Synchronous Reluctance Motor Research Articles

Finite-time robust speed control of synchronous reluctance motor using disturbance rejection sliding mode control with advanced reaching law.

In recent years, there has been a significant focus on synchronous reluctance motors (SynRM) owing to their impressive efficiency and absence of magnetic material. Although the SynRM shows great potential for use in electric vehicles, its widespread adoption is limited by unmodeled dynamics and external disturbances. Moreover, the uncertainty factor significantly restricts SynRM's peak efficiency and superior control performance, leading to an unjustifiable current loop reference command. To address these issues, this work presents various new research contributions which focus on the robust control of SynRM to optimize performance through the novel reaching law-based sliding mode control. Initially, a novel advanced sliding mode control reaching law (ASMCRL) with adaptive gain is proposed, to enhance the acceleration of the system state reaching the sliding surface. After that, an extended state observer (ESO) is designed to estimate and compensate for the overall disturbances of the system. Finally, the ASMCRL and ESO are integrated to design two nonlinear controllers namely, the disturbance-rejection sliding mode controller (DRSMC) and the disturbance-rejection sliding mode speed regulator (DRSMSR) for SynRM. The proposed DRSMSR eliminates the steady-state error and eradicates inherent chattering in DRSMC. Moreover, this yields a system trajectory that converges to a predetermined proximity of the sliding surface, irrespective of any lumped disturbances. The steady-state error of DRSMSR is less as compared to DRSMC. Furthermore, the speed response of this technique is 22.62% faster as compared to the state-of-the-art finite-time adaptive terminal sliding mode control. Additionally, the asymptotic stability of the proposed system is validated using Lyapunov's theorem. Thus the experimental results demonstrate the effectiveness and robustness of the proposed approach.

Performance Validation of PM Assisted SynRM and PMSM with Optimized Design for EV Application

This paper presents the comparison of Permanent Magnet-Assisted Synchronous Reluctance Motor (PMASynRM) and Permanent Magnet Synchronous Motor (PMSM) for the same design parameters and the evaluation of various performance parameters based on the Finite Element (FE) Method. FE Analysis is conducted after selecting the optimized design for PMASynRM and PMSM using an FE tool, with loading conditions to determine various performance parameters. This is achieved by maintaining the same motor dimensions and stator parameters while altering the rotor geometry for both motors. The final simulation results are discussed, and other performance parameters are recorded for comparison purposes. A PMASynRM is introduced, in which the problems of Synchronous Reluctance Motor (SynRM) can be eliminated with a permanent magnet in the rotor flux barrier. Due to higher flux barriers in PMASynRM, the reluctance torque is higher than in PMSM. If the magnet is placed very near to the air gap in PMSM, higher magnet torque is achieved, but due to the high reluctance torque in PMASynRM, the electromagnetic torque of PMASynRM is higher compared to PMSM. The research proves that the proposed design of PMASynRM is the best choice for Electric Vehicle (EV) applications. For PMASynRM, the shape of the flux barrier is not possible to change due to the design limitation of the FE software tool. Further analysis can be conducted by changing the shapes of the flux barriers to propose the most effective barriers. Basic theory and FE analysis of conventional PMSM and SynRM are reported in the literature. An optimal design is proposed through comparative analysis for EV applications to find out the best candidate for an EV motor.

Design and Analysis of Line-Start Synchronous Reluctance Motor Considering the Maximum Inertia and Power Factor

Design and Analysis of Line-Start Synchronous Reluctance Motor Considering the Maximum Inertia and Power Factor

Topology Optimization of Synchronous Reluctance Motors Considering the Optimal Current Reference in the Field-Weakening and Maximum-Torque-Per-Voltage Regions

The torque performance of the synchronous reluctance motors (SynRMs) is primarily determined by the geometric design and current control. The motor structure needs to be designed to yield the maximum output torque under the given current and voltage limitations. The current reference supplied to the stator coils also needs to be determined to maximize the output torque while suppressing the back electromotive force (EMF) to protect a power supply system. However, in the field of design optimization, it has been challenging to simultaneously consider the geometric design and current control due to their complicated relationships. To solve the aforementioned issue, this study proposes a new topology optimization that can cover the maximum-torque-per-ampere (MTPA), field weakening (FW), and maximum-torque-per-voltage (MTPV) controls under both the current and voltage limitations, thereby maximizing the output torque in an entire rotational speed range. To effectively investigate the coupling effects between the geometric design and current reference, this study proposes the design parameterization for the FW and MTPV operation by performing the electromagnetic finite element (FE) analysis and then expresses the optimal current reference in terms of design variables. At every iteration, the structural FE analysis is also performed under the design-dependent loads to obtain a structurally meaningful design. By doing so, both the optimal design and the corresponding optimal current reference can be simultaneously determined. The optimized SynRM is manufactured and experimentally validated to demonstrate the effectiveness of the proposed optimization framework.

