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High torque ripple can be observed with a 6/4 variable flux reluctance machine (VFRM). In order to minimize the torque ripple in VFRMs, this paper presents a harmonic injection method for 6/4 VFRMs with an open-winding configuration. By analyzing the impact of harmonics on VFRMs, the method involves detecting the third harmonic using a first-order low-pass filter (FLPF). Subsequently, the extracted harmonics are controlled and shifted to counteract the voltage harmonics in both inverters without inducing phase imbalance or overvoltage. With the proposed method, the torque ripple can be significantly reduced by about 50% under load conditions. The effectiveness of the harmonic injection method is validated through a prototype VFRM. [ABSTRACT FROM AUTHOR]

This paper contains research on the development of a fault-tolerant six-phase synchronous reluctance motor (SynRM) based on the stator adopted from a general-purpose three-phase induction motor. In the design and calculation process, an extended Clarke transformation was developed for a six-phase asymmetrical system. To verify the proposed design approach, a field–circuit model of electromagnetic phenomena in the studied motor was developed and used to study the motor performance. The increased torque value and reduction in torque ripples were confirmed by comparison to the classical three-phase SynRM design. To illustrate fault tolerance capabilities, the operation of the studied three- and six-phase synchronous reluctance motors under inverter-fault conditions was examined. The conducted analysis shows, among other things, that from the electromagnetic performance point of view, only the proposed six-phase machine is able to properly operate under inverter-fault conditions. The results of the winding design calculations, the performed simulations of six-phase motor operation, and the preliminary tests of the prototype motor are presented and discussed. [ABSTRACT FROM AUTHOR]

This document discusses the importance of condition monitoring and fault diagnosis in electrical machines and devices. It highlights the benefits of these practices, such as failure prediction, cost reduction, and prevention of damage and downtime. The document also mentions the use of artificial intelligence and machine learning in fault diagnosis and control. The special issue focuses on topics such as modeling, control strategies, failure detection, fault-tolerant control, condition monitoring techniques, and AI and machine learning techniques. The document provides summaries of 10 scientific research articles published in the special issue, covering various aspects of electrical machine modeling, control, and diagnosis. [Extracted from the article]

The inverter dead time effect is non-negligible for the control performance of sensorless synchronous reluctance motor (SynRM) drives at low speeds. In this paper, a reduced-order observer-based sensorless control method for SynRM drives combined with the adaptive linear neurons (ADALINE)-based dead-time compensation is proposed. The reduced-order observer-based sensorless control method is presented, for which is parameter tuning is easy. On this basis, the dead-time compensation strategy using ADALINE filters is proposed to reduce the voltage harmonics effect on the estimation performance of the reduced-order observer. With ADALINE filters, the sixth current harmonic can be successfully filtered out by compensating the voltage directly or fitting the current to compensate the voltage. In this way, the low-speed estimation performance of the reduced-order observer is improved. The effectiveness of the proposed method is verified on a 3 kW SynRM experimental platform. [ABSTRACT FROM AUTHOR]

There is limited research focused on achieving optimal torque control performance of Switched Reluctance Generators (SRGs). The majority of existing studies tend to favor voltage or power control strategies. However, a significant drawback of SRGs is their susceptibility to high torque ripple. In power generation systems, torque ripple implicates fluctuations in the generated power of the generator. Moreover, high torque ripple can lead to mechanical vibrations and noise in the powertrain, impacting the overall system performance. In this paper, a Torque Sharing Function (TSF) with Indirect Instantaneous Torque Control (IITC) for SRG applied to Wind Energy Conversion Systems (WECS) is proposed to minimize torque ripple. The proposed method adjusts the shared reference torque function between the phases based on instantaneous torque, rather than the existing TSF methods formulated with a mathematical expression. Additionally, this paper introduces an innovative speed control scheme for SRG drive using a Fuzzy Super-Twisting Sliding Mode Command (FSTSMC) method. Notably robust against parameter uncertainties and payload disturbances, the proposed scheme ensures finite-time convergence even in the presence of external disturbances, while effectively reducing chattering. To assess the effectiveness of the proposed methods, comprehensive comparisons are made with traditional control techniques, including Proportional–Integral (PI), Integral Sliding Mode Control (ISMC), and Super-Twisting Sliding Mode Control (STSMC). The simulation results, obtained using MATLAB®/SIMULINK® under various speeds and mechanical torque conditions, demonstrate the superior performance and robustness of the proposed approaches. This study presents a thorough experimental analysis of a 250 W four-phase 8/6 SRG. The generator was connected to a DC resistive load, and the analysis focuses on assessing its performance and operational characteristics across different rotational speeds. The primary objective is to validate and confirm the efficacy of the SRG under varying conditions. [ABSTRACT FROM AUTHOR]

This paper describes a simplified one-phase equivalent circuit model of three-phase salient pole synchronous machines and synchronous reluctance machines. The model represents the pole saliency as a susceptance, with a magnitude based on the pole saliency and a phase angle based on twice the load angle. The reluctance torque itself is then modeled equivalent to a conductance. The model is made as an extension to Norton equivalents, where the internal inductance is connected as a shunt. This approach shares similarities to the magnetization shunt branch in circuit models of transformers and induction motors. The model is derived using the rotating d q -frame, using Park transform and two-reaction theory. The model is then rewritten to better fit one-phase equivalent circuit models, with the terminal voltage as the angular reference. The resulting two-pole model can then more easily be combined with basic circuit theory, thereby synthesizing d q -theory and phasor circuit models. [ABSTRACT FROM AUTHOR]

