https://eecs.nri.ac.ir/ Electromechanical Energy Conversion Systems en daily 1 Mon, 01 Sep 2025 00:00:00 +0330 Mon, 01 Sep 2025 00:00:00 +0330 https://eecs.nri.ac.ir/article_226963.html Ball-bearings are one of the most important components in rotating machinery. Due to practical importance of rotating machineries in industry, fault detection has become inevitable. Various techniques have been implemented for ball-bearing fault detection using vibration signals. In this research, vibration signal analysis methods are presented to extract suitable features for training some of the machine learning techniques in order to diagnose ball-bearing defects in different speeds. The purpose of this study is to obtain a highly accurate algorithm and compare its performance with that of other machine learning algorithms. To achieve this goal, Hilbert transform has been applied for envelope analysis to attenuate the frequencies that are not related to ball-bearing fault and perform power spectral density and descriptive statistics to extract features. Also comparison and evaluation of random forest, support vector machine, artificial neural network and k-nearest neighbour have been carried out for this study. For dataset with 1465 samples in various speed, random forest has achieved the accuracy above %97. https://eecs.nri.ac.ir/article_241157.html This paper presents the design and analysis of an axial flux switched reluctance motor (AFSRM) developed as a propulsion system for electric vehicle applications. The proposed motor leverages an axial flux topology to achieve high torque density and compact construction. Detailed electromagnetic modeling through finite element method (FEM) were conducted to evaluate its performance, including flux density, phase current, induced voltage, flux linkage, electromagnetic torque, and torque ripple characteristics. Results indicate that the AFSRM delivers superior performance in terms of operational reliability, making it an attractive solution for modern and light electric drive systems with low speed and high torque density. This paper also discusses the motor’s suitability for lightweight and high-efficiency applications, highlighting its potential for future advancements in sustainable transportation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . https://eecs.nri.ac.ir/article_229497.html In many engineering textbooks, very simple algebraic relations are used for magnetic forces. The simplicity of the relations lies in the well-known magnetic circuit model from which they have been derived. However, some applications require more accuracy. One niche application is the calculation of magnetic forces in electrical machines due to slotting effect. The application is twofold: 1) vibration analysis which requires calculation of the net torque ripple (leading to cogging torque) and the oscillation of resultant normal force (attractions/repulsions). 2) deformation analysis which requires calculating the surface and volume force density distribution. Given the magnetic field distribution, the analyses can be furnished by leveraging advanced formulae of magnetic force. Thus in order to increase the accuracy, engineers would have to resort to 1) more advanced magnetic models that yield a precise two-dimensional magnetic field distribution and 2) a reliable method of magnetic force calculation. The latter is the subject of this paper. To be a reference for engineering community, this paper follows these objectives: 1) since not all engineers are accustomed with advanced physics topics; this paper aims to bring a handful of formulae from the outset. Additionally, two novel formulae are derived: surface force density and Maxwell couple stress tensor. 2) Revisiting the underlying theory and derivation of the related formulae for three purposes: 2-1) providing subjective foresight, 2-2) elucidating the limitation of the usage of the formulae and 2-3) to point out common mistaken interpretations. Two case-studies are investigated to verify the identity of all formulae. https://eecs.nri.ac.ir/article_241160.html Electric drive trains have become the backbone of modern rail transportation, offering significant improvements in energy efficiency, environmental sustainability, and operational performance compared to traditional diesel-powered systems. Electric propulsion enables faster acceleration, higher speeds, and smoother operation due to precise motor control. Electric trains operate more quietly than diesel locomotives, improving urban livability near rail corridors. Compatibility with renewables, hydrogen hybrids, and automation ensures adaptability to evolving green energy landscapes. Regenerative braking recovers up to 30% of braking energy, feeding it back to grid or onboard storage for reuse. Electric trains convert over 90% of grid power into motion, far surpassing diesel engines (30-35% efficiency), reducing overall energy consumption. This paper provides an in-depth analysis of electric drive trains, covering their historical evolution, key technological components, advantages, applications, challenges, and future trends. The study highlights the role of advanced traction motors, power electronics, and energy storage systems in enhancing rail efficiency. Case studies from high-speed rail networks, urban transit systems, and freight operations illustrate the real-world impact of electrification. Additionally, the paper addresses critical challenges such as infrastructure costs and energy sourcing while exploring emerging innovations like hydrogen fuel cells, AI-driven optimization, and renewable energy integration. The findings underscore the importance of continued investment in electric rail technologies to achieve global sustainability goals in transportation. https://eecs.nri.ac.ir/article_241173.html Electric rail systems are vital for sustainable urban transport but generate noise that impacts communities and passengers. Noise detection and mitigation in electric rail systems provides several key benefits, including improved quality of life for nearby residents by reducing disruptive noise pollution. It enhances passenger comfort through quieter cabins and smoother rides, leading to better travel experiences. For operators, mitigation measures like optimized wheel designs and track maintenance lower long-term maintenance costs by minimizing wear and tear from vibrations. Additionally, compliance with environmental regulations is achieved, avoiding legal penalties and fostering positive community relations. This paper examines key noise sources in electric rail operations, including wheel-rail interaction, aerodynamic effects, traction systems, and electromagnetic fields. Acoustic measurement techniques such as beamforming, near-field acoustic holography, and pass-by testing are evaluated for their effectiveness in identifying and quantifying noise emissions. Computational models, including finite element and statistical energy analysis, are explored for predicting noise propagation. Mitigation strategies focus on optimized wheel and rail