Abstract
Due to the importance of the drive system reliability, several diagnostic methods have been investigated for the SSTPI-IM association in the literature. Based on the normalized currents and the current vector slope, this paper investigates a fuzzy diagnostic method for this association. The fuzzy logic technique is appealed in order to process the diagnosis variable symptoms and the faulty IGBT information. Indeed, the design, inputs, and rules of the fuzzy logic are distinct compared with the other existing diagnostic methods. The proposed fuzzy diagnostic method allows the best efficient detection and identification of the single and phase OCF of the SSTPI-IM association. Accordingly, after the fault detection and identification using this proposed FLC diagnostic method, a reconfiguration step of IGBT OCFs must be applied in order to compensate for these faults and ensure the drive system continuity. This reconfiguration is based on the change of the SSTPI-IM topology to the FSTPI-IM topology by activating or deactivating the used relays. Several simulation results utilizing a direct RFOC controlled SSTPI-IM drive system are investigated, showing the fuzzy diagnostic and reconfiguration methods’ performances, their robustness, and their fast fault detection during distinct operating conditions.
Highlights
Given the reliability and efficiency, the Six-switch three-phase inverter FSTPI (SSTPI)-IM association has been used in several industrial applications such as medical and military applications, renewable energy sources, robotics, and electric vehicles [1,2,3]
A novel FLC diagnostic method for the SSTPI-IM drive system has been proposed. is proposed method is based on the measured currents, which avoids the utilization of extra hardware or sensors
We focus only on the single Open circuit faults IGBTs (OCFs) and phase OCF appearing in the SSTPI-IM association controlled by the direct Rotor flux oriented control IM (RFOC) strategy. ese faults are detected and identified by using a fuzzy variable, which proves the ability to precisely avoid false alarms during speed and load variations
Summary
Given the reliability and efficiency, the SSTPI-IM association has been used in several industrial applications such as medical and military applications, renewable energy sources, robotics, and electric vehicles [1,2,3]. In order to ameliorate the robustness and to precisely detect and identify these faults without false alarms during speed and load variations, the used diagnosis variables must be processed based on the FLC theory. The value 0 indicates the healthy case; the values between 0 and 1 indicate the faulty case This proposed fuzzy method can detect and locate the IGBT OCFs without false alarms during speed and load variations which prove their high performance and robustness. Rated power (kW) Rated line voltage (volt) Supply frequency (Hz) Rated speed (rpm) Rated load torque (N.m) Number of pole pairs Stator resistance (Ω) Rotor resistance (Ω) Stator inductance (H) Rotor inductance (H) Mutual inductance (H) Moment of inertia (kg.m2) Friction factor (N.m.s/rad) Based on these fuzzy rules, the switch faults can be precisely located and detected without false alarms. It is to be underlined that the proposed fuzzy diagnostic method is effective in the reconfiguration step in order to compensate for the fault
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