Abstract
This paper proposes a current sensor fault detection method based on a sliding mode observer for the torque closed-loop control system of interior permanent magnet synchronous motors. First, a sliding mode observer based on the extended flux linkage is built to simplify the motor model, which effectively eliminates the phenomenon of salient poles and the dependence on the direct axis inductance parameter, and can also be used for real-time calculation of feedback torque. Then a sliding mode current observer is constructed in αβ coordinates to generate the fault residuals of the phase current sensors. The method can accurately identify abrupt gain faults and slow-variation offset faults in real time in faulty sensors, and the generated residuals of the designed fault detection system are not affected by the unknown input, the structure of the observer, and the theoretical derivation and the stability proof process are concise and simple. The RT-LAB real-time simulation is used to build a simulation model of the hardware in the loop. The simulation and experimental results demonstrate the feasibility and effectiveness of the proposed method.
Highlights
Permanent magnet synchronous motors (PMSMs) can efficiently satisfy the requirements of railway vehicles, including power quality, energy consumption and control characteristics thanks to their high efficiency, high ratio of torque to weight, high power density and faster response [1,2,3]
First a sliding mode observer based on the extended flux linkage is designed to simplify the motor model, which effectively eliminates the phenomenon of salient poles and the dependence of the direct axis inductance parameter, and can be used for online calculation of feedback torque
The torque calculation value which is obtained by the extend flux linkage is shown in in order to illustrate the function of sliding mode observer, we introduce signal v at t = 0.1 s
Summary
Permanent magnet synchronous motors (PMSMs) can efficiently satisfy the requirements of railway vehicles, including power quality, energy consumption and control characteristics thanks to their high efficiency, high ratio of torque to weight, high power density and faster response [1,2,3]. A fault diagnosis structure of position and phase current sensors faults of a PMSM driven system is studied in [18]; the method is based on two interconnected observers: an Extended Kalman Filter and a Model Reference Adaptive System observer. An adaptive observer method for detection and isolation of abrupt gain faults and offset faults for phase current sensors is studied in [19,20], but they did not consider the slow-variation faults which are difficult to observe, and only give the fault residuals of αβ axis virtual current sensors, detect the phase sensor faults through logical judgments, but this causes misjudgments because the threshold is set larger, and the motor model adopted by the tmethod has serious salient features which are inconvenient for the observation of PMSM status. The simulation and experimental results demonstrate the feasibility and effectiveness of this method
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