There are usually noise problems when the position sensorless control of a synchronous reluctance motor (SynRM) is carried out by high-frequency (HF) signal injection method. Due to the special structure, the cross-saturation effect of the SynRM is particularly serious, resulting in reduced position observation accuracy. In this paper, a variable-angle random HF voltage injection strategy with cross-saturation effect compensation is proposed for position sensorless SynRM drives. Random number generation based on the chaotic mapping method is used to generate random HF voltage signals with different frequencies for injection; the current power spectral density (PSD) distribution is extended and the HF noise can be reduced. A control strategy based on variable-angle square-wave injection is proposed to suppress the cross-saturation effect. By measuring the position error curves of different loads off-line and polynomial fitting the curves, the position error is achieved by combining with the corresponding signal demodulation algorithm. The proposed method does not require additional hardware resources and can maintain high control accuracy and robustness. Finally, the effectiveness of the proposed sensorless control strategy is verified on a 3 kW SynRM experimental platform. [ABSTRACT FROM AUTHOR]

Synchronous reluctance machines are considered a cost-effective solution for several industrial applications and present potential efficiency benefits compared to induction motors. In industrial applications, power supply oscillations can lead to short-term disturbances that can affect the drive operation; therefore, the control must be robust to guarantee high efficiency and service continuity. The focus of this study was to identify the speed boundaries considering different values of applied DC-link voltage, taking into account the highly nonlinear magnetic behavior of the machine and its cross-coupling characteristics. In addition, a comprehensive carrier-based implementation of a pulse width modulation strategy was proposed to achieve optimal efficiency in both the machine and converter, which is essential in the presence of "weak" grids. The proposed technique was demonstrated to meet the desired reference torque and rated speed, even during DC-link voltage drops (up to 7.4% of the rated voltage). The proposed methodology was experimentally validated on a 90 kW SynRM drive with a broader modulation range and higher efficiency. This work considered several different supply voltage levels to assess the stability and continuity of torque output and further proved the proposed method. [ABSTRACT FROM AUTHOR]

Real-time hardware-in-the-loop-(HIL) simulation integration is now a fundamental component of the power electronics control design cycle. This integration is required to test the efficacy of controller implementations. Even though hardware-in-the-loop-(HIL) tools use FPGA devices with computing power that is rapidly evolving, developers constantly need to balance the ease of deploying models with acceptable accuracy. This study introduces a methodology for implementing a full-bridge inverter and buck converter utilising the associate-discrete-circuit-(ADC) model, which is optimised for real-time simulator applications. Additionally, this work introduces a new approach for choosing ADC parameter values by using the artificial-bee-colony-(ABC) algorithm, the firefly algorithm (FFA), and the genetic algorithm (GA). The implementation of the ADC-based model enables the development of a consistent architecture in simulation, regardless of the states of the switches. The simulation results demonstrate the efficacy of the proposed methodology in selecting optimal parameters for an ADC-switch-based full-bridge inverter and buck converter. These results indicate a reduction in overshoot and settling time observed in both the output voltage and current of the chosen topologies. [ABSTRACT FROM AUTHOR]

In this study, a generalized torque estimation method is proposed for synchronous motors, including surface permanent magnet synchronous motors (SPMSMs), synchronous reluctance motors (SynRMs), and interior permanent magnet synchronous motors (IPMSMs) for building the analytical motor model. The average motor torque is estimated using the Lorentz force by the generated flux density in the air gap to determine the relationships among torque, flux density, and injected current. In the proposed method, the generated flux density is derived step by step by considering the effects of magnetic flux saturation, the stator slot, the rotor barrier, and permanent magnets (PMs) to ensure that the generated average torque complies with the operating condition of the motor. To verify the proposed method, the output torque of finite element analysis (FEA), Maxwell 2D, is compared to the proposed method in a SPMSM. Moreover, a phasor diagram is plotted to determine the mechanism through which torque is generated in SynRMs and IPMSMs. A SynRM and an IPMSM with ferrites PMs are analyzed using the proposed method, FEA, and the experimental results of this study indicate the effectiveness. [ABSTRACT FROM AUTHOR]

The Dual–Vector model predictive control (DV–MPC) method can improve the steady–state control performance of motor drives compared to using the single–vector method in one switching cycle. However, this performance enhancement generally increases the computational burden due to the exponential increase in the number of vector selections, lowering the system's dynamic response. Alternatively, limiting the vector combinations will sacrifice system steady–state performance. To address this issue, this paper proposes an enhanced DV–MPC method that can determine the optimal vector combinations along with their duration time within minimized calculation times. Compared to the existing DV–MPC methods, the proposed enhanced technique can achieve excellent steady–state performance while maintaining a low computational burden. These benefits have been demonstrated in the results from a 2.5k rpm permanent magnet synchronous motor drive. [ABSTRACT FROM AUTHOR]

Switched reluctance motors (SRMs) face challenges in achieving high performances in terms of the power factor, torque per ampere, and torque ripples. Although several parameters impact their performance, magnetic saliency has a significant impact. This paper presents a study on the influence of the saliency ratio on the performance of switched reluctance motors. A detailed design procedure for a mid-drive electric motor for a high-performance electric bike is presented. A systematic methodology is adopted to estimate the power rating for desired vehicle performance while considering the vehicle's mechanical and aerodynamic parameters. Additionally, the paper discusses and analyzes the design of two SRM motor configurations with different rotor poles (6/4 and 6/10) while performing magnetostatic analysis for generated torque validation. A parametric study is performed on the 6/10 SRM design for further improvement in the torque profile while keeping the same fill factor and electrical loading. Furthermore, the transient analysis in Ansys Maxwell 2D for both SRMs confirms the designed performance. The results shows that the SRM with higher rotor poles (6/10) is a better choice. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

