Search Results (89)

This paper deals with an analysis of the operation of switched reluctance machines with a non-uniform air gap. The main focus was on the analysis of the performance of machines with a linearly decreasing air gap. Intensive field calculations made it possible to provide their accurate characteristics, which were then used in simulations of various dynamic states. On this basis, the advantages and disadvantages of machines with a non-uniform air gap were finally discussed from the point of view of applications in efficient high-speed drive systems. Full article

Switched Reluctance Machines (SRMs) are gaining increasing traction within the industrial sector, primarily due to their inherently simple and robust structure. Nevertheless, SRMs are characterized by two major drawbacks—high torque ripple and strong radial forces—both of which render them less suitable for applications requiring smooth operation, such as Electric Vehicles (EVs). To address these limitations, researchers and designers focus on optimizing these critical performance metrics during the design phase. In recent years, the concept of System-Level Design Optimization (SLDOM) has been introduced and applied to SRM drive systems, where both the machine and the controller are simultaneously considered within the optimization framework. This integrated approach has shown significant improvements in mitigating the aforementioned issues. This paper aims to review the existing literature concerning the SLDOM applied to SRMs, highlighting the key methodologies and findings from studies conducted in recent years. Despite its promising outcomes, the adoption of SLDOM remains limited due to its high computational cost and complexity. In response to these challenges, the paper discusses complementary techniques used to enhance the optimization process, such as search space and computational time reduction strategies, along with the associated challenges and potential solutions. Finally, two critical directions for future research are identified, which are expected to influence the development of the SLDOM and its application to SRMs in the coming years. Full article

Currently, electric machines predominantly rely on costly rare-earth NdFeB magnets, which pose both economic and environmental challenges due to rising demand. This research explores recent advancements in machine topologies and magnetic materials to identify and assess promising solutions to this issue. The study investigates two alternative machine topologies to the conventional permanent magnet synchronous machine (PMSM): the permanent magnet-assisted synchronous reluctance machine (PMaSynRM), which reduces magnet usage, and the wound-field synchronous machine (WFSM), which eliminates magnets entirely. Additionally, the potential of ferrite and recycled NdFeB magnets as substitutes for primary NdFeB magnets is evaluated. Through detailed simulations, the study compares the performance and cost-effectiveness of these solutions against a reference permanent magnet synchronous machine (PMSM). Given their promising performance characteristics and potential to reduce or eliminate the use of rare-earth materials in next-generation electric machines, it is recommended that future research should focus on novel topologies like hybrid-excitation, axial-flux, and switched reluctance machines with an emphasis on manufacturability and also novel magnetic materials such as FeN and MnBi that are currently seeing synthesis challenges. Full article

In this paper, an improved online torque compensation strategy considering phase torque-generation capability is proposed to enhance the conventional torque-sharing function (TSF), thus reducing torque ripple for switched reluctance machines (SRMs). The improvements are mainly attributed to two aspects: First, the phase turn-on angle and TSF starting angle are separated. Thus, the phase turn-on angle can be advanced independently to enhance the torque-generation capability of the incoming phase. Second, to generate the desired torque with minimum current, the torque per ampere (TPA) characteristic is considered for commutation region separation. This can ensure that in each separated region, the phase with a stronger torque-tracking ability is utilized for torque error compensation. Accordingly, efficiency is not sacrificed. In addition to improving the TSF, a direct instantaneous torque control (DITC) method combined with a PWM regulator is proposed to reduce large torque increments due to the limited control frequency. As a result, the torque ripple can be further suppressed. Finally, an experimental setup is established, and tests are conducted under different working conditions. The results demonstrate the effectiveness of the proposed method. Full article

This study proposes a rotational speed measurement machine based on the flux-switching principle with a 6-stator-slot/19-rotor-pole (6s/19p) topology. With a rotor shape similar to a variable reluctance sensor (VRS), the proposed machine features a simple and robust structure while ensuring the same output frequency as VRS. Additionally, compared to the conventional 12s/10p topology, the 6s/19p configuration reduces permanent magnet (PM) consumption by half while maintaining high induced voltage characteristics. A nonlinear analytical model (NAM), which incorporates the harmonic modeling (HM) technique and an iterative process, is presented. This model more accurately captures the rectangular shape of the PM and stator teeth while accounting for core saturation effects. Based on this model, the optimal dimensions of the proposed machine are investigated to achieve the best performance for speed measurement applications. A coupling FEA simulation between Ansys Maxwell and Twin Builder further analyzes the machine’s performance. Compared to a commercial product of the same size, the proposed machine achieves 31.5% higher output voltage while ensuring lower linearity errors. Moreover, superior load characteristics are observed, with a voltage drop of only 1.58% at 1500 rpm and 30 mA. The proposed machine and NAM provide an improved solution and analytical tool for speed measurement applications. Full article

