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To achieve high precision and robust control of switched reluctance machines (SRMs), this paper proposes a novel rotor position estimation method based on gain-optimized sliding mode observer (SMO) with neural networks and whale optimization algorithm. For the SMO, this paper uses the easily measured phase current to constitute the error function of the SMO, which requires less pre-stored data. Using the neural networks' powerful nonlinear mapping capability, the relationship between the sliding mode gains and speed estimation error and the position estimation error is obtained, and then the whale optimization algorithm is used to find the optimal sliding mode gains in the restricted range. The simulation and experiment results show that the accuracy of the SMO control system is significantly improved. [ABSTRACT FROM AUTHOR]

Variable reluctance motor is becoming a competitive candidate among all other machines available due to its added features. The development of variable reluctance motor is simple due to the simple construction of rotor without any permanent magnets. Reduced complexity in structure paves the way for low-cost motor and it also leads to the application of SRM in a wide manner. In order that the machine could be used in various applications, it is much necessary to have a suitable driving system (converter configuration). The best choice of converter for SRM would pave the way for desirable control of the machine. The proposed work includes the design and analyses of an appropriate driver configuration for SRM and interface it with the motor which is already designed and analyzed using ANSYS Maxwell. The design and analysis of the converter are carried out using the ANSYS Simplorer tool box. [ABSTRACT FROM AUTHOR]

An online torque sharing function (TSF) with instantaneous torque error compensation method for switched reluctance machines is proposed to maintain a minimized ripple operation. The proposed method adjusts the shared torque between the phases based on instantaneous torque error different than the existing TSF methods formulated with a mathematical expression. The objective of this approach is to benefit from the outgoing phase torque as it has slow current dynamics due to the high inductance. Also, the incoming phase is turned on as soon as it can generate positive torque. During this process, the total torque is estimated instantaneously using lookup tables, and a correction current is calculated and injected into the incoming phase reference current as the inductance is low and current dynamics are fast. This way, the torque ripple is reduced for a wide speed range. Compared to the conventional linear, sinusoidal, exponential, and cubic TSFs, better torque ripple performance is obtained.

Reducing vibration and noise in electrical machines for a given application is not an easy task, especially when the application imposes some restrictions. There are many techniques for reducing vibration based on design or on control. Switched reluctance motors (SRMs) have a double-saliency structure, which results in a radial pulsation force. Consequently, they cause vibration and acoustic noise. This paper investigates the correlation between the radial force and the skew angle of the stator and/or rotor circuits. The analysis is computed from two-dimensional (2D) transient magnetic finite-element analysis (FEA) of three machine topologies, namely the 12/8 three-phase SRM, the 6/4 three-phase SRM and the 8/6 four-phase SRM. Compared to SRM, these topologies have the same basic dimensions (stator outer diameter, rotor outer diameter, and length) and operate in the same magnetic circuit saturation. The flux linkage and torque characteristics of the different motors are presented. The radial force distributed on the stator yoke under various skewing angles is studied extensively by FEA for the three machines. It is also demonstrated the effect of skewing angles in the reduction of radial force without any reduction in torque production.

This article introduces a new technique for reducing the time of calculating radial and tangential force density waves of switched reluctance machines (SRMs). The method is based on the finite element (FE) simulation of a fraction of an electrical cycle. The new approach shows that a significant time reduction is achieved as compared to the time required for stator radial force density and the rotor tangential force calculation based on the one mechanical cycle simulation method. As the switched reluctance motors introduce new challenges in aspects such as acoustic noise, vibrations, and torque ripples, the method introduced in this paper will help reduce the time of the optimization process of switched reluctance machines in the design stage to improve the machine performance. The proposed method is applied to radial flux SRMs. Three different topologies were used to show the effectiveness of this technique in different force components with minimal error as compared to the benchmark method based on the FE simulation of one mechanical cycle.