For recycling waste batteries, high-gain DC-DC provides a great solution. In this article, the design and optimization of a high-gain converter–synchronous rectification low-inductance current secondary boost converter (SLIC-QBC) is studied. The optimization objective of this article is to propose an automatic design method for passive components and the switching frequency of the converter to improve efficiency and power density. A machine learning-integrated optimization method is proposed to minimize the converter mass and power loss of the converter. In this method, first, a component-based automatic design model is built with embedded SLIC-QBC simulation. Then, a series of design schemes is generated within a large parameter range, and training data for machine learning are collected. Support vector machine (SVM) and artificial neural network (ANN) are used to validate the converter design scheme, where ANN establishes the mapping relationship from design parameters to optimization objectives. After the optimization, an experimental prototype is built for experimental verification. The simulation and experimental results verify the practicability of the proposed method. [ABSTRACT FROM AUTHOR]

This paper presents research on an unconventional electric machine. It is a hybrid excited machine which includes the features of three types of machines: the Permanent Magnet Synchronous Machine, the Synchronous Machine, and the Synchronous Reluctance Machine. Therefore, a broad literature review related to the above-mentioned types of machines was constructed. The well-known Permanent Magnet assisted Synchronous Reluctance Machine joins features of Permanent Magnet Synchronous Machine and Synchronous Reluctance Machine topologies. This paper shows the results of the innovative design of the Hybrid Excited Permanent Magnet assisted Synchronous Reluctance Machine, which additionally has advantages of the Synchronous Machine. In the article the basic methods of electromagnetic flux control and the designs using them are also presented. Finally, the results of simulation studies of the effect of the stator skew on the machine performance are described. [ABSTRACT FROM AUTHOR]

An intelligent servo drive system for a permanent magnet-assisted synchronous reluctance motor (PMASynRM) that can adapt to the control requirements considering the motor's nonlinear and time-varying natures is developed in this study. A recurrent wavelet fuzzy neural network (RWFNN) with intelligent backstepping control is proposed to achieve this. In this study, first, a maximum torque per ampere (MTPA) controlled PMASynRM servo drive is introduced. A lookup table (LUT) is created, which is based on finite element analysis (FEA) results by using ANSYS Maxwell-2D dynamic model to determine the current angle command of the MTPA. Next, a backstepping control (BSC) system is created to accurately follow the desired position in the PMASynRM servo drive system while maintaining robust control characteristics. However, designing an efficient BSC for practical applications becomes challenging due to the lack of prior uncertainty information. To overcome this challenge, this study introduces an RWFNN as an approximation for the BSC, aiming to alleviate the limitations of the traditional BSC approach. An enhanced adaptive compensator is also incorporated into the RWFNN to handle potential approximation errors effectively. In addition, to ensure the stability of the RWFNN, the Lyapunov stability method is employed to develop online learning algorithms for the RWFNN and to guarantee its asymptotic stability. The proposed intelligent backstepping control with recurrent wavelet fuzzy neural network (IBSCRWFNN) demonstrates remarkable effectiveness and robustness in controlling the PMASynRM servo drive, as evidenced by the experimental results. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Currently, applications of the algorithms based on artificial intelligence (AI) principles can be observed in various fields. This can be also noticed in the wide area of electrical drives. Consideration has been limited to neural networks; however, the tasks for the models can be defined as follows: control, state variable estimation, and diagnostics. In the subsequent sections of this paper, electrical machines, as well as power electronic devices, are assumed as the main objects. This paper describes the basics, issues, and possibilities related to the used tools and explains the growing popularity of neural network applications in automatic systems with electrical drives. The paper begins with the overall considerations; following that, the content proceeds with the details, and two specific examples are shown. The first example deals with a neural network-based speed controller tested in a structure with a synchronous reluctance motor. Then, the implementation of recurrent neural networks as state variable estimators is analyzed. The achieved results present a precise estimation of the load speed and the shaft torque signals from a two-mass system. All descriptions in the article are considered in the context of the trends and perspectives in modern algorithm applications for electrical drives. [ABSTRACT FROM AUTHOR]

Operation at low speed and high torque can lead to the generation of strong ripples in the speed, which can deteriorate the system. To reduce the speed oscillations when operating a five-phase asynchronous motor at low speed, in this article, we propose a control method based on Gray Wolf optimization (GWO) algorithms to adjust the parameters of proportional–integral (PI) controllers. Proportional–integral controllers are commonly used in control systems to regulate the speed and current of a motor. The controller parameters, such as the integral gain and proportional gain, can be adjusted to improve the control performance. Specifically, reducing the integral gain can help reduce the oscillations at low speeds. The proportional–integral controller is insensitive to parametric variations; however, when we employ a GWO optimization strategy based on PI controller parameters, and when we choose gains wisely, the system becomes more reliable. The obtained results show that the hybrid control of the five-phase induction motor (IM) offers high performance in the permanent and transient states. In addition, with this proposed strategy controller, disturbances do not affect motor performance. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) or 3D printing has opened up new opportunities for researchers in the field of electrical machines, as it allows for more flexibility in design and faster prototyping, which can lead to more efficient and cost-effective production. An overview of the primary AM techniques utilized for designing electrical machines is presented in this paper. AM enables the creation of complex and intricate designs that are difficult or impossible to achieve using traditional methods. Topology Optimization (TO) can be used to optimize the design of parts for various purposes such as weight, thermal, material usage and structural performance. This paper primarily concentrates on the most recent studies of the AM and TO of the reluctance machines. The integration of AM with TO can enhance the design and fabrication process of magnetic components in electrical machines by overcoming current manufacturing limitations and enabling the exploration of new design possibilities. The technology of AM and TO both have limitations and challenges which are discussed in this paper. Overall, the paper offers a valuable resource for researchers and practitioners working in the field of AM and TO of electrical machines. [ABSTRACT FROM AUTHOR]