Achieving increased fault tolerance in an electric motor requires decisions to be made about the type and specifications of the motor machine and its appropriate design. Depending on the type of motor, there are generally three ways to achieve an increased resistance of the drive system to tolerate resulting faults. The simplest way is to select the right motor and design it appropriately. Switched reluctance motors (SRMs) have a high tolerance for internal faults (in the motor windings). Failure tolerance can be improved by using parallel paths. The SRM 24/16 solution has been proposed, which allows for operation with four parallel paths. In this paper, a mathematical model designed to analyse the problem under consideration is provided. Based on numerical calculations, the influence of typical faults (open and partial short circuit in one of the paths) on the electromagnetic torque generated as well as its ripple and (source and phase) currents were determined. The higher harmonics of the source current (diagnostic signal) were determined. Laboratory tests were performed to verify the various configurations for the symmetric and emergency operating states. The feasibility of SRM correct operation monitoring was determined from an FFT analysis of the source current. Full article

The benefits of utilizing Switched Reluctance Motor (SRM) drives in traction applications can be realized fully by improving the electromagnetic performance of the machine in the generating mode of operation. This is because the generating capability of an SRM drive could be utilized for regenerative braking and also for the machine to generate power for the vehicle while the engine is in operation. In this paper, a current profiling-based control strategy is proposed to reduce the torque ripple in an SRM drive in the generating mode. The reference current profile is determined using a multi-step computation method to minimize torque ripple and maximize the average torque. The reference current profile is derived based on the reference torque command by utilizing the torque–current–angle look up table. The flux linkage characteristics of the SRM are considered when deriving the phase reference current profile. Then, the performance of the proposed profiling method, analytical linear and cubic torque sharing functions (TSFs), and the average torque optimization scheme are compared using simulation results. Finally, an experimental correlation is performed to validate the efficacy of the proposed control scheme. Full article

In this paper, the methodology for designing an asymmetrical four-phase 8/6 switched reluctance motor (SRM) that achieves approximately constant output power over a wide speed range is described. In an asymmetrical 8/6 SRM, orthogonal phase pairs are different in terms of the pole width and number of turns. The main comparison criterion between the asymmetrical and symmetrical 8/6 SRM is the power-speed characteristic, obtained for a given rated RMS phase current of the symmetrical drive. The obtained results demonstrate that the asymmetrical 8/6 SRM allows the shape of the power-speed characteristic to be modified, thereby extending the constant power region well beyond that of the symmetrical configuration with the same rated power level. To make a fair comparison between the asymmetrical and symmetrical 8/6 SRM drives, the converter volt-ampere rating, machine volume, slot fill factor, and ohmic losses per phase are kept constant in all analyzed cases. For determination of the optimal control parameters and maximal drive performance for both designs, the appropriate SRM mathematical model and differential evolution algorithm are used. The applied model includes all substantial non-linearities and mutual coupling between phases. The simulation results are verified using a Finite Element Method (FEM)-based model in the Ansys Electronics 2020 R2 software package. Full article

Switched Reluctance Motors (SRMs), Permanent Magnet Synchronous Motors (PMSMs), and induction motors may experience failures due to insulation-related breakdowns. The SRM rotor is of a non-salient nature and made of solid steel material. There are no windings on the rotor. However, the stator is composed of windings that are intricately insulated from each other using materials such as enamel wire, polymer films, mica tapes, epoxy resin, varnishes, or insulating tapes. The dielectric strength of the insulation may fail over time due to several environmental factors and processes. Dielectric breakdown of the winding insulation can be caused by rapid switching of the winding current, the presence of contaminants, and thermal aging. For reliable and efficient operation of the SRMs and other electrical machines, it is necessary to take into account the physics of the winding insulation and perform appropriate diagnostics and estimations that can monitor the integrity of the insulation. This article presents the estimation problem using a Genetic Algorithm (GA)-optimized Random Forest Regressor. Empirical properties and measurable quantities in the historical data are utilized to derive temperature and leakage current estimation. The developed model is then combined with a moving average function to increase the accuracy of prediction of the stator winding temperature and leakage current. The performance of the model is compared with that of the Feedforward Neural Network and Long Short-Term Memory over the same winding temperature and leakage current historical data. The performance metrics are based on computation of the Mean Square Error and Mean Absolute Error. Full article