Torque Ripple Suppression of Synchronous Reluctance Motors for Electric Vehicles Based on Rotor Improvement Design

Torque Ripple Suppression of Synchronous Reluctance Motors for Electric Vehicles Based on Rotor Improvement Design

Adaptive Gain Tuning Rule for Nonlinear Sliding-Mode Speed Control of Encoderless Three-Phase Permanent Magnet Assisted Synchronous Motor

In this paper, an adaptive gain tuning rule is designed for the nonlinear sliding mode speed control (NSMSC) in order to enhance the dynamic performance and the robustness of the permanent magnet assisted synchronous reluctance motor (PMa-SynRM) with considering the parameter uncertainties. A nonlinear sliding surface whose parameters are altering with time is designed at first. The proposed NSMSC can minimize the settling time without any overshoot via utilizing a low damping ratio at starting along with a high damping ratio as the output approaches the target set-point. In addition, it eliminates the problem of the singularity with the upper bound of an uncertain term that is hard to be measured practically as well as ensures a rapid convergence in finite time, through employing a simple adaptation law. Moreover, for enhancing the system efficiency throughout the constant torque region, the control system utilizes the maximum torque per ampere technique. The nonlinear sliding surface stability is assured via employing Lyapunov stability theory. Furthermore, a simple sliding mode estimator is employed for estimating the system uncertainties. The stability analysis and the experimental results indicate the effectiveness along with feasibility of the proposed speed estimation and the NSMSC approach for a 1.1-kW PMa-SynRM under different speed references, electrical and mechanical parameters disparities, and load disturbance conditions.

Comprehensive Overview of Modern Controllers for Synchronous Reluctance Motor

Synchronous reluctance motor drives (SynRMs) are the best promising machines utilized in modern industries and electric vehicles, according to the current study. Research on new SynRMs drive systems has increased as a result. This review article disseminates the most recent developments in these technologies’ design, modeling, and controlling. First, a simple comparison between the main motor technologies and SynRMs is made. To aid researchers in selecting the appropriate motor controller for their motor drive systems, the most common motor control approaches are examined and classed.

Torque ripples reduction of electric vehicle synchronous reluctance motor drive using the strong action controller

Smart, Micro and Nano-grids are the future of electric power systems. In parallel with this future, electric vehicles (EVs) take a great deal of attention, as they are one of the important elements in these systems. Also, with the passage of time, the development continues in the technology of manufacturing EVs. Since the electric motor is the main component in these vehicles, research and development is continuing to find the most suitable motors that can work in such vehicles. The synchronous reluctance motor (SynRM) is the newest motor used in this industry. SynRMs faces different challenges, one of which is the torque ripples. Different trials were used to reduce or eliminate or minimize these ripples. Most of previous work focuses on the SynRM design parameters to reduce torque ripples. In this paper, the control methodology and the strong action controller (SAC) are used as a tool to reduce these ripples. The simulation results showed the effectiveness of the application of the proposed SAC in ripples factor reduction. This reduction represents a new contribution over the already existed techniques.

Improved Current Regulators for Sensorless Synchronous Reluctance Motor

Improved Current Regulators for Sensorless Synchronous Reluctance Motor

Speed Sensorless Control Method of Synchronous Reluctance Motor Based on Resonant Kalman Filter

When estimating the active back electromotive force (AEMF) of synchronous reluctance motor (SynRM) at medium and high speed, the traditional Kalman Filter (KF) will produce large phase delay due to the low-pass filter characteristics. A novel speed sensorless control scheme of SynRM based on resonant Kalman filter (RKF) is proposed in this paper. Firstly, the AEMF observer based on KF is designed and the bandwidth performance is analyzed. To solve the phase delay problem caused by KF, a generalized integral resonance perturbation estimator (GIRPE) is introduced to the framework of KF and the proposed RKF is formed. The estimation error of AEMF is compensated through GIRPE in the current error feedback loop of KF observer. In this way, the high-precision position estimation at high speed range is obtained. Finally, an improved dynamic position compensator (IDPC) is proposed to enhance the position estimation performance under dynamic case. The effectiveness of proposed scheme is validated at a 1.5kW SynRM drive, and the computational burden of the proposed method is assessed quantitatively.