An online torque sharing function (TSF) with instantaneous torque error compensation method for switched reluctance machines is proposed to maintain a minimized ripple operation. The proposed method adjusts the shared torque between the phases based on instantaneous torque error different than the existing TSF methods formulated with a mathematical expression. The objective of this approach is to benefit from the outgoing phase torque as it has slow current dynamics due to the high inductance. Also, the incoming phase is turned on as soon as it can generate positive torque. During this process, the total torque is estimated instantaneously using lookup tables, and a correction current is calculated and injected into the incoming phase reference current as the inductance is low and current dynamics are fast. This way, the torque ripple is reduced for a wide speed range. Compared to the conventional linear, sinusoidal, exponential, and cubic TSFs, better torque ripple performance is obtained. [ABSTRACT FROM AUTHOR]

In electric vehicles, performances of electric vehicle drivetrains depend on the electric machine and the control. Switched Reluctance Machines (SRMs) are today an alternative to rare earth magnets machines such as Permanent Magnet Synchronous Machine (PMSM), which is used in the vehicle drivetrain. Because of its high nonlinear behavior, the classical control designed for SRMs is not sufficient to obtain good performances. The objective of this paper is to make performance and robustness comparisons of the designed robust controllers considering the high nonlinear behavior of SRMs. Sliding Mode Control (SMC) and Super-Twisting Sliding Mode Control (STSMC) are developed and validated by simulation for the velocity control loop and the current control loops of the control strategy. However, an evaluation of their performances compared to classical control based on PI controllers is carried out. For a robustness comparison, a variation of SRM parameters is carried out by simulation using the three controllers. Finally, an experimental validation on a developed test bench using the three controllers is conducted to show that Super-Twisting Sliding Mode Control (STSMC) is the best in terms of performances and robustness for an electric vehicle application. [ABSTRACT FROM AUTHOR]

This paper presents the comparisons between two types of switched reluctance machines (SRMs) and SRM converters. An SRM with a segmental rotor is compared with a conventional SRM (CSRM), and an SRM converter containing a passive boost circuit is compared with a conventional asymmetric half-bridge (AHB) converter. The segmental SRM has an asymmetric rotor with a segmented structure. The four rotor segments are made of steel laminations. Two segments are misaligned with the other two by 15 degrees. The torque ripple of the SRM with this structure is decreased, and the static torque is increased compared to a conventional SRM. The boost converter comprises a front-end circuit and a conventional AHB converter. The front-end circuit boosts the voltage level. The boosted voltage accelerates the rising and falling progress of the phase current. In this way, the SRM can obtain a greater speed and a smaller torque ripple. The comparison is conducted in simulation and validated through the experimental results. The experiment results have demonstrated that the segmental SRM obtains a maximum 7% torque ripple reduction at a low-speed range, compared to the CSRM. With the boost converter, both the CSRM and the segmental SRM can achieve a lower torque ripple and a higher maximum speed. [ABSTRACT FROM AUTHOR]

The switched reluctance motor (SRM) is a promising candidate for electric propulsion systems. In the design process of an SRM, the motor geometry needs to be determined. Using the finite element method (FEM) might be time-consuming for the sizing of the motor geometry. As an alternative, electromagnetic models based on a magnetic equivalent circuit (MEC) can be utilized for the sizing of an SRM. MEC models require fewer computational resources and can help determine the electromagnetic performance with reasonable accuracy. Using the conventional MEC method for SRM sizing might be challenging since the flux pattern inside the motor should be changed for different motor dimensions. In order to address this challenge, this paper applies a reluctance mesh-based MEC technique to determine the geometry of a three-phase 12/16 SRM for a high-lift motor in the NASA Maxwell X-57 electric aircraft. A comprehensive reluctance mesh-based MEC model is developed for this purpose. Both the static and dynamic characteristics of the SRM geometry are evaluated using the reluctance mesh-based MEC method. The determined geometry is verified using the results computed from FEM. [ABSTRACT FROM AUTHOR]

The main component in renewable energy and electrical vehicles is the electric motor. The choice of a low-cost motor, easy to maintain and with high efficiency is an important issue. Because of its many advantages, the switched reluctance machine (SRM) can be a suitable solution. However, the SRM is characterized by a so extremely nonlinear behavior, making the control of these devices very crucial issue. Then, The SRM is often run in the magnetically saturated mode. Furthermore, the most of available works have been based on several approximations. Presently, an analytical model and identification method for SRM are established. Then, the magnetization characteristics of SRM can be easily obtained using the proposed model. Unlike previous research, the inherent magnetic nonlinearity and the hysteretic effect of SRM are taken into consideration. Furthermore, a standstill test identification method based on fuzzy techniques is proposed. Then, it is verified that the SRM can be modeled by a fuzzy Wiener model. Specifically, it can be described by the series connection of a linear block and a static Takagi–Sugeno fuzzy model. Finally, the magnetization characteristics of SRM and the SRM model parameters can be achieved. The obtained results show the effectiveness of the proposed solution based on fuzzy logic techniques. [ABSTRACT FROM AUTHOR]