design, active noise control, and passive damping materials. Emerging technologies like machine learning for noise prediction and metamaterials for sound absorption show promise for future applications. This study provides a comprehensive framework for addressing noise challenges in electric rail systems, contributing to quieter and more sustainable urban mobility. https://eecs.nri.ac.ir/article_245418.html In D-STATCOM (Distribution Static Synchronous Compensator) systems, the harmonic quality of the injected current is strongly affected by several operational and structural parameters, such as the achievable compensation level, modulation strategy, DC-link energy storage, and the characteristics of the AC-side filters. Among these elements, DC-link capacitors represent one of the most failure-prone components in power electronic converters due to aging effects, partial cell degradation, and protection-device malfunctions within capacitor banks. Such degradations modify the effective DC-link capacitance, leading to increased voltage ripple, constrained modulation capability, and a subsequent rise in current harmonic distortion at the point of common coupling (PCC), ultimately deteriorating grid power quality.To mitigate this issue, this paper introduces a supplementary adaptation scheme integrated as a secondary control layer into the conventional multi-loop control architecture. Instead of modifying the primary current and voltage controllers, the proposed approach dynamically adjusts the reactive power reference, thereby indirectly constraining the current THD within permissible limits. The method operates in steady-state conditions and remains compatible with existing control frameworks. Both simulation results and hardware-in-the-loop validations confirm that the proposed adaptation strategy effectively suppresses harmonic distortion and improves grid power quality, even under significant DC-link capacitance reduction. https://eecs.nri.ac.ir/article_227606.html As the demand for Two-Degree of Freedom (2-DoF) electrical machines continues to grow, the need for advanced sensors capable of detecting positions in multiple directions becomes increasingly critical. Compared to employing two separate sensors, using a single 2-DoF sensor offers significant advantages by reducing weight, volume, and complexity in control systems. This paper investigates a 2-DoF position sensor designed for helical motion detection. Given the significant impact of winding arrangements on resolver performance, determining the optimal winding configuration for helical motion is essential. To address the computational challenges associated with 3D Finite Element Analysis (3D-FEA), a numerical model based on the Winding Function (WF) method is developed to facilitate the optimization process. Subsequently, the Particle Swarm Optimization (PSO) algorithm is applied to refine the winding arrangement further and achieve greater accuracy. The results demonstrate that the resolver equipped with the optimized winding configuration significantly outperforms the one with the initial winding arrangement in terms of accuracy. https://eecs.nri.ac.ir/article_227707.html Geomagnetically induced current (GIC) is a geomagnetic phenomenon. Inducing this current in power grid can cause damage the transformers by creating hot spots, increases the losses of power system and causes some problems in the electrical energy transmission process to the consumers. GIC can make the transformer to operate in its magnetic saturation region and therefore to increase the reactive power and harmonics by the transformer. This paper introduces the GIC and its impacts on the power systems and power transformers. Moreover, several methods to confront this destructive phenomenon are investigated and their merits and drawbacks are proposed using computer simulations of a power system in the presence of GIC. Increasing the sensitivity of the neutral wire leads to faster changes in the power system when a problem occurs in the neutral wire. So, system operation in normal case and in the presence of the GIC must be realized and all these involve a comprehensive control of power system. https://eecs.nri.ac.ir/article_230786.html A transformer is a vital component of the power grid infrastructure as it facilitates efficient transmission, distribution, and utilization of electrical energy, and ensures reliable and uninterrupted power supply to consumers. As the demand for electricity in a power grid increases, additional transformers with higher ratings may be required to handle the increased load. Therefore, the reduction of losses in power transformers is essential for optimizing energy efficiency, reducing costs, and maintaining a reliable power grid. Stray loss which is 20-25% of the total load loss of the transformer, can affect power quality by introducing harmonics into the power grid. Stray losses also increase the temperature, and cooling requirement for the transformer. In addition to the power grid’s cost and performance, the transformer’s lifetime is also important, which ultimately depends on the amount of losses. Therefore, to compromise between the cost and performance and guarantee losses, it should be reduced. In reducing stray losses, shielding is an effective technique that generates opposing fields to the stray flux or establishes a path with lower reluctance. In this study, the three-dimensional finite element method (FEM) is employed to accurately assess the stray losses in the structural components of a 250 MVA power transformer. Various factors, including the choice of materials (ferromagnetic and copper) and the strategic placement of shields, are considered to minimize energy losses and enhance the overall efficiency of the transformer. https://eecs.nri.ac.ir/article_229832.html In the electric drive systems of marine propulsion, particularly in submarines, multiphase permanent magnet synchronous motors (PMSMs) have garnered significant attention due to their enhanced reliability in high-power applications. This paper investigates a twelve-phase non-sinusoidal PMSM with double stator windings, where each stator phase's windings are symmetrically positioned relative to the stator centre. Each winding is powered by a single-phase H-bridge inverter, with both inverters of each phase controlled by a dedicated microcontroller. Given the independent control system for each phase, conventional dq-axis modeling and control methods are not applicable. Instead, the system is modeled in a stationary 12-phase reference frame. Furthermore, due to the non-sinusoidal back-EMF voltage waveforms, harmonic current injection is independently applied to each phase to mitigate torque ripple. For harmonic reference current regulation, a state feedback controller based on an ultra-local model is employed, replacing traditional PI or hysteresis controllers. Additionally, extended state observers (ESOs) are designed to estimate uncertainties and parameter mismatches. Simulation results validate the superiority of the proposed control approach.