The inductance model used in traditional sensorless control methods for switched reluctance machines (SRMs) exhibits high-order harmonics. The precision of the motor may be impacted by the buildup of rotor estimate errors caused by these harmonics. To address this issue, this paper proposes a novel method for SRMs that employs a hybrid algorithm combining an enhanced second-order generalized integrator (SOGI)-based frequency-locked loop (FLL) and an active disturbance rejection control (ADRC)-based phase-locked loop (PLL). This approach involves coordinate transformation and parameter identification to reconstruct the motor inductance model. Rotor position errors are calculated using the unsaturated inductance difference method. In order to enhance the accuracy of motor position estimation, a hybrid algorithm is employed to efficiently filter out harmonic errors and mitigate the tremor effect caused by the rotor position differential algorithm. This hybrid algorithm enables the estimate of the motor’s speed and rotor position. A sensorless control simulation model was developed using a 12/8 pole SRM to assess the motor’s performance under varying load conditions. Based on the results obtained, it is established that the application of this method can accurately estimate the rotor’s position and rotational speed and thus improve the performance of position sensorless control. Ultimately, a prototype system for a switched reluctance motor was created, and the effectiveness and feasibility of the proposed control technique were confirmed through experimental validation. This presents an innovative approach to engineering practice. Full article

The adoption of renewable energy sources, particularly wind energy, has seen remarkable growth in recent years. Wind energy generation requires efficient and reliable generators that can convert wind energy into usable electrical energy. Switched Reluctance Generators (SRGs) have been gaining popularity in wind energy applications due to their high efficiency, reliability, and low maintenance requirements. The multiphase switched reluctance generators are used especially in wind power plants due to their ability to operate in variable speed ranges. In this paper, a MATLAB/SIMULINK based model of Switched Reluctance Generator (SRG) is presented. The obtained results show good agreement under different operating conditions. The obtained results (current, voltage, torque, speed, flux, and angle of generator) are shown in graphs. Full article

This article proposes a new simulation strategy to support the calculation of the angular interval of the current supply to minimize the torque ripple in switched reluctance machines, focusing on the motor working condition. Supposing the best angular interval is strongly linked to the working condition of the machine, a formula is needed to calculate the boundary angles of the intervals of the current supply for each phase, starting from real-time speed and electromagnetic torque. Starting from the dataset of simulations made with this new strategy, linear regression was used to train a model that computes useful formulas. The aim of this research is to show how the application of simple calculations allows torque ripple and power losses to be reduced, i.e., RMS phase currents, without altering the geometry of the machine. Simulations on a virtual four-phase 8/6 SRM are carried out to verify the model’s feasibility and effectiveness, even though this strategy can be easily applied to all other configurations of SRMs. Full article

The optimization of energy production in renewable energy systems is crucial to improve energy efficiency. In this context, the aim of this study focuses on maximizing the efficiency of a switched reluctance generator. This paper presents a novel approach to enhance the electrical power and efficiency of a switched reluctance generator by determining the optimal operating parameters based on the mechanical input power of the system. The proposed strategy consists of the following steps: First, an algorithm was developed that provides machine data for different power modes based on control parameters, including electrical and mechanical powers such as speed, torque, and turn-on and turn-off angles. In the next step, the obtained data were analyzed to identify the optimum points corresponding to the states with maximum power and efficiency for various scenarios. An algorithm for maximum power point tracking was also developed to determine the optimal parameters as a function of mechanical energy. Finally, the data and algorithms were integrated into the switched reluctance generator control system. Simulations were conducted to compare the proposed MPPT technique with other techniques. This comparison is essential to validate the effectiveness of the proposed strategy in achieving enhanced electrical power generation efficiency. Full article

Switched reluctance machines (SRMs) are potential candidates for use in the propulsion systems of electric vehicles. However, they suffer from low power density and high torque ripple. In this paper, a segmented rotor double-sided axial flux SRM (DSAFSRM) is chosen for detailed analysis. A hybrid design algorithm is proposed to take the effects of iron non-linearity into account. The proposed design procedure benefits from simplicity and high accuracy at the same time. A two-step optimization procedure is presented which minimizes the torque ripple of the DSAFSRM without jeopardizing its efficiency. The torque ripple is reduced from 120% to 35% after optimization. In the two-step optimization procedure, both geometrical and switching related parameters are investigated. Moreover, a double-sided radial flux SRM is designed and compared with the proposed DSAFSRM in terms of torque ripple, average torque, efficiency and power density. The results indicate superior performance of the optimized DSAFSRM, especially in terms of average torque, which is 26% higher than the torque produced by the double-sided radial flux SRM. Full article

The torque ripples in a switched reluctance motor (SRM) are minimized via an optimal adaptive dynamic regulator that is presented in this research. A novel reinforcement neural network learning approach based on machine learning is adopted to find the best solution for the tracking problem of the SRM drive in real time. The reference signal model which minimizes the torque pulsations is combined with tracking error to construct the augmented structure of the SRM drive. A discounted cost function for the augmented SRM model is described to assess the tracking performance of the signal. In order to track the optimal trajectory, a neural network (NN)-based RL approach has been developed. This method achieves the optimal tracking response to the Hamilton–Jacobi–Bellman (HJB) equation for a nonlinear tracking system. To do so, two neural networks (NNs) have been trained online individually to acquire the best control policy to allow tracking performance for the motor. Simulation findings have been undertaken for SRM to confirm the viability of the suggested control strategy. Full article