Bearingless switched reluctance motor (BSRM) adopts a doubly salient structure without windings on the rotor. BSRMs have the advantages of high rate of fault tolerance and simple structure, high power, super high speed and strong adaptability. They have broad application prospects in aerospace, flywheel energy storage, new energy and biomedical fields. Firstly, the suspension operation mechanism of a conventional double winding BSRM is described in this paper. The coupling between torque and suspension force is analyzed with a finite element method. On this basis, from the perspective of magnetic circuit optimization of the torque system and suspension system, the magnetic circuit design, decoupling mechanism and performance characteristics of self-decoupled BSRMs with different topological structures are described centering on the self-decoupled topology form of the BSRM. Finally, the study and development of BSRMs in the future are prospected based on the research status. [ABSTRACT FROM AUTHOR]

Today, switched reluctance motors (SRMs) represent a promising technology for the long-term sustainability of electrified transportation, mainly due to their simpler structure, lower production cost, and robust configuration compared to other motor technologies. Notwithstanding, high acoustic noise and torque ripple are two performance imperfections that have prevented the widespread implementation of SRMs. This paper presents different structural design techniques to reduce the acoustic noise of an 8/6 SRM, while maintaining the electromagnetic performance of the machine. For each technique, a corresponding multiphysics FEA analysis of the motor's performance is presented. The accuracy of the multiphysics model is confirmed experimentally using acoustic noise measurements obtained from a four-phase 8/6 SRM. Then, several structural techniques have been investigated on the 8/6 SRM represented in two main categories: stator-housing modifications and rotor modifications. The best design strategies are then combined to improve the acoustic noise level of the 8/6 SRM while maintaining its performance. [ABSTRACT FROM AUTHOR]

The modern era of green transportation based on Industry 4.0 is leading the automotive industry to focus on the electrification of all vehicles. This trend is affected by the massive advantages offered by electric vehicles (EV), such as pollution-free, economical and low-maintenance cost operation. The heart of this system is the electric motor powered by lithium-ion batteries; however, due to their many limitations, a hybrid energy storage system (HESS) consisting of batteries and ultracapacitors is currently gaining increased attention. This paper aims to review the distinct motor technologies such as brushless motors, synchronous reluctance and induction motors currently used in EVs. Additionally, through eleven selected criteria, such as regenerative braking efficiency and power density at different load ranges, the motors are classified in terms of their combined ability to operate with a HESS in order to maximize efficiency and sizing. The results show that permanent magnet and induction motors are the best options when all criteria are considered, while synchronous reluctance motor outperforms the induction motor regarding only the main factors affecting the performance of the hybrid storage system. [ABSTRACT FROM AUTHOR]

Consuming energy sources and greenhouse gas emission are one of the most prominent problems of the latest century. Most of the energy consumed globally and carbon dioxide emissions originate from electric motors used in the industry. Therefore, researchers have recently focused on the production of highly efficient, eco-friendly, and low-priced machines: Synchronous Reluctance Machines. In this study, the design and comprehensive Finite Element Analysis of a TLA-SynRM including the effects of the number of conductors per slot and wire diameter directly affecting stator slot fill factor and crucial for obtaining more realistic results from experiments has been initially carried out. Moreover, power factor, saliency ratio, and efficiency of the novel SynRM are enhanced by utilizing a fine-tuning process based on d- and q-axes flux paths. Additionally, the layer structure of the initial design is changed to a double-layer structure to improve the performance of the machine in the fine-tuning process. In the final step of this study, the machine has been manufactured, and experiments have been accomplished. This study has concluded that the novel SynRM have low torque ripple, high power factor, saliency ratio, and efficiency, whose value is within the range of IE5 efficiency class. [ABSTRACT FROM AUTHOR]

This paper presents a new three-layer, five-phase winding configuration theory of unconventional slot-pole combinations by each layer of winding for a phase vector correction, three layers of winding superimposed together to achieve the results of three-phase symmetry. Since the single-layer unconventional winding has to have an empty slot to meet its symmetry, based on the characteristics of single-layer winding, the unconventional winding design is carried out. Based on the simulation comparison between the single-layer unconventional winding and double-layer unconventional winding, a three-layer, nine-phase unconventional winding is proposed, which is based on the theory of single-layer unconventional winding, and three layers are staggered and stacked to realize nine-phase winding, which not only increases the utilization rate of the winding slot but also improves the fault tolerance performance. In addition, a 105-slot, 20-pole, three-layer, five-phase motor is proposed for a winding configuration and performance analysis to achieve both low torque pulsation and high fault tolerance. [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]

Sensorless control based on high-frequency square-wave voltage injection (HFSVI) is one of the most common sensorless control methods for synchronous reluctance motors (SynRMs). However, the injection frequency for SynRMs cannot be too high due to various factors. As the injection frequency decreases, the dead-time harmonic current will greatly affect the separation of high frequency signals. This paper analyzes the effect of dead-time harmonic current on the HFSVI-based sensorless control performance of SynRMs and proposes a source of position estimation error. Then, a dead-time compensation method suitable for filter-free HFSVI is proposed. It can estimate current vector spatial orientation without any low-pass filters (LPFs) and effectively compensate the impact of dead-time setting. The correctness of the theoretical analysis and the feasibility of the proposed methods in this paper are verified by experiments. [ABSTRACT FROM AUTHOR]