Acoustic noise and vibration is one of the shortcomings of a switched reluctance machine (SRM). Harmonics of the radial force waveform in the airgap excite the stator structure at different vibration modes with specific frequencies. The radial force density in the airgap should be calculated before analyzing and mitigating acoustic noise and vibration. This paper proposes a reluctance mesh-based magnetic equivalent circuit (MEC) model to calculate the airgap radial force density. Reluctance mesh-based MEC models are developed for 3-phase 6/4, 6/16, 12/8 and 4-phase 8/6, 8/10, and 16/12 SRMs. A technique for the dynamic modeling of SRMs is proposed using the reluctance mesh-based MEC method. Dynamic currents are calculated using the proposed technique and, then, the radial and tangential flux density in the airgap are calculated. The radial force density in the airgap is calculated by applying the Maxwell Stress Tensor method. Fourier series is used to calculate the harmonics of the radial force density. The results obtained from the MEC model are verified using finite element method (FEM) models. The implemented MEC-based dynamic modeling method is validated using experimental results.

This paper proposes a novel electromagnetic modelling method, with experimental study of the magnetic can-shield effect, based on a novel canned switched reluctance machine. Such model considers the characteristic electromagnetic coupling relation between magnetic flux and eddy current on cans, with harmonic analysis by analytical calculation in vector form. The model is structured with multiple concentrated layers in cylindrical coordinate and the main modeling process includes domain solution of the magnetic field, and an energy vector deduction for loss and energy. Comparative measurement with an indirect method demonstrates the electromagnetic features by the use of cans and meanwhile verifies the analytical model. [ABSTRACT FROM AUTHOR]

In this article, a switched reluctance machine (SRM) with six phases and a misaligned segmental rotor is proposed. The segmental rotor has an internal 15-degree misalignment, allowing the SRM structure to be a one-layer 2D structure with a short flux path structure. The proposed SRM produces a relatively low torque ripple by exciting two phases simultaneously. Additionally, an optimization method is applied, allowing for the maximum torque position of one phase to be aligned with the zero-torque position of the adjacent phase. The finite element method (FEM) is used to analyze and design the proposed SRM and to simulate the proposed liquid cooling system. The static torque waveforms are analyzed, and the dynamic torque waveforms are simulated with a drive using SiC MOSFETs. Finally, a prototype is manufactured, and the experiment is performed to validate the design and simulation results. [ABSTRACT FROM AUTHOR]

In this paper, a finite element analysis (FEA) based fast optimization method to optimize a lightweight in-wheel switched reluctance machine is presented. This method speeds up the switched reluctance machine optimization procedure by running the FEA simulations with single-phase constant current excitations for half electrical cycle and estimating the machine performance metrics using the gathered FEA data. Hence, the machine's dynamic performance estimation process takes shorter for each design candidate. The optimization algorithm employs designs of experiments (DOE), response surface (RS) analysis method, and differential evolution algorithm (DE). Here, the DOE method is used to reduce the search space by narrowing down the upper and lower boundaries of each design variable based on the RS analysis. Although this process does not guarantee getting the Pareto front, it places the search space close to the actual one. Hence, the multi-objective DE optimization finds the Pareto optimal solution set without requiring a large number of iterations as well as a large number of candidate designs for each iteration. The method is applied to a 24/16 SRM that is intended to be used in a lightweight race car as a hub motor. Six dimensionless geometric variables are optimized to satisfy three objective functions, namely torque ripple, motor mass, and copper loss. While the conventional DE takes at least 3000 candidate designs, the proposed method considers only 559 designs to reach a similar Pareto front. It is observed that the proposed method takes about 6 h 30 min compared to the conventional method that takes 32 h 50 min using the same computer. Therefore, the computation time is reduced almost five times with the proposed method. [ABSTRACT FROM AUTHOR]

In this study, the fully pitched axial flux switched reluctance machine (FP-AFSRM), which is a new configuration in the literature, was designed and 3D magnetostatic analyses were performed. The focus of the study is to produce higher torque density by simply changing the winding structure. Conventional SRMs are also known as short pitched SRM (SPSRM) since they have a short pitched winding structure. Fully pitched SRMs (FPSRMs) produce higher torque compared to SPSRMs with the mutual coupling effect between phases due to their fully pitched winding structure. In parallel with that, especially for electric vehicles, axial designs have increased gradually instead of radial design of electrical machines. For this purpose, the FP-AFSRM structure was proposed by combining axial design and fully pitched winding structure. The proposed FP-AFSRM model achieved up to 15.07% higher torque density than the basic SP-AFSRM model at different currents and equal copper losses. The proposed FP-AFSRM can be considered as an important alternative machine, especially for electric vehicle technologies and different technological fields, with the advantages of the high torque density and axial geometric structure. [ABSTRACT FROM AUTHOR]

Copyright of Dicle University Journal of Engineering / Dicle Üniversitesi Mühendislik Dergisi is the property of Dicle Universitesi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The switched reluctance machine has been an attractive candidate for many applications owing to its simple design and low construction costs, without the use of permanent magnets. However, the double saliency of its stator and rotor poles results in noise-causing torque ripples. And although advanced torque ripple minimization control techniques exist, they rely on modeling the machine, which in turn requires specialized offline experimental setups or online (during operation) parameter identification techniques. To date, existing online techniques are iterative without proof of convergence, do not provide all model parameters, and/or rely on a priori information that can change after the machine is commissioned. In this work, an online parameter identification method is developed with a new empirical model of its flux linkage and electromagnetic torque, to provide a complete nonlinear model of the machine. With two seconds of data collected online, all electrical and mechanical parameters are identified using a non-iterative algorithm, and so it does not pose a risk of divergence. Therefore, parameter identification can be reliably and frequently carried out at different operating conditions as the machine ages for diagnostics. Also, the resulting model is designed to be used by advanced torque ripple minimization control techniques. The implementation procedure is detailed along with simulation results to demonstrate its efficacy.

This article advocates the use of two different optimization techniques, namely, gravitational search algorithm (GSA) and particle swarm optimization (PSO), to obtain suitable combinations of firing angles for the asymmetric half bridge converter (AHBC) to ensure optimum power extraction from a switched reluctance generator (SRG) based wind power generating system, at any given wind speed. As optimum power generation from an SRG turns out to be a multi‐dimensional search problem due to the nonlinear magnetic behavior of the machine, optimization techniques can be aptly employed for obtaining suitable values of control parameters. The techniques considered in this work, GSA and PSO, do not require any information about the geometrical features of the machine. Both techniques are implemented with an outer power control loop to propel the machine to perform optimally at variable wind speeds. Simulated results obtained by modeling these techniques in MATLAB environment are validated with the experimental results from a laboratory prototype consisting of a 1 hp, 2000 rpm, 8/6 SRM, and an AHBC. The results presented bring out the relative merits and demerits of the optimization techniques, thus highlighting their suitability for actual field implementation. [ABSTRACT FROM AUTHOR]

The main objective of modeling a switched reluctance machine is to derive a mathematical function to relate the outputs to the inputs. Due to the nonlinear relationship between the variables of torque, flux linkage, current and angular position of the rotor, Switched Reluctance Machine (SRM) modeling is a very challenging task and an open problem. Modeling is usually done in two situations, modeling a single machine, or modeling a set of machines. Each one must fulfill different requirements. This work presents a survey of different SRM modeling approaches, evaluating its advantages and limitations when modeling a single machine or a set of machines.

Abstract This article advocates the use of two different optimization techniques, namely, gravitational search algorithm (GSA) and particle swarm optimization (PSO), to obtain suitable combinations of firing angles for the asymmetric half bridge converter (AHBC) to ensure optimum power extraction from a switched reluctance generator (SRG) based wind power generating system, at any given wind speed. As optimum power generation from an SRG turns out to be a multi‐dimensional search problem due to the nonlinear magnetic behavior of the machine, optimization techniques can be aptly employed for obtaining suitable values of control parameters. The techniques considered in this work, GSA and PSO, do not require any information about the geometrical features of the machine. Both techniques are implemented with an outer power control loop to propel the machine to perform optimally at variable wind speeds. Simulated results obtained by modeling these techniques in MATLAB environment are validated with the experimental results from a laboratory prototype consisting of a 1 hp, 2000 rpm, 8/6 SRM, and an AHBC. The results presented bring out the relative merits and demerits of the optimization techniques, thus highlighting their suitability for actual field implementation.

This article reports design and testing of silicon carbide) devices-based three-phase asymmetric H-bridge converter capable of switching at 50 kHz and intended to drive high-speed switched reluctance machine. Electromagnetic designs of a 7.5-kW, 30 000-r/min and a 20-kW, 50 000-r/min Switched reluctance machine are presented. The 30 000-r/min machine is fabricated and characterized. A machine model is obtained from the measured characteristics. Based on the machine model, as well as drive operating variables and device data-sheet parameters, two methods are proposed for evaluating the losses in the power devices. The first method relies on machine model to obtain machine current and converter duty ratio, and thereby estimate the device losses. A second simplified method provides closed-form expressions for device losses. The proposed analytical expressions relate the machine characteristics such as inductance and saturation current with converter losses. The estimated loss is further used to predict device junction temperature. The power converter and device ratings are chosen so that the converter is suitable for both machines. The capacitor selection and sizing are discussed. Further, the power converter architecture and other subsystems of the converter are described. Test results are presented for the asymmetric H-bridge converter at 800 V dc bus voltage, 50 A of load current, and 50 kHz of switching frequency. Thermal image is presented for validation of estimated heat-sink temperature. The predicted heat-sink temperature is found to agree well with the measured temperature. The power converter is used to operate the 30 000-r/min machine at various speeds. [ABSTRACT FROM AUTHOR]

The switched reluctance motor (SRM) is a promising candidate for electric propulsion systems. In the design process of an SRM, the motor geometry needs to be determined. Using the finite element method (FEM) might be time-consuming for the sizing of the motor geometry. As an alternative, electromagnetic models based on a magnetic equivalent circuit (MEC) can be utilized for the sizing of an SRM. MEC models require fewer computational resources and can help determine the electromagnetic performance with reasonable accuracy. Using the conventional MEC method for SRM sizing might be challenging since the flux pattern inside the motor should be changed for different motor dimensions. In order to address this challenge, this paper applies a reluctance mesh-based MEC technique to determine the geometry of a three-phase 12/16 SRM for a high-lift motor in the NASA Maxwell X-57 electric aircraft. A comprehensive reluctance mesh-based MEC model is developed for this purpose. Both the static and dynamic characteristics of the SRM geometry are evaluated using the reluctance mesh-based MEC method. The determined geometry is verified using the results computed from FEM.

The prospect of physical exertion commonly acts as a deterrent to the adoption of cycling for everyday transport. A battery powered assistance torque electric motor could alleviate such physical exertion by reducing the effort required by the cyclist. This study investigates the potential effectiveness, efficiency, and energy saving of electrically-assisted cycling when assistance torque of a switched reluctance motor is designed to vary in accord to the cyclist instantaneous torque at the pedal cranks. Specifically, the modulated motor assistance torque is delivered at the least efficient human input torque points on the cycle. For a representative short distance cycling schedule modulating the instantaneous torque of the on-board electric motor causes the electric energy expenditure to not exceed that of the assisted cycling mode of an identical constant-torque motor. Furthermore, for the same speed profile cycling journey with added road gradient and head wind resistance, the energy expenditure of the modulated torque motor is equal to the constant torque motor. These findings indicate significant improvements in the cycling experience.

Additive manufacturing is acknowledged as a key enabling technology, although its adoption is still constrained to niche applications. A promising area for this technology is the production of electrical machines (EMs) and/or their main components (e.g. magnetic cores, windings, heat exchangers, etc.) due to the potential of creating lightweight, highly efficient rotating motors, suitable for applications requiring a low moment of inertia. This work investigates the readiness of metal additive manufacturing, specifically Laser Powder Bed Fusion (LPBF), applied to the field of EMs to bridge the gaps of how to use this technological approach in this field. A soft magnetic material featuring high silicon content (Fe-5.0%w.t.Si) has been developed for LPBF and a rotor has been 3D-printed for a switched reluctance machine. The printed rotor was assembled into a conventionally laminated stator and the performance of the whole machine was evaluated. Its performance was compared against an identical machine equipped with a laminated rotor of the same dimensions made of conventional non-oriented silicon steel. A comparative study was carried out through both finite element simulations and experimental tests. The efficiency of the two machines was assessed together with the principal electrical and mechanical quantities under several operating conditions.

The work presented in this paper concerns the study of the thermal behavior due to copper losses and iron losses of a switched reluctance machine with double salience (SRM6/4) by analytical coupling - 2D finite elements. Calculation by analytical methods of the conduction coefficients in the radial and axial direction as well as the convection coefficients in the air gap of this machine are presented. The values of these found coefficients are used to solve the transient thermal problem for this device using the ADEMEF2D software. The obtained results show a very large increase in temperature at the winding. Heat conduction in both radial and axial directions has a very large effect on the temperature value in all regions of the SRM6/4.

In the present paper, a simple model based on magnetic equivalent circuit (MEC) method is introduced for the switched reluctance machine to predict the phase flux linkage characteristic. All equations required to build up the model are given, and therefore, someone can use it easily for different types of the switched reluctance machines. Because of large speed of the suggested model, it can be utilized properly for quick prediction of machine performance. The suggested MEC model is applied to a typical 8/6 switched reluctance motor (SRM), and simulation results including flux linked by a phase, phase current and instantaneous torque are presented. In order to validate the suggested MEC model, the obtained simulation results are compared to those derived from finite element method (FEM) and experimental results. [ABSTRACT FROM AUTHOR]

In this article, a method to evaluate the dc-link capacitor rms current of a switched reluctance motor (SRM) drive under different operating conditions is presented. Square current reference in both hard and soft chopping modes of pulsewidth-modulated current control is considered. By approximating the current controller response and using a recently proposed flux linkage model, the switching-cycle-average phase voltage and current are evaluated over an electrical cycle. The phase voltage and current are further used to obtain the rms values of dc-link current and capacitor current. The proposed method is also used to determine the capacitor current for low-torque-ripple current reference and single-pulse operation. The analytical predictions pertaining to different control methods under different operating conditions are verified by simulation and experimental results obtained from a 4 kW, 1500 r/min, four-phase SRM drive. While the capacitor current is found to be maximum at the lowest operating speed with hard chopping, the maximum capacitor current is observed at an intermediate speed with soft chopping, both for a given magnitude of square wave current reference. The proposed method is useful to size the dc-link capacitor and evaluate its loss in an SRM drive. Furthermore, closed-form expressions for capacitor rms current are also derived, assuming perfect tracking of square wave current reference at low speeds. These expressions bring out the dependence of capacitor rms current on the machine characteristics. [ABSTRACT FROM AUTHOR]

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

High-speed electrical machines have been of great research interest because of their excellent efficiency and high storage capacity. In the case of switched reluctance machines (SRMs), position feedback is required for effective operation. The installation of this sensor in a high-speed flywheel is difficult and expensive. This paper proposes and analyses a methodology to estimate the position of a SRM and remove the position encoder to apply the machine as a flywheel at 50,000 rpm. The machine is modeled with non-linear characteristics, and is simulated under single-pulse operation due to the high-speed. Two configurations of the sensorless method are presented: Robust Method and Sequential Method. The robust configuration identifies the firing angles position only, while the sequential setup can track any position. Both configurations present advantages and disadvantages in relation to the error of estimation and to the number of estimations. The methods are tested in closed-loop speed control. In the two cases, the position estimation supports satisfactory results for simulating operation of the machine at high speed.

Switched reluctance motors (SRMs) have a robust and simple structure, high reliability because of the absence of magnetic field source on rotor, low cost and simple cooling system. However, conventional SRMs confront with some challenges such as low mean torque, low torque density and high torque ripples. For wider applications of SRM, the above-mentioned drawbacks must be mitigated. One possible method is changing the structure of SRMs. In this article, a novel 12/14 three-phase SRM with connected C-core structure is introduced which has a short path for the main flux of stator teeth. This brings about core loss reduction. On the other hand, both teeth of the stator phase in C-core develop a positive torque during the movement of the rotor from the unaligned position to the aligned position; this enhances the torque, the mean torque and torque density of the proposed SRM, keeping the volume fixed. Finally, the proposed SRM was prototyped and tested and its torque/rotor angular position characteristic was measured. To verify the novelty and merits of the proposed SRM, its mean and peak torque, torque density, core losses and torque ripples were compared with those of an optimized 12/8 three-phase conventional SRM and a significant match was achieved. [ABSTRACT FROM AUTHOR]

The torque production mechanism of switched reluctance machines (SRMs) is investigated from the perspective of air-gap field modulation principle. The unipolar stator current excitations can be divided into DC and AC components and they induce the air-gap magneto-motive force (MMF) respectively. Meanwhile, thanks to the salient structure in SRMs, the air-gap MMFs induced by the two sources above can be modulated to obtain the synchronized air-gap fields for torque production. It is revealed that a multitude of field harmonics contribute to the torque together. The MMF-permeance model is built and the analytical deduction of the field modulation effect is provided, with which the orders of the field harmonics contributing to the torque output can be identified. Moreover, finite element method is employed to verify the predictions on various SRM topologies. Finally, aprototype machine is fabricated and measuredfor validation. [ABSTRACT FROM AUTHOR]

Relatively high torque ripple limits the further development of the switched reluctance machine, and the application of the ripple suppression method will reduce the efficiency of the system. To simultaneously improve the efficiency and torque ripple of the switched reluctance machine, a new commutation and online optimization strategy is proposed. According to the torque per ampere characteristics of the machine, two rotor position angles are defined, which are the boundaries for the high and low torque per ampere operation modes of the two adjacent phases, respectively, and for different operating modes, specific torque hysteresis control schemes are performed. Furthermore, an objective function is constructed with the efficiency and torque ripple coefficient, and during the operation of the machine, the defined boundary angles are online optimized by the genetic algorithm to maximize the value of the objective function. The effectiveness of the method is verified by detailed simulation and experiment under different operating conditions. [ABSTRACT FROM AUTHOR]

In the design processes of Switched Reluctance (SR) Machines that operate in wide constant power speed ranges, the maximum power available at maximum speed must be evaluated for every machine candidate. This is critical to ensure compliance with the power requirement. Important parameters to include in the design routine are the duration of the energizing period and the advance of the turn-on instant, i.e., advance angle. The latter is highly related to the machine geometry and is usually evaluated through time-consuming finite-element-based iterative methods. In this article, a simple, yet novel analytical model is proposed to cater for the torque-maximising advance angle in a closed-form analytical expression, directly from the machine geometry. The goal is to provide a non-iterative design tool that speeds up the design process. Successful validations against finite element analyses and experimental results on an SR machine prototype are reported. The main outcome of this article is shown by the improvement in computation time, without any significant loss of accuracy. [ABSTRACT FROM AUTHOR]

The goal of this paper is to present a comparative analysis of two types of winding arrangements for a three-phase 12/8 switched reluctance motor (SRM), where short- and fully-pitched winding arrangements under unipolar operation are considered. From the analytical results, the short-pitched winding has the best torque per copper weight ratio. The core loss based on counting the number of flux reversals in the stator yoke for each winding arrangement is also proposed and mentioned. To reduce the magnetic flux reversals in the stator core, changing the direction of the magnetic flux path by modifying the winding polarities of the short-pitched winding could reduce 10–13% of core loss compared to the conventional winding. A 1 kW, 12/8 SRM prototype for the ventilation fan application is constructed and tested in order to verify the design consideration of winding configuration. At the rated condition, a maximum efficiency around 82.5% could be achieved.

This paper presents a high resolution automatic system capable of performing magnetic characterization tests and obtaining the data needed to conduct reliable models for switched reluctance machines (SRM). In addition, the detailed description of the instrumentation system performed in this paper has as contribution the study of mathematical interpolation techniques for the treatment process of test data to obtain a nonlinear model based on lookup tables. It was observed that the commonly used polynomial regressions may cause inaccuracies in the final characteristics of the model data. Thereat, smoothing splines were applied, which results in more accurate and consistent results for the SRMs operation. Thus, it is possible to obtain control projects, optimization systems and advanced studies through computer simulations. Simulation and experimental results have proved the efficiency of the system and have confirmed the importance of achieving real curves when accurate models of a SRM are needed.

The modeling and simulation of Switched Reluctance (SR) machine and drives is challenging for its dual pole salient structure and magnetic saturation. This paper presents the input data in form of experimentally obtained magnetization characteristics. This data was used for computer simulation based model of SR machine, “Selecting Best Interpolation Technique for Simulation Modeling of Switched Reluctance Machine” [1], “Modeling of Static Characteristics of Switched Reluctance Motor” [2]. This data is primary source of other data tables of co energy and static torque which are also among the required data essential for the simulation and can be derived from this data. The procedure and experimental setup for collection of the data is presented in detail.

The utilization of position sensor reduces the system reliability of switched reluctance motor (SRM), especially in harsh environments. It also increases the complexity of the system. Therefore, the research on sensorless control has become one of the hot spots in recent years. Comparing with the existing sensorless control technology, the new method exploring the sensorless control of double-sided linear switched reluctance motor (DLSRM) shows the following advantages:1)high accuracy , and 2) good practicability. Based on the new proposed method, the DLSRM speed controller is augmented with the peak current method and the voltage chopping closed-loop speed control. Moreover, the winding resistance in the equation is corrected according to the integral flux linkage when the phase current is zero. The accuracy and feasibility of the simplified flux linkage method in estimating the position of the DLSRM is verified.

Double Stator Switched Reluctance Machine (DSSRM) is a novel switched reluctance machine with limited information about its heat distribution and dissipation. This paper presents a two dimensional (2-D) thermal analysis of Double Stator Switched Reluctance Machine (DSSRM) to observe actual heat distribution in the parts of the machine, using Finite Element Method (FEM). Two topologies for the rotor of DSSRM are considered, Non-Squirrel Cage Double Stator Switched Reluctance Machine (NSC-DSSRM) and Squirrel Cage Double Stator Switched Reluctance Machine (SC-DSSRM). The heat distribution of these two topologies is analyzed, using Computational Fluid Dynamics (CFD). Finally the results are presented and compared.

Aiming at the noise suppression of switched reluctance machine (SRM), the two-step commutation control method is improved. Combining this with pulse width modulation (PWM), the optimisation problem of the switching angle is studied and analysed and given a method to determine the turn-on angle, the zero-voltage turn-off angle and the turn-off angle of the negative bus voltage online. The control method is verified by MATLAB/Simulink simulation and experimental prototype platform. The results show that this method is simple and effective. It can achieve variable angle control, and can reduce the operating noise of the motor under different speed and load conditions. It has a high application value in the field of switched reluctance motor-type electric vehicle development.

To effectively find a valid solution in the development process of electrical machines, it is essential to predict machine iron loss in the pre-design stage. In guidance on the choice of the most suitable configuration of the switched reluctance machine (SRM) is given, but iron loss prediction is neglected. Based on the study of Burkhart et al., this study proposes a simplified model to efficiently calculate iron loss in the design procedure of SRMs. For this purpose, a maximum co-energy loop control method is implemented to facilitate the estimation of flux waveform and machine torque. Three different iron loss calculation methods are compared in terms of accuracy and time. The accuracy of the simplified model is verified by comparison with finite element simulation results. Furthermore, the impact of different parameters on the iron loss is discussed, and the iron loss of various machine geometries is comparatively analysed.

The switched reluctance machine (SRM) design is different from the design of most of other machines. SRM has many design parameters that have non-linear relationships with the performance indices (i.e., average torque, efficiency, and so forth). Hence, it is difficult to design SRM using straight forward equations with iterative methods, which is common for other machines. Optimization techniques are used to overcome this challenge by searching for the best variables values within the search area. In this paper, the optimization of SRM design is achieved using multi-objective Jaya algorithm (MO-Jaya). In the Jaya algorithm, solutions are moved closer to the best solution and away from the worst solution. Hence, a good intensification of the search process is achieved. Moreover, the randomly changed parameters achieve good search diversity. In this paper, it is suggested to also randomly change best and worst solutions. Hence, better diversity is achieved, as indicated from results. The optimization with the MO-Jaya algorithm was made for 8/6 and 6/4 SRM. Objectives used are the average torque, efficiency, and iron weight. The results of MO-Jaya are compared with the results of the non-dominated sorting genetic algorithm (NSGA-II) for the same conditions and constraints. The optimization program is made in Lua programming language and executed by FEMM4.2 software. The results show the success of the approach to achieve better objective values, a broad search, and to introduce a variety of optimal solutions.

Minimizing torque ripple in electrical machines for a given application is not a straightforward task, especially when the application imposes certain constraints. There are many techniques to improve torque ripple, either design-based or control-based. In this paper, a new geometry for switched reluctance machines based on rotor poles skewing is proposed to minimize torque ripple. This paper describes a methodology to design an asymmetrical skew rotor—switched reluctance machine using a multi-objective differential evolutionary algorithm. The main parameters of the optimization process are defined, as is the optimization methodology to obtain an improved design with less torque ripple than a conventional one. Moreover, the analytical formulas used in the optimization method, as well as the optimization technique, are deduced and explained in detail. The mathematical model used to simulate the electrical machine and the power converter are also described. Two-dimensional and three-dimensional finite element analyses were also conducted to assess whether 3D effects (end-effect and axial fringing field) affected the results. Finally, a particular case of a high-voltage direct current-controlled generator in the base of the More Electric Aircraft (MEA) concept or an energy storage system as an electrical machine was analyzed, and the results for the improved configuration were compared with those for the conventional one.