Initial Rotor Position Estimation of SynRM Based on Pulsating Voltage Injection Combined With Finite Position Set Algorithm

Initial rotor position estimation is the basis of stable starting without reverse rotation; also initial position estimation directly affects the maximum starting torque. DC pulse voltage injection is one of the common methods for estimating the initial rotor position, which has low implementation complexity. However, the conventional DC voltage pulse injection methods, which works through injecting three DC voltage pulses, has low accuracy and slow response in estimating initial position. A rotor initial position estimation method based on pulsating voltage injection combined with an iteration algorithm is proposed in this paper. This method works by injecting only one DC voltage pulse to the motor and measuring the peak values of currents and fluxes of the motor; afterwards these values should be applied to an iterative algorithm. The iteration algorithm in the proposed method leads to increment of the accuracy of initial position estimation, and reduction of the number of injected dc pulses in comparison with the conventional methods. The performance of the proposed method is verified experimentally on a synchronous reluctance motor (SynRM). Also, a comparison between the two conventional methods and the proposed method is provided by this SynRM drive experimental setup.

Dual Motor Model Prediction Control with Senseless Control and Parameter Identification Function

A new control strategy is proposed to address the issues of poor stability and inability to achieve torque synchronization in dual-drive systems. Firstly, the structure of the permanent magnet assisted synchronous reluctance motor is described, and the principles of model prediction dual-torque control, Beetle Antennae Search algorithm, and Kalman filter algorithm are analyzed. The permanent magnet assisted synchronous reluctance motor is used as the main motor, and a senseless control module and parameter identification module for the motor is established on this basis, creating a model prediction dual-torque control model for the dual motor with the above functions. Finally, through simulation, the rationality and accuracy of the model are verified. The results show that the model can balance the torque of the two motors and achieve accurate senseless control and parameter identification.

A Super-twisting SMC Design for Bidirectional DC–DC Converters in Electric Vehicle Applications

Many industrial and electrical systems, such as electric vehicles, employ DC/DC converters. Since DC/DC converters are nonlinear and time-varying systems, it is inappropriate to regulate them using linear control techniques. In this paper, a super-twisting sliding mode control (STSMC) is applied for bidirectional DC-DC converter in electric vehicle applications. The traction chain of the electric vehicle consists of a battery-supercapacitor energy storage system (ESS) linked in parallel to the DC bus through two bidirectional DC–DC converters and a synchronous reluctance motor drive (SynRM). The benefit of sharing power in an HPS, which is primarily made up of a supercapacitor and battery, is the ability to use the strengths of both sources, with the former having high specific energy and the latter having high specific power. The on-board energy storage system's performance is enhanced by this hybridization in terms of cost, mass, and charging time. In addition to the proposed control, the hybrid power system (HPS) needs a strategy for routing energy between the two sources and the motor. This strategy is based on frequency decoupling (DFS), which protects the battery from peak current during the acceleration and deceleration phases. The objective of using the control law based on super-twisting sliding mode control (STSMC) is to follow the reference trajectories in finite time with high precision, very good robustness, and a reduction in chattering. Using the MATLAB/Simulink software, a thorough simulation of an electric vehicle was performed in order to confirm the effectiveness of the suggested control approach and assess the effectiveness of the source's energy management strategy. This control method ensures a reduction in the bus voltage stress (Δv=5V) and improves the quality of the power. The overshoot voltage for a load power of 21 kw is reduced to 15V (3.2%) compared to the linear control techniques, improving the system's robustness and reliability..

Design and Double-Stage Optimization of Synchronous Reluctance Motor for Electric Vehicles

In this study, a high-power synchronous reluctance motor (SynRM) was designed for the traction motor of electric vehicle (EV) and its double-stage optimization was performed. Genetic algorithm and sensitivity analysis methods were used to obtain the best design parameters. Double-stage optimization was carried out to minimize the torque ripple and obtain the targeted torque, speed, and power values of the SynRM. In the first stage, the genetic algorithm method was used to improve the design parameters of the stator and rotor. With the improved design parameters, it was observed that the torque ripple decreased. In the second stage, the sensitivity analysis method was used. In this method, the effect of changing the skew angle of the stator on the torque ripple was investigated. The performance of the designed motor was examined in the optimization process. It was observed that the targeted torque, power, speed, efficiency, and torque ripple minimization values are successfully achieved with the best stator and rotor parameters. The results showed that SynRM produces high torque and high power with high efficiency and low torque ripple over wide speed range. It is quite proper to use the designed SynRM as a traction motor of new generation electric vehicles.

Comprehensive Comparative Study on Permanent-Magnet-Assisted Synchronous Reluctance Motors and Other Types of Motor

At present, the induction motor (IM), synchronous reluctance motor (SynRM), ferrite-assisted synchronous reluctance motor (ferrite-assisted SynRM) and interior permanent magnet motor (IPM) are research hotspots, but comprehensive comparative research on the four motors is still rare. This paper mainly compares the four motors from the aspects of electromagnetic performance, material cost and temperature distribution. Firstly, the volume of the four motors is ensured to be the same. The influence of the rotor design parameters of the SynRM, ferrite-assisted SynRM and IPM on the electromagnetic properties of the machine is analyzed. Secondly, based on the effects of each parameter, the overall design parameters of the four motors are determined. The electromagnetic performance, material cost and temperature of the four motors are compared and discussed. Finally, the comparison results are summarized, and the advantages of the four motors are analyzed. In different applications, the electromagnetic performance, heat dissipation and cost requirements of the four motors are different. Therefore, this paper makes a comprehensive comparison of the four motors to provide a reference for the selection of motors for different applications.

