Current Sensor Fault Research Articles

Reconstructed Current Model Predictive Control of NPC Three-Level Grid-Tied Converter With Current Sensor Fault

Neutral-point clamped (NPC) three-level grid-tied converter is the key power electronic equipment connecting renewable energy and power grid. High temperature and other factors can lead to current sensor failure, control strategy failure, output current distortion, and even lead to the disconnection of renewable energy. To maintain the normal operation of NPC three-level grid-tied converter with current sensor fault, a model predictive fault-tolerant control strategy based on space voltage vector set and fault phase current reconstruction is proposed. Firstly, the relationship between fault phase current and voltage vector is studied. After the current sensor fault, only 12 out of 27 voltage vectors were found to be able to reconstruct faulty phase currents with a DC current sensor and an AC current sensor. Model predictive current control using the set of these 12 voltage vectors, and fault phase current is directly calculated by DC current and normal phase current, which improves the fault tolerance and stability of the converter system. Finally, simulation and experimental results verified the effectiveness of the proposed method.

A Sign Logic‐Based Method of Current Sensor Fault Detection for PMSM Drivers

A simplified method of current sensor fault detection and isolation (FDI) for permanent magnet synchronous motor (PMSM) drives, which only requires to collect the information of motor positions and currents of the measured phases, has been proposed in this paper. Compared with the classical state‐observer‐based approaches, the calculations needed in the new method only involve a few addition and logical operations. The simplicity and reliability of the new method makes itself especially useful for fault detection of current sensors in real‐time control systems with limited computational capability, e.g., single‐chip microcomputers (SCM) or field programmable gate arrays (FPGA). The experimental results on the basis of a FPGA controller have validated the feasibility and robustness of the proposed FDI approach.

Current sensor fault diagnosis and fault‐tolerant control for single‐phase PWM rectifier based on a hybrid model‐based and data‐driven method

In this study, a hybrid model-based and data-driven method is proposed for the current sensor fault diagnosis used in single-phase pulse width modulation (PWM) rectifier. According to the principle of model-based methods, the proposed diagnostic method is based on signal prediction and residual generation. Differently, instead of a mathematical model, the signal prediction model is developed based on a data-driven method. Non-linear autoregressive exogenous learning model, randomised learning technique, and extreme learning machine are utilised to generate the data-driven prediction model. Once the fault is detected, fault-tolerant control is activated by substituting the predicted signal for the information of faulty sensors. The offline test shows that the proposed method is able to predict the sensor signal accurately with the root mean square error of 4.276 × 10−5. In addition, hardware-in-the-loop tests are conducted to verify the feasibility and reliability of the proposed method in the real-time application.

Maximum Current Estimation Method for the Backup of Current Sensor Faults

Maximum Current Estimation Method for the Backup of Current Sensor Faults

A Novel Speed and Current Sensor Fault-Tolerant Control Based on Estimated Stator Currents in Induction Motor Drives

The paper introduces a novel Fault Tolerant Control (FTC) algorithm based on estimated stator currents to diagnose some faulty states of stator current and speed sensors of Induction Motor (IM) drives. The FTC unit is integrated in the field-oriented control of induction motors to ensure that the IM drive can operate stably when current and speed sensor failures occur. The presented scheme combines two stator current estimators and a rotor speed estimator where a correction coefficient determined from the healthy current sensor is used to enhance the accuracy of the stator current estimation. To verify the capability of the proposed approach, the simulation in MATLAB-Simulink has been accomplished for various conditions of the IM drive, i.e. normal speed, low speed, and very low speed operating ranges. The results have confirmed very good features of the proposed FTC against the current and speed sensor fault in the different speed ranges.