To identify the parameters of variable flux reluctance machines (VFRMs), the input voltage value is usually obtained from the reference voltage indirectly. However, the reference and actual voltages may be different due to the nonlinearity of the open winding inverter when using zero-sequence current, leading to the inaccuracy of parameter identification. To solve this problem, this paper proposes an equivalent nonlinearity voltage error model of the open winding inverter to compensate for the input voltage of VFRM during the online parameter identification. Since in the proposed method the phase current direction is not required, the calculation time can be reduced. Moreover, in the developed parameter identification model of VFRM the derived equivalent nonlinear voltage error is used to correct the input of the identification model so as to improve the accuracy of parameters. Finally, the experimental results on the prototype VFRM are presented for verification. [ABSTRACT FROM AUTHOR]

The switched reluctance motor (SRM) benefits from its magnet-free nature, robust construction, low cost, flexible controls, and the ability to operate in harsh environments such as high temperatures and high pressure. It has received increasing attention for all-electric or multi-electric aircraft systems and electric vehicles (EVs) as compared with permanent magnet synchronous motors (PMSM) and other AC motors in some required high reliability and fault tolerance applications. However, the SRM is prone to considerable wind resistance due to the convex pole structure of the rotor during high-speed rotation, high torque ripple, and also vibration noise. Thus, it is currently a trending topic to develop special SRMs, tailored with high reliability and fault tolerance. Recent research demonstrates several promising feasible solutions to reduce torque ripples and enhance torque density and power factors, including changing topology of SRM, using advanced control methods, as well as different winding configurations. Among these options, the segmented switched reluctance motor (SSRM), as a deformation of the conventional topology, is shown to be capable of effectively optimizing the torque performance. Motivated by this advance, this paper aims to present a comprehensive literature review on the SSRM, first illustrating the development of the topology of the SRM, then providing a description as well as a classification according to the topology of the SSRM. In particular, we focus on the evolution of various kinds of segmental topology and improvement measures. Then, we discuss the performance, advantages, and disadvantages of various types of structures in terms of their electromagnetic aspects and their applications. Eventually, several promising future trends and application prospects of the SSRM are prospected, with the aim of shedding light on further research. In sum, the key contribution of this paper is to provide a valuable basis for detailed analyses of the structure and electromagnetic design of the SSRM that are expected to benefit future research. [ABSTRACT FROM AUTHOR]

With the rapid development of power electronic techniques and the increasing cost of permanent magnets (PMs) materials, switched reluctance motors (SRMs) have recently gained more attention. However, traditional SRMs have a relatively low torque density. For the sake of increasing the motor torque density, this paper proposes a novel segmental rotor type SRM. The proposed motor adopts hybrid stator poles and concentrated windings in the stator side and a segmental rotor structure in the rotor side, which is completely different from the structures of the traditional SRM. The special structure of the motor shortens the magnetic flux paths of the motor, separates the parts of the magnetic flux paths from one another, and eradicates the magnetic flux reversal in the motor stator in order to improve the electric utilization and output torque density of the motor. Meanwhile, the requirement of the magneto-motive force and the core loss of the motor is also decreased, thereby improving the efficiency of the motor. For the purpose of proving the proposed structure, the characteristics of the motor are analyzed using the finite element method and are compared to those of the traditional 12/8 SRM, which is designed for the same application. Moreover, the prototypes of the traditional 12/8 and proposed SRMs are manufactured, and experiments based on the prototypes are performed. Finally, the effectiveness of the structure of the proposed motor is further proven by the experimental results. [ABSTRACT FROM AUTHOR]

The rotor permanent magnet flux-switching (RPM-FS) machine is a promising candidate for electric vehicle (EV) and hybrid electric vehicle (HEV) applications. In this paper, we propose the magnetic flux barrier design to improve the torque capability of the RPM-FS machine. The response surface optimization method was used to design and optimize the topology of flux barriers. The 2D finite element analysis shows that the proposed RPM-FS machine has a higher electromotive force than the conventional structure, with only a slight increase in cogging torque. Notably, an insertion of flux barriers could yield a reduction of magnetic flux leakage, an improvement of magnetic saturation capability, and an enhancement of working harmonics of the air-gap flux density. As a result, a significant improvement in torque capability, eddy current losses, and efficiency was obtained. Hence, the RPM-FS machine proposed in this work is capable of being used in EV and HEV applications. [ABSTRACT FROM AUTHOR]

In electric vehicle (EV) applications, hybrid excitation of switched reluctance motors (HESRMs) are gaining popularity due to their advantages over other EV motors. The benefits include control flexibility, simple construction, high torque/power density, and the ability to operate over a broad speed range. However, modern HESRMs are constructed by increasing the air gap flux density with permanent magnets (PMs) in the excitation system in order to generate more electromagnetic torque. This study aims to investigate a new topology for increasing the torque capabilities of HESRM without the use of permanent magnets (PMs) or other rare-earth components. This paper provides a comprehensive evaluation of the static and dynamic characteristics, software analysis using the Ansys 2D finite element method (FEM), and an experimental demonstration of the real-time motor with an advanced control strategy in MATLAB/Simulink. Our simulation and experimental results for a machine with 12/8 poles and a machine rating of 1.2 kW indicate that the HESRM designed without PMs has greater torque capability and efficiency than the conventional SRM. The proposed HESRM without PMs has a high torque/power density and a higher torque per ampere across the entire speed range, making it suitable for EV applications. [ABSTRACT FROM AUTHOR]

