The paper presents a feasibility study for full-electric aircraft in terms of a conversion design. The advancement of energy storage technologies has given the potential to fully electrify future transport systems. The means of electrifying aircraft are to reduce carbon emission and increase efficiency in air transport. This paper studies the feasibility of developing an all-electric short to midrange aircraft. The study investigates the possibility of replacing the aircraft’s conventional system with an all-electric drive train. Using the current conventional aircraft model, different types of electrical systems are compared to examine their advantages and limitations. The parameters of De Havilland Canada Dash 8 (DH8D) and the average flight are used to analyze the feasibility of completing a desired range. The results show that the electrification of aircraft with the studied propulsion system is not feasible for the conventional range, but producing an all-electric aircraft is possible when the technology allows for it. Additionally, a reliability analysis is conducted for both the conventional and the electrified version of aircraft, including different electric topologies, whereas a multiple electric motor topology is nearly as available as the conventional one.

This paper deals with the reliability of today's induction machines. The fault tree analysis is presented including the most important parts of the machine, whereas the bearings are emphasized within this paper. The general focus is set on data acquisition, their analysis, and the resulting statistics which finally allow to derive tendencies and perspectives regarding the reliability of induction machines. Hence, it gets obvious that despite the significant advances in the field of new materials and technologies, the average failure probability of induction machines approximately remained at the level of the 1970s.

Electric vehicles (EVs) are playing a pivotal role in transportation systems to conform to the rising exigencies for enhanced performance with safety and hindered environmental impact. Thus, to improve the efficiency and downsize the maintenance cost of EVs, an early fault diagnosis (FD) framework is crucial. Bearing and stator winding faults, which account for approximately 78% of induction machine (IM) incipient faults in EVs, remain rather elusive for conventional sensors to accurately classify them and their incipient values. To this end, this paper presents a novel Attention-enhanced Autoencoder-Gated Recurrent Unit (AAGRU) model that improves the accuracy and efficiency of fault analysis in IMs. Moreover, since bearing faults are usually captured through vibration sensors, which are expensive and require direct coupling with the IM, a hybrid signal re-constructor is devised based on merely stator current signals. The proposed model leverages Empirical Mode Decomposition (EMD), Fast Fourier Transform (FFT), and Discrete Wavelet Decomposition (DWT) to process the electric current data, which are then used by the AAGRU model to identify, detect, and classify the fault patterns. Experimental results demonstrate that the proposed model offers a 1%–6% improvement in fault detection and an 8%–28% improvement in inter-turn short-circuit fault severity classification relative to different shallow and deep-based benchmark models. The proposed model was also tested on different load conditions to ensure its applicability in practice.

This article presents a performance evaluation of a flexible manufacturing system (FMS), in which the system and its components can have different performance levels ranging from perfect functioning to total failure. An original multistate transition process for the FMS’s main component, Computerized Numerical Control (CNC) machine tools, proposed in the current article and treated as an aging process because of its increasing failure rate is investigated. The Markov reward approach is utilized to analyze the availability of CNC machine tools and sensitivity analysis of each non-operational state to the machine’s downtime. To overcome the “state explosion problem” in the subsequent FMS performance evaluation process, an application of the Lz-transform method is proposed to determine the performance evaluation and availability of such aging multistate FMS. An illustrated case is presented to demonstrate the performance evaluation process. The results show that the suggested methods can be implemented in engineering decision making and construction of various aging multistate FMS related to demands, availability, and output performance.

This paper describes a methodology of quantitative assessment of the fault tolerance of the multi-state safety-critical systems with functional redundancy. Such systems are the traction drives of electrical vehicles, consisting of the multiphase traction electric motor and multilevel electric inverter. It is suggested to consider such traction drive as a system with several degraded states. As a comprehensive parameter for the quantitative evaluating the fault tolerance, it is proposed to use the criterion of degree of the fault tolerance. For the approbation of proposed methodology, based on the multi-state system reliability Markov Model, the fault tolerance assessment of the traction train of an electrical helicopter has been carried out.