Current sensors fault detection and tolerant control strategy for three-phase induction motor drives

In the case of failure of one or more components of a drive system, the emergency shutdown of the system is not always the best way to act. Therefore, simultaneous reconfiguration of the drive control strategy is mandatory to enable an uninterrupted operation to cater for the catastrophic failure. In this context, this paper presents a current sensors fault-tolerant control method for induction motor drives, based on vector control and currents estimation. Several important issues are considered in the proposed method, namely, the detection of sensors failure, isolation of the faulty sensors, and reconfiguration of the control system by proper currents estimation. A new adaptation of the Luenberger observer is proposed and used to perform the task of stator currents estimation. Furthermore, a developed logic circuit is used to detect the faulty current sensors and isolate them with simultaneous generation of logic impulses allowing switching to a proper estimation. The proposed fault-tolerant control strategy is firstly tested in MATLAB/Simulink environment in order to illustrate its high-performance. Then, several experimental tests are carried out on a 1.1 kW three-phase induction motor to validate the theoretical results and to confirm the effectiveness of the proposed algorithm.

Model Predictive Control for Virtual Synchronous Generator with Improved Vector Selection and Reconstructed Current

Due to the large-scale renewable energy connected to the power grid by power electronic converters, the inertia and stability of the power grid is declining. In order to improve the inertia and support the grid recovery, the three-phase converter works as a virtual synchronous generator (VSG) to respond to the frequency and voltage changes of the power grid. This paper proposes a model predictive control for the virtual synchronous generator (MPC-VSG) strategy, which can automatically control the converter output power with the grid frequency and voltage changes. Further consideration of fault-tolerant ability and reliability, the method based on improved voltage vector selection, and reconstructed current is used for MPC-VSG to ensure continuous operation for three-phase converters that have current-sensor faults, and improve the reconstruction precision. The proposed method can respond to the frequency and voltage changes of the power grid and has fault-tolerant ability, which is easy to realize without pulse width modulation (PWM) and a proportional-integral (PI) controller. The effectiveness of the proposed control strategy is verified by experiment.

Real‐time open‐switch fault diagnosis in automotive permanent magnet synchronous motor drives based on Kalman filter

This study proposes an effective diagnosis method for single and multiple open-switch faults (OSFs) in three-phase permanent magnet synchronous motor (PMSM) drives. The proposed method is based on the real-time estimation of the three-phase motor currents using three Kalman filters (KFs). Three residual signals are defined as the differences between the three-phase measured and estimated stator currents. The averaged normalised residual signals are used as diagnostic criteria for the detection of OSFs. The proposed method accurately detects the OSFs, localises the faulty switches and effectively discriminates between the OSFs and current sensor faults. The main superiorities of the proposed KF-based method are its fast detection time and high robustness to measurement noises/errors and load variations. Moreover, the proposed method is useful for both closed-loop and open-loop PMSM drives. The proposed method can be embedded as a subroutine in the drive control unit without any hardware extension. The effectiveness of the proposed method is confirmed through extensive simulations and several hardware-in-the-loop experiments on a testbed with a 1.5 kW PMSM and dSPACE1104 control board. In addition, the real-time feasibility of the proposed method using low-cost microprocessor technology is guaranteed by testing it on TMS320F28335 from Texas Instruments © .

Fault-tolerant control of steer-by-wire systems under voltage and current sensors faults

Steer-by-wire (SBW) systems benefit from several advantages including lower weight, volume, and cost compared to counterpart electric power steering systems. However, system reliability is impacted since SBW performance is highly dependent on correct operation of several voltage, current, speed, yaw rate, and position sensors. This paper presents a new method in SBW system reliability improvement by introducing a novel fault detection, isolation, and reconstruction (FDIR) control technique. The proposed FDIR method detects if any fault is observed on voltage or current sensors and identifies the faulty sensor location. Additionally the identified faulty sensor’s output is replaced with an estimated value to allow system continuous fault-ride through operation. The SBW system equipped with proposed FDIR technique provides fault-tolerance property against up to 3 faulty voltage or current sensors. Therefore, enhanced overall reliability is obtained at no further hardware costs associated with additional sensors redundancy solutions. The proposed technique is studied using system modelling and hardware prototyping, and its effectiveness is demonstrated using simulation and experimental results.