Slotting effect in electric machines reduces flux per pole that effect magnetic flux density distribution in the air gap which induces harmonics in magnetic flux density causing flux pulsation, that in turn generates dominant torque pulsation in the form of cogging torque and torque ripples. To overcome the abovesaid demerits, a novel outer rotor field-excited flux-switching machine (OR-FSFSM) with a combined semi-closed and open slots stator is proposed in this study. The developed OR-FEFSM offers a high-power factor, due to the utilization of the semi-closed slot for armature coils. The open slot stator structure was chosen for the field excitation coil, which effectively suppresses leakage reluctance that causes flux pulsation. Thus, the influence of torque ripples is reduced, and the average torque is improved. In order to investigate the effectiveness of the proposed OR-FEFSM, a detailed study of stator slot and rotor pole combinations are performed. Based on simplified mathematical formulation, 12S/7P (stator slot/rotor poles), 12S/11P, 12S/13P, and 12S/17P are the most feasible combinations. Finite Element Analysis (FEA) based on comprehensive electromagnetic performance is performed on each combination, and found that 12S/13P offers the highest average torque of 4.62 Nm, whereas 3.72 Nm, 2.72Nm, and 1.68 Nm average torque is offered by 12S/17P, 12S/7P, and 12S/11P, respectively. Based on the initial analysis, 12S/13P was considered for further analysis and optimized using JMAG built-in Genetic Algorithm (GA). Moreover, thermal analysis was performed, and the proposed design was compared with the conventional design. [ABSTRACT FROM AUTHOR]

Dual three–phase synchronous reluctance motors (DTP–SynRM) have the advantages of simple structure, high power density, fast dynamic response, and small torque ripple, and have broad application prospects in flywheel batteries. However, the synchronous reluctance motor has no permanent magnet, and the inductance value will change with the current change in actual operation. Direct torque control (DTC) is more suitable for the control strategy of dual three–phase synchronous reluctance motors because of its low dependence on motor parameters. However, traditional direct torque control uses a large vector control motor within one control period, which can not suppress the inherent 5th and 7th current harmonics in the motor. A new harmonic suppression method is proposed in this paper: that is, using a low harmonic vector to replace a large vector in traditional direct torque control, which can be synthesized by adjusting the action time and order of three adjacent large vectors within one control period. Through this improvement, torque control can have a harmonic suppression effect. The three vector synthesis method can make full use of the existing space voltage vector, and to adapt to different working conditions, two synthesis methods of switching frequency reduction and constant torque response are proposed. An improved direct torque control strategy is obtained by optimizing the design of the switch table using a new vector synthesis method. Finally, the suppression effect of traditional DTC and improved DTC on current harmonics is compared and analyzed. The results show that the direct torque control with low harmonic vector can suppress the harmonic current in x–y subspace, and the current harmonic content is greatly reduced. [ABSTRACT FROM AUTHOR]

In this paper, a thorough framework for multiobjective design optimization of switched reluctance motor (SRM) is proposed. Selection of stator and rotor pole embrace coefficients is an essential step in the SRM design process since it influences torque output and torque ripple in SRM. The problem of determining optimal pole embrace is formulated as a multi-objective optimization problem with the objective of optimizing average torque, efficiency and torque ripple, and response surface models were obtained based on the genetic aggregation method. The results obtained by genetic aggregation response surface (GARS) and the non-dominated genetic algorithm (NSGA-II) were validated with the finite element method (FEM) model of the initial SRM. The optimized model displayed better efficiency profile over a wide speed range. The initial and optimized models recorded maximum efficiencies of 85% and 94.05%, respectively, at 2000 rpm. The efficiency values of 93.97–94.05% were achieved for the three pareto optimal candidates. The findings indicate the viability of the suggested strategy and support the use of GARS and NSGA-II as useful methods for addressing SRM key challenges. [ABSTRACT FROM AUTHOR]

This paper studies the speed control strategy of a switched reluctance motor based on angle-position control (APC). The switched reluctance motor has three control parameters: turn-on angle, turn-off angle and voltage PWM duty cycle. This paper studies the function of the three parameters and designs the control algorithms of the parameters, respectively, which can reduce the coupling degree, simplify the control process, and realize the optimal control of the switched reluctance motor. By studying the nonlinear characteristics of the switched reluctance motor, the optimal current waveform in the effective working range of the inductor is obtained, and then a control strategy of the turn-on angle is designed to realize the ideal winding current waveform. According to the torque characteristics of the motor, taking the coincidence of the freewheeling zero point and the position angle at the end of the maximum inductance interval as the control target, a control strategy for the turn-off angle that makes full use of the effective inductance working interval is proposed, which improves the efficiency of the system. For the nonlinear and time-variant switched reluctance motor running process, a data-driven model-free adaptive control algorithm is introduced, and a switched reluctance motor speed control algorithm based on voltage PWM duty cycle is designed. The main contribution of this paper is to propose a control strategy that is generally applicable to switched reluctance motors, which does not depend on the precise mathematical model of the motor. The control algorithms are designed separately for the three control parameters according to the characteristics of the motor, which reduces the degree of coupling among them. A switched reluctance motor drive system based on angle-position control is designed. This strategy is especially suitable for driving the load with sudden large torque pulsation. [ABSTRACT FROM AUTHOR]