Intelligent Backstepping Control of Permanent Magnet-Assisted Synchronous Reluctance Motor Position Servo Drive with Recurrent Wavelet Fuzzy Neural Network

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.

Field-Oriented Predictive Control Structure for Synchronous Reluctance Motors

This paper presents a cascade predictive control structure based on field-oriented control (FOC) in the dq rotor reference frame for the synchronous reluctance machine (SynRM). The constant d-axis current control strategy was used, and thus, the electromagnetic torque was directly controlled by the q-axis current. Because the model of the two axes of currents from the inner loop is a coupled non-linear multivariable one, to control in a non-interaction and linear way the two currents, their decoupling was achieved through feedforward components. Following the decoupling, two independent monovariable linear systems resulted for the two current dynamics that were controlled using model predictive control (MPC) algorithms, considering their ability to automatically handle the state bounds. The most important bounds for SynRM are the limits imposed on currents and voltages, which in the dq plane correspond to a circular limit. To avoid computational effort, linear limitations were adopted through polygonal approximations, resulting in rectangular regions in the dq plane. For the outer loop that controls the angular speed with a constrained MPC algorithm, the q-axis current closed-loop dynamics and the torque linear equation were considered. To evaluate the performance of the proposed cascade predictive control structure, a simulation study using MPC controllers versus PI ones was conducted.

Unified Vector Torque Control for Reluctance Motor With Different Coil Pitch

This paper unifies the vector torque control of reluctance motor with different coil pitch in the classic vector model frameworks, including the typical switched reluctance motor (SRM), mutually coupled switched reluctance motor (MCSRM), synchronous reluctance motor (SynRM) and so on. Based on the proposed vector model, the instantaneous electromagnetic torque of the reluctance motor is decoupled into two components. The first partial torque is called as the Synchronous-Speed Reluctance Force (SSRF), generated by the interaction of the <i>d</i>-axis and <i>q</i>-axis currents. The second partial torque is the Double-Speed Reluctance Force (DSRF), generated by the interaction between the <i>dq</i>-plane current and the 0-axis current. The torque formula can reflect the torque generation and fluctuation reasons, and the proportion of the two torque components is related to the ratio of the varying components of the motor&#x0027;s self-inductance and mutual inductance. Different types of reluctance motors can be summarized in the unified vector model. The conclusion is that the SynRM only contains the SSRF torque while the typical SRM and MCSRM contain both the SSRF torque and DSRF torque. The proposed unified vector torque control method is verified by simulations and experiments of 12-slot 8-pole reluctance motors with different coil pitch.

Proximate Maximum Efficiency Control for Synchronous Reluctance Motor via AMRCT and MTPA Control

To develop a high-efficiency synchronous reluctance motor (SynRM) drive system, a proximate maximum efficiency (PME) control is proposed in this study. First, a SynRM drive based on a traditional vector control with a constant <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i> -axis current command is developed. However, the constant command is not suitable for the high-efficiency applications of SynRM. Therefore, a three-control-mode system including the adjustable maximum rate of change of torque (AMRCT) control, finite element analysis (FEA)-type maximum torque per ampere (MTPA) control, and PME control is proposed to enhance the efficiency of the SynRM drive system. Moreover, the PME control is a combination of an AMRCT control and an FEA-type MTPA control. As a result, the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i> -axis current command is flexible and depends on the minimizing loss target chosen by the end-user. In addition, a novel adaptive computed <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">q</i> -axis current speed control with <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i> -axis current regulation is proposed to further increase the robustness of speed control. Finally, the proposed three-control-mode system is implemented in a 32-bit floating-point digital signal processor and some experimental results are provided to verify its effectiveness.

Vibration and Noise Optimization of New Asymmetric Modular PMaSynRM

This study proposes an optimized structure to weaken the vibration and noise of a new asymmetric permanent magnet-assisted synchronous reluctance motor (PMaSynRM). The new asymmetric PMaSynRM has the advantages of a low torque ripple and high fault tolerance. However, the asymmetric structure generates an unbalanced magnetic force (UMF), which results in vibration and noise problems. In this study, the vibration and noise of the motor are analyzed and optimized. First, the radial pressure is analyzed, and an optimized structure is proposed. The electromagnetic performance of the motor before and after optimization is analyzed using the finite element method. Second, a three-dimensional model is established, and modal analysis is conducted considering the orthotropy of the stator and effective windings. Finally, the vibration and