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BLDC motors are widely employed in various applications because of their high efficiency, reliability, and long operational life. For BLDC motors, any electric malfunctions in the commutation signal creation with or without Hall sensors can lead to unexpected vibrations, crashes, and accidents according to application areas. Therefore, fast detection and diagnosis of these faults are crucial for the reliable operation of BLDC motor drive systems. In this paper, a unique approach has been explored for developing fault signatures to detect commutation signal faults accurately and rapidly in the BLDC motor drive system under highly dynamic loads. After the fault detection, a commutation signal is indirectly reconstructed based on healthy commutation signals to continuously drive the motor drive system to avoid serious electrical and mechanical issues due to the faults. The proposed approach and feasibility of the method have been verified both by simulation and experimental studies. The results of the proposed method will significantly improve the accuracy of the commutation signal fault detection and eventually enhance the reliability of the BLDC motor drive. 

Unmanned aerial vehicles (UAVs) are widely used for various applications, such as military surveillance and reconnaissance; delivery of packages; monitoring of plants and buildings; and search and rescue. Besides basic battery-electric propulsion, in order to improve range and endurance, hybrid electric propulsion systems based on combinations of batteries, fuel cells, solar cells, and ultracapacitors are increasingly being applied to these UAVs. For small- and medium-scale UAVs, the solar and fuel cell converters have non-isolated DC-DC converters that include a high-frequency switching device. In this paper, a novel switch fault detection technique based on virtual admittance is proposed for DC-DC converters. A fault index function is formulated based on the virtual admittance to minimize potential influence by highly dynamic load change while reducing computation complexity to implement the technique in cost-effective UAVs. The proposed technique has been verified by simulations and experiments to validate the feasibility of the approach.