The energy-efficiency indicators of a direct-on-line synchronous reluctance motor with a power rating of 4 kW are compared with a motor with rare-earth permanent magnets on the rotor, as well as with an IE3 energy efficiency class induction motor. The permanent magnet motor provides slightly greater energy savings; however, unlike the synchronous reluctance motor, it has a long payback period due to its high cost associated with the use of expensive rare earth magnets. In [[10]], for electric vehicles, a novel design of an SRM with twelve stator teeth and eight rotor teeth without permanent magnets is proposed. [Extracted from the article]

With the challenges of global climate anomalies and energy crises, vehicle electrification has an increasing trend as an exciting solution for reducing greenhouse gas emissions and fossil fuel-based energy consumption. That is to say, the fault diagnosis part plays a crucial role in active FTC, and inaccurate or wrong fault diagnosis results directly impact the control strategy's performance and even lead to the system's instability. Fault Diagnosis Methods for Electric Vehicle Powertrains Fault diagnosis includes fault detection, fault isolation, and fault identification, and provides diagnostic results based on specific faults in the system to facilitate a fault assessment or implement fault-tolerant control [[10]]. However, the increasing complexity of electric vehicle powertrain architectures has made fault diagnosis techniques challenging. [Extracted from the article]

This paper proposes a modelling technique for Synchronous Reluctance Motors (SynRMs) based on a generalized Magnetic Equivalent Circuit (MEC). The proposed model can be used in the design of any number of stator teeth, rotor poles, and rotor barrier combinations. This technique allows elimination of infeasible machine solutions during the initial machine sizing stage, resulting in a lower cohort of feasible machine solutions that can be further optimized using finite element methods. Therefore, saturation effects, however, are not considered in the modelling. This paper focuses on modelling a generic structure of the SynRM in modular form and is then extended to a full SynRM model. The proposed model can be iteratively used for any symmetrical rotor pole and stator teeth combination. The developed technique is applied to model a 4-pole, 36 slot SynRM as an example, and the implemented model is executed following a time stepping strategy. The motor characteristics such as flux distribution and torque of the developed SynRM model is compared with finite elemental analysis (FEA) simulation results. [ABSTRACT FROM AUTHOR]

Deflection switched reluctance motors (DSRM) are prone to chattering at low speeds, which always affects the output efficiency of the DSRM and the mechanical loss of the motor. Combining the characteristics of a traditional reluctance motor with the strong nonlinear and high coupling of the DSRM, a control system for a DSRM based on a flexible neural network (FNN) is proposed in this paper. Based on the better robustness and fault tolerance of fuzzy PI control, the given speed signal is adjusted and converted into a torque control signal. As a result, the FNN control module possesses the strong self-learning ability and adaptive adjustment ability necessary to obtain the control voltage signal. Through simulations and experiments, it was verified that the control system can run stably on DSRM and shows good dynamic performance and anti-interference ability. [ABSTRACT FROM AUTHOR]

We propose a method to predict performance variables according to the rotor slot shape of a three-phase squirrel cage induction motor using a convolution neural network (CNN) algorithm suitable for utilizing image data. The set of performance variables was labeled according to the images of each training dataset, and this set was generated from the efficiency, power factor, starting torque, and average torque. To verify the accuracy of the trained deep learning model, the analysis and prediction results of the CNN model were compared and verified with nine untrained double cage slot shapes and shapes optimized based on the root mean square error (RMSE). Although a large number of training data are required for high accuracy in the existing image processing deep learning model, the proposed deep learning method can predict the performance variables for various shapes with the same level of accuracy as the finite element analysis results using a small number of training data. Therefore, it is expected to be applied in various engineering fields. [ABSTRACT FROM AUTHOR]

Grid-powered pumping plants are widespread electromechanical systems commonly set in motion by electrical machines. The productivity of these electromechanical systems varies substantially according to the shift of the location of the working point on the H-Q plane, which is determined with the help of mutual positions of the characteristics of the pump unit itself and the hydraulic parameters of the pipeline. The topic of the proposed article is mainly focused on the investigation of pumping plant productivity equipped with two various types of electrical machines known as induction and synchronous reluctance motors. A simulation method of efficiency prediction of a centrifugal pumping plant for flow regulation is proposed. The described Simulink/Matlab simulation approach is quite valuable for validating efficiency in the case of pumping plants supplied with various types of electrical machines. The data relating to the electrical machines' efficiency estimation were obtained during a series of experimental tests with the real experimental setup. Thus, the calculation results of the model are accurate and based on confirmed experimental measurements. [ABSTRACT FROM AUTHOR]

Line start permanent magnet assisted synchronous reluctance motor (LSPMaSynRM) is an important high-efficiency and high-quality motor. Its parameter matching and operating characteristics are complex, with an increase in salient ratio resulting in a valley in the power factor curve. In this study, the formation principle of power factor curve valley was first deduced by the mathematical model of LSPMaSynRM. Then, the parameter matching principle of power factor curve valley was analyzed in detail. On this basis, the characteristics of load rate corresponding to the critical state of the power factor curve valley were obtained, and its influence on whole load efficiency was analyzed. The design principles for optimal efficiency in wide high-efficiency region and specific load point were obtained. Finally, a 5.5 kW LSPMaSynRM was designed and manufactured to verify the validity of the principle. [ABSTRACT FROM AUTHOR]

Synchronous reluctance (SynRel) machines are considered one of the promising and cost-effective solutions to many industrial and mobility applications. Nonetheless, achieving an optimal design is challenging due to the complex correlation between geometry and magnetic characteristics. In order to expand the limits formed by template-based geometries, this work approaches the problem by using topology optimization (TO) through the density method (DM). Optimization settings and their effects on results, both in terms of performance and computation time, are studied extensively by performing optimizations on the rotor of a benchmark SynRel machine. In addition, DM-based TO is applied to an existing rotor geometry to assess its use and performance as a design refinement tool. The findings are presented, highlighting several insights into how to apply TO to SynRel machine design and its limitations, boundaries for performance improvements and related computational cost. [ABSTRACT FROM AUTHOR]

This paper presents the results of simulation tests of a unique hybrid-excited permanent magnet machine operating in in different working regimes. The common feature of analyzed machine is a presence of magnetic barriers in the rotor structure. Structurally, this machine combines the advantages of the PMa-SynRM machine (Permanent Magnet-assisted Synchronous Machine) and a wound synchronous machine. The paper presents, among other results, the voltage and torque characteristics as a function of the current in the stator and the additional DC control coil. Selected results of experimental studies are also shown. [ABSTRACT FROM AUTHOR]

Featured in low-speed and high-torque operation, outer-rotor switched reluctance motors (OSRMs) have the potential to be widely deployed in low-speed commuter and logistics vehicle applications. In this paper, a five-phase OSRM and the control method featuring torque ripple reduction has been proposed, which can be applied as the wheel hub motor in the electric vehicles. The simulation was carried out to analyze the OSRM operation. The electromagnetic characteristics of single-phase and two-phase hybrid excitation mode, as well as step current excitation mode, were compared and analyzed. To solve the problem of the large torque ripple of OSRMs under traditional excitation modes, the torque ripple suppression method based on step current excitation was also studied. The experiment design, including motor start-up control, speed control, and torque ripple reduction, are presented to verify the system torque ripple mitigation method. [ABSTRACT FROM AUTHOR]

In this paper, an analysis of noise and vibration of a synchronous reluctance machine for EV applications is performed. The analyzed machine was designed for electric vehicle application. The noise and vibration of a synchronous reluctance machine were first estimated during simulations; next, the obtained results were validated during laboratory tests. The analyzed model of the machine was simplified and included only stator core as it was assumed to be the main source of the machine vibration and generated noise. To simulate the noise and vibration of the machine, multiphysics modeling of the machine was performed. Laboratory tests proved the correctness of performed simulations. The obtained results allowed us to investigate the influence of the machine's operating point on the generated noise and vibration. The frequency of the magnetic radial forces were proven to be the dominant factor in noise generation. The influence of the load and current angle on the machine's noise and vibration was proven to be negligible. It was also proven that considering only the stator structure in numerical analysis of the noise and vibration of the machine leads to valuable results. [ABSTRACT FROM AUTHOR]

Recently, non-rare-earth motors are attracting more and more attention due to the booming of the electric vehicle (EV) market and, more importantly, the increasing price of the rare-earth magnet material. This paper focuses on the performance comparison among a commercial interior permanent magnet (IPM) motor and two non-rare-earth motors, including a synchronous reluctance motor (SynRM) and a permanent-magnet-assisted synchronous reluctance motor (PMaSynRM). The design procedure to develop a high-torque-density, low-torque-ripple and high-efficiency SynRM is presented. Combined with a developed automatic modeling and simulation procedure, the finite element analysis (FEA)-based differential evolution (DE) algorithm is introduced for the SynRM rotor optimization. In order to fully inspire the potential of the SynRM, a novel method to optimize the motor split ratio is proposed under the constraint of the copper loss. In addition, different slot–pole combinations are investigated to maximize the motor torque, and the rotor structure is also dealt with towards the centrifugal stress at the maximum operating speed. Finally, the motor performance comparison is carried out, and the results show that although the SynRM achieves almost 61% cost savings, its poor torque capability, power factor and flux weakening (FW) capability are non-negligible defects. On the contrary, the PMaSynRM exhibits excellent features for the EV applications in terms of cost, torque density, efficiency and FW capability. This paper presents a novel split ratio optimization method for the optimal SynRM/PMaSynRM design and demonstrates the characteristics of the IPM motors, SynRMs and PMaSynRMs for EV applications. [ABSTRACT FROM AUTHOR]

The accurate magnetic model is mandatory for high-performance control of high anisotropy synchronous machines. This paper presents a time-efficient and accurate magnetic model identification based on triangle current injection while the machine under the test is driven at a constant speed by a prime mover. The current injection pattern allows scanning the whole range of current, reducing the identification time compared to the standard constant-speed method (CSM) with the same level of accuracy. The ohmic voltage drop and inverter nonlinearities are compensated by using the average voltage of motor and generator modes. The synchronous reluctance machine is used as a case study for validation through the comparison between the experimental results obtained by the proposed method and the CSM against finite element simulation. Moreover, the temperature variation of the machine winding is measured showing no considerable changes during the identification test. [ABSTRACT FROM AUTHOR]

This paper discusses the tracking coordination of a linear switched reluctance machine (LSRM) network based on a global feedback control strategy with a full-state observation framework. The observer is allocated on the follower instead of the leader to form a leader--follower--observer network, by utilizing the leader as the global feedback tracking controller and the observer as the observation of the full states. The internal model compensator (IMC) is applied to the leader for the improvement of the network performance. The full-state information of the LSRM network is reconfigured by the output of the LSRM where the observer is located to provide necessary feedback information to the leader. Then, the controllability and observability of the leader--follower--observer network with the IMC are inspected, serving as a basis for the design of the global controller with the IMC and full-state observer. Experimentation verifies the effectiveness of the proposed network control scheme and the results demonstrate that both the absolute and the relative accuracy can be simultaneously improved, compared to the LSRM network with only the consensus algorithm and no global feedback mechanism. [ABSTRACT FROM AUTHOR]