Rotor-current-based fault detection for doubly-fed induction generator using new sliding mode observer

To detect the fault of the doubly-fed induction generator (DFIG), in this paper, a fault detection method of novel sliding mode observer is proposed, without a velocity sensor. In addition to better elimination of chattering for the new sliding mode observer, at the same time, it has better stability and faster convergence speed than the traditional sliding mode observer. Firstly, the sliding mode observer is built according to the mathematical model of the DFIG. Then, the rotor current and the rotational speed are estimated. After comparing the actual rotor current value with the observed value, the self-detection of the fault for the DFIG is realized. Secondly, three faults of grid voltage sags failure, DFIG inter-turn stator fault and rotor current sensor fault are given respectively. After that the Simulink simulation model is built under different fault conditions. It is proved by simulation that this sliding mode observer can well detect faults occurring at different positions. Additionally, it can also be proved that the sliding mode observer has the characteristics of fast response and good stability.

A Fault Diagnosis Method for Current Sensors of Primary Permanent-Magnet Linear Motor Drives

In this article, a fault diagnosis method is proposed to detect current sensor faults for the studied primary permanent-magnet linear motor (PPMLM) traction system, in which only two current sensors are required, and the gain fault and zero-offset fault can be distinguished. In this proposed fault diagnosis method, synchronous currents are estimated by the PPMLM model. By comparing the estimated and measured synchronous currents, estimation errors are calculated, and ac components can be extracted by corresponding filters. In the synchronous frame, the zero-offset fault and the gain fault can be detected by the single-frequency and double-frequency components, respectively. Furthermore, the fault phase also can be located. Compared with conventional fault diagnosis methods, the proposed one can distinguish gain fault and zero-offset fault but only two current sensors are required. Simulation and experimental results verify the effectiveness of the proposed fault diagnosis method.

Robust Current Sensorless Control of VSC-Based MTDC Transmissions for Integrating Wind Farms

This article presents an observer-based robust current sensorless control (RCSC) scheme for voltage-source-converter (VSC)-based multiterminal direct-current (MTDC) transmission system integrated with wind farms. Perturbation observer-based point of common coupling (PCC) voltage controller and dc-link voltage controller are designed for wind farm station (WFS) and grid-side station (GSS) of MTDC, respectively, for grid integration of multiple wind farms. Perturbation states are defined to describe the interactions of voltage control loops of nonlinear VSC model, and the feedback linearization control is realized based on the state estimations provided by perturbation observers to achieve the decoupled voltage control of MTDC. Neither current sensors nor parameters of MTDC are required in the RCSC scheme, thus achieving the robust sensor fault-tolerant operation of the MTDC system. Simulation and experimental studies are undertaken on a three-terminal MTDC transmission system integrated with two wind farms to verify the control performance of the RCSC scheme under the conditions of wind speed variations, sudden load changes, parameter variations, and current sensor faults.

An Online Data-Driven Method for Simultaneous Diagnosis of IGBT and Current Sensor Fault of Three-Phase PWM Inverter in Induction Motor Drives

This article presents an online data-driven diagnosis method for multiple insulated gate bipolar transistors (IGBTs) open-circuit faults and current sensor faults in the three-phase pulsewidth modulation inverter. The fast Fourier transform (FFT) algorithm is used to extract the fault frequency spectrum features of the three-phase currents. Then, a feature selection method named ReliefF is introduced to select the most critical features by removing redundant and irrelevant features. In addition, as novel fast learning technology, a random vector functional link network is applied to learn the faulty knowledge from the historical dataset. Based on the well-learned model, the fault type and location of the converter can be accurately identified as long as the three-phase current signals are measured. Offline test results verify that the proposed method can identify the IGBT and sensor faults with an accuracy of 98.83% and outperforms the state-of-the-art learning algorithms. Moreover, the real-time hardware-in-the-loop test results show that the proposed method can successfully identify the IGBT faults and current sensor faults within 22 ms. It is robust to the dc-link voltage fluctuations, model parameters, and speed or load variations. The extensibility of the proposed method is also validated based on the test results in terms of other fault modes and drive systems.

Current and Position Sensor Fault Diagnosis Algorithm for PMSM Drives Based on Robust State Observer

This study proposes an advanced current and position sensor fault diagnosis mechanism for permanent magnet synchronous motor (PMSM) applications. Machine nonlinear dynamics as well as parameter and load uncertainties are addressed. The features of the results of this study are summarized as follows: 1) a proportional-type full-state observer is combined with a disturbance observer to deal with the model uncertainties, 2) a partial optimal process is introduced for determining the observer gain, 3) the concept of normalized residuals is introduced for fault diagnosis criteria, and 4) a closed-loop analysis of the convergence, performance recovery, and offset-free guarantee is provided. The performance recovery property makes the proposed algorithm robust to parameter uncertainties and load variations, and sensitive only to sensor faults. In addition, the location and type of sensor faults can be identified by the fault diagnosis criteria using the normalized residuals. The performance of the sensor fault diagnosis algorithm was experimentally verified under several credible scenarios using a 7.5-kW PMSM.

Model predictive power control for a fault‐tolerant grid‐connected converter using reconstructed currents

The reliability and stability of a grid-connected converter is vital to the power conversion system. The faults of switching device and current sensor lead to operation failure for a grid-connected converter. An improved model predictive power control (MPPC) based on reconstructed currents is proposed for fault-tolerant operation of a grid-connected converter. Firstly, the three-phase currents are reconstructed using the sampled dc current and normal sensor information according to the relationship between the voltage vector and output currents. Secondly, the predictive power model is built based on fault-tolerant three-phase four-switch topology. Then the reconstructed current is used for the MPPC method. To keep the balance of dc capacitor voltages, the cost function is optimised and the switching vector, which minimises the cost function, is applied to the fault-tolerant converter. Finally, the experiment platform and simulation models are built to verify the proposed method. The results show that the proposed MPPC using reconstructed currents can keep the fault-tolerant operation of the grid-connected converter with sinusoidal currents and stable output power. The proposed method achieves the fault-tolerant operation under switching device and ac current sensor fault, which improve the reliability of the system.

Sensor-Fault-Estimation-Based Tolerant Control for Single-Phase Two-Level PWM Rectifier in Electric Traction System

This article presents a fault-estimation-based tolerant control strategy for single-phase two-level pulsewidth modulation rectifier subjected to catenary current sensor fault and dc-link voltage sensor fault. First, an augmented descriptor system is developed for the rectifier, whose augmented state vector consists of the state vector of original system as well as the sensor fault together with the measurement disturbance. Then, a linear reduced-order observer is designed for the descriptor plant. Accurate asymptotic estimation of the original state vector and the disturbed sensor fault are thus achieved simultaneously. Finally, the fault tolerant design method is addressed through sensor fault compensation, which allows the pre-design controller to continue to function normally even when both catenary current sensor and dc-link voltage sensor are faulty. Simulation and hardware-in-the-loop test results confirm the effectiveness of the proposed method.

Simple and Robust Current Sensor Fault Detection and Compensation Method for 3-Phase Inverters

The present paper proposes a genuine, simple to implement, robust and reliable method for current sensors fault detection and compensation used for 3-phase inverters. Its functionality is based on an algorithm programed into a Field Programmable Gate Array (FPGA) as general controller. Usually, 3-phase inverters are controlled using field oriented control (FOC) which is generally triggered to sample the measured currents on the established switching frequency. As the latter is much smaller than the base clock of the FPGA, this allows hundreds of free time samples to perform other calculations in-between two FOC samplings. In this paper, a method that uses these free and unused time samples is presented. This method performs calculations for fault detection and compensation ensuring that at each new FOC sampling, this will receive the correct current data to reach continuous operation despite faults. The interleaving principle of the FOC with the fault detection method, as it will be proven in the paper, ensures high reliability of the complete controller diminishing the possibility of undesired or faulted readings to disturb the FOC’s calculations. The fault detection philosophy is based on continuous comparison of the instantaneous measured currents (sensor’s response) against reference values. The experimental results presented in the paper prove reliable operational performances of the method in both steady state and transient conditions. The added value of the paper consists in its genuine approach to handle the fault detection and compensation in-between two PWM ticks, ensuring that no faulted measurements can reach the control unit. This added value is based on functionality divided on several functions triggered by an internal generated clock synchronizing and handshaking their operations towards one goal: fault detection and compensation.

Robust Reconstruction of Current Sensor Faults for PMSM Drives in the Presence of Disturbances

The reliability and availability of a permanent magnet synchronous motor (PMSM) drive system are of increasing importance in industrial applications. Occurrence of current sensor faults in the system can lead to system degradation. Therefore, early detection of the faults has become an important problem. However, various exogenous disturbances seriously affect the accuracy of the faults detection. This paper presents a method of reconstructing current sensor faults for a PMSM drive containing unknown disturbances. An equivalent-input-disturbance approach is devised to reject the effects of unknown disturbances on system performance and reconstruction of faults And an integral observer is designed to approximately separate faults from the measured output to eliminate the interference to disturbance rejection. Then, a sliding-mode observer is designed for the disturbance-rejected system with current sensor faults. And the faults are reconstructed based on sliding-mode equivalent control methodology. The presented scheme has good performance in terms of faults reconstruction and is robust to time-varying unknown disturbances. Simulations and experiments validate the effectiveness of the method.

Virtual Current Sensor in the Fault-Tolerant Field-Oriented Control Structure of an Induction Motor Drive.

Designing electrical drives resistant to the failures of chosen sensors has recently become increasingly popular due to the possibility of their use in fault-tolerant control (FTC) systems including drives for electric vehicles. In this article, a virtual current sensor (VCS) based on an algorithmic method for the reconstruction of the induction motor (IM) phase currents after current sensor faults was proposed. This stator current estimator is based only on the measurements of the DC-bus voltage in the intermediate circuit of the voltage-source inverter (VSI) and a rotor speed. This proposal is dedicated to fault-tolerant vector controlled IM drives, where it is necessary to switch to scalar control as a result of damage to the current sensors. The proposed VCS allows further uninterrupted operation of the direct rotor-field oriented control (DRFOC) of the induction motor drive. The stator current estimator has been presented in the form of equations, enabling its practical implementation in a microprocessor system. Simulation studies of the proposed algorithm in an open and closed-loop DRFOC structure are presented under different operation conditions of the drive system. The experimental verification of the proposed method is also presented and the accuracy of the stator current estimation algorithm is analyzed under various operating conditions of the drive system.

Enhanced Control Algorithm in PMSMs with Machine Current Sensor FDI and Current Management for Hardware Protection

This paper proposes an enhanced control algorithm in permanent magnet synchronous machines (PMSMs) with machine current sensor fault detection and isolation (FDI) and current management for hardware protection. Different from existing work on machine current sensor FDI, the proposed method addresses the sensor FDI problem under co-existence of PMSM current sensor and non-sensor imbalance faults, and thereby help prevent the controller performance degradation caused by a faulty machine current sensor signal. Meanwhile, hardware protection is achieved through the proposed algorithm which has a unique feature of providing online overcurrent regulation and source power management at the same time to enhance protection of power inverter and power source. Benchmark comparison of the proposed sensor FDI method to state-of-the-art techniques is carried out to validate the good performance of the proposed FDI method in terms of fault detection time, false detection rate and missed detection rate. Sensitivity analysis of the proposed current management algorithm with overcurrent regulation and source power management is performed under changing rotor flux linkage and machine stator d-axis self-inductance, as an example to demonstrate the robustness of the proposed algorithm for hardware protection against system parameter variations. The effectiveness of the proposed algorithm is confirmed by simulation results in MATLAB for a PMSM.