-Tolerant Control Based on Current Space Vectors against Total Sensor Failures

Tran,

Kuchar,

Sotola

et al. 2024

Sensors

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“…According to the type of diagnostic objects, these methods can be divided into two categories: single-sensor fault diagnosis and joint fault diagnosis of multiple types of sensors. Regarding single-sensor faults, current sensor faults are diagnosed using different methods, including current estimation [7], a phase-locked loop-based current reconstruction technique [8], an adaptive observer [9], and a sliding-mode observer [10]. In terms of motor speed or position sensors, diagnostic methods have been proposed based on q-axis current fault characteristics' analysis [11], look-up table [12], Kalman filter [13], and the speed estimation model [14].…”

Section: Introductionmentioning

confidence: 99%

Real-Time Multi-Sensor Joint Fault Diagnosis Method for Permanent Magnet Traction Drive Systems Based on Structural Analysis

Gan,

Li,

Wei

et al. 2024

Sensors

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Sensor faults are one of the most common faults that cause performance degradation or functional loss in permanent magnet traction drive systems (PMTDSs). To quickly diagnose faulty sensors, this paper proposes a real-time joint diagnosis method for multi-sensor faults based on structural analysis. Firstly, based on limited monitoring signals on board, a structured model of the system was established using the structural analysis method. The isolation and detectability of faulty sensors were analyzed using the Dulmage–Mendelsohn decomposition method. Secondly, the minimum collision set method was used to calculate the minimum overdetermined equation set, transforming the higher-order system model into multiple related subsystem models, thereby reducing modeling complexity and facilitating system implementation. Next, residual vectors were constructed based on multiple subsystem models, and fault detection and isolation strategies were designed using the correlation between each subsystem model and the relevant sensors. The validation results of the physical testing platform based on online fault data recordings showed that the proposed method could achieve rapid fault detection and the localization of multi-sensor faults in PMTDS and had a good application value.

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“…Several CS fault compensation methods are proposed in the literature [5][6][7][8][9][10][11][12][13][14][15]. Their characteristics are summarized in Table 1.…”

Section: Introductionmentioning

confidence: 99%

“…Their characteristics are summarized in Table 1. [5] asymmetry index method, [6] axes transformation method, [7] multiple observers, [8] SEPLL + sliding mode observer, [9] Luenberger observer, [10,11] adaptive observer, [12] VCS, [13] flux-based state observer, [14] flux-based EKF, [15] state observer with resistance adaptation.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Compensation of Current Sensor Faults in Vector-Controlled Induction Motor Drive Using Extended Kalman Filters

Orlowska-Kowalska,

Miniach,

Adamczyk

2024

Electronics

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In electric drive systems, one of the most common faults is related to measurement equipment, including current sensors (CSs). As information about the stator current is crucial to ensure precise control of AC drives, such a fault significantly affects the quality and security of the entire system. For this reason, a modified extended Kalman filter (EKF) has been presented in this paper as an algorithmic solution to restore stator current in the event of CS failure. In order to minimize the impact of rotor and stator resistance variations on the quality of the estimation, the proposed model includes an estimation of the general coefficient of their changes. In contrast to solutions known in the literature, the presented model considers changes in both resistances in the form of a single coefficient. This approach allows us to maintain a low order of the estimator (fifth) and thus minimize the tendency to system instability and decrease computation burden. Extensive simulation tests have shown a significant improvement in the accuracy of stator current estimation under both motor and regenerating modes, a wide speed range (1–100%), and changes in motor parameters.

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Current Sensor Fault-Tolerant Control for Speed-Sensorless Induction Motor Drives Based on the SEPLL Current Reconstruction Scheme

Cited by 18 publications

References 36 publications

Fault-Tolerant Control Based on Current Space Vectors against Total Sensor Failures

Fault-Tolerant Control Based on Current Space Vectors against Total Sensor Failures

Real-Time Multi-Sensor Joint Fault Diagnosis Method for Permanent Magnet Traction Drive Systems Based on Structural Analysis

Compensation of Current Sensor Faults in Vector-Controlled Induction Motor Drive Using Extended Kalman Filters

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