The bio-inspired algorithms are novel, modern, and efficient tools for the design of electrical machines. However, from the mathematical point of view, these problems belong to the most general branch of non-linear optimization problems, where these tools cannot guarantee that a global minimum is found. The numerical cost and the accuracy of these algorithms depend on the initialization of their internal parameters, which may themselves be the subject of parameter tuning according to the application. In practice, these optimization problems are even more challenging, because engineers are looking for robust designs, which are not sensitive to the tolerances and the manufacturing uncertainties. These criteria further increase these computationally expensive problems due to the additional evaluations of the goal function. The goal of this paper is to give an overview of the widely used optimization techniques in electrical machinery and to summarize the challenges and open problems in the applications of the robust design optimization and the prospects in the case of the newly emerging technologies.

Since electrical machines are the largest consumer of electricity worldwide, their fault diagnostic at the incipient stage and condition monitoring is essential for better reliability, economy, and safety of operation. Out of several condition monitoring techniques, motor current signature analysis is gaining heightened popularity because of its non-invasive nature, the least number of sensors required and versatility of compatible algorithms. In this study, the best characteristics of infinite impulse response (IIR) filter are exploited to observe the broken rotor bar (BRB) frequencies with good legibility in current and voltage spectrum of the grid and inverter-fed motor, respectively. The causes of various harmonics in the stator current spectrum are first investigated for better understanding. The results are taken based on simulation and measurements taken from the laboratory setup. It is observed that a better tuning of IIR filters can make diagnostic algorithms capable of detecting the frequencies of interest by effectively attenuating the fundamental component and reducing its spectral leakage. Moreover, in case of direct torque control-based industrial inverter-fed motors, the current cannot be a good candidate for fault diagnostics rather the phase voltage can be effectively used for the detection of BRBs.

This study presents the modelling and simulation of a squirrel cage induction motor using a modified winding function‐based method. The aim of the model is to compute the motor's performance parameters, which are similar to the results obtained using the finite element method (FEM) with a considerably reduced simulation time. This fact can make this model good for iterations based optimisation and fault diagnostic algorithms. For this purpose, the actual stator and rotor winding functions and the air gap, with the inclusion of rotor and stator slots, are defined as conditional expressions. The resistances and various inductances are calculated with stepping rotor, saved in lookup tables and are used to calculate speed, torque, and currents of the motor. For the validation of the model, the frequency spectrum of stator current is compared with the one calculated using FEM and measurements taken in the laboratory setup under healthy and broken rotor bar conditions.

Recent studies show that synchronous reluctance motors (SynRMs) present promising technologies. As a result, research on trending SynRMs drive systems has expanded. This work disseminates the recent developments of design, modeling, and more specifically, control of these motors. Firstly, a brief study of the dominant motor technologies compared to SynRMs is carried out. Secondly, the most prominent motor control methods are studied and classified, which can come in handy for researchers and industries to opt for a proper control method for motor drive systems. Finally, the control strategies for different speed regions of SynRM are studied and the transitions between trajectories are analyzed.