Fast transistor open-circuit faults diagnosis in grid-tied three-phase VSIs based on average bridge arm pole-to-pole voltages and error-adaptive thresholds
This paper presents a model-based method to diagnose single-and multiple-transistor open-
circuit (OC) faults in grid-tied three-phase voltage-source inverters (VSIs). The method is
based on calculated average bridge arm pole-to-pole (PTP) voltages and error-adaptive
thresholds. Only existing signals for closed-loop control are needed; thus, this method can
be easily embedded in the system without extra sampling and circuits. Average PTP voltage
deviations are chosen as diagnosis variables, which show considerable distinction quickly …
circuit (OC) faults in grid-tied three-phase voltage-source inverters (VSIs). The method is
based on calculated average bridge arm pole-to-pole (PTP) voltages and error-adaptive
thresholds. Only existing signals for closed-loop control are needed; thus, this method can
be easily embedded in the system without extra sampling and circuits. Average PTP voltage
deviations are chosen as diagnosis variables, which show considerable distinction quickly …
This paper presents a model-based method to diagnose single- and multiple-transistor open-circuit (OC) faults in grid-tied three-phase voltage-source inverters (VSIs). The method is based on calculated average bridge arm pole-to-pole (PTP) voltages and error-adaptive thresholds. Only existing signals for closed-loop control are needed; thus, this method can be easily embedded in the system without extra sampling and circuits. Average PTP voltage deviations are chosen as diagnosis variables, which show considerable distinction quickly after fault. Consequently, fast fault diagnosis speed can be achieved. The fault diagnosis time for single fault can be as short as two switching periods. Besides, diagnosis variables show the same faulty characteristics in inverter mode and rectifier mode; thus, this method is effective in both modes. Moreover, for the first time, the variation of inductance caused by conducted current is considered to obtain a more accurate variable-inductance model, and the thresholds are updated according to mathematically estimated diagnosis variable calculation errors from sampling error, inductance error, dead time, and delay time, which maintains high robustness as well as fast speed. Finally, the effectiveness of the proposed method is validated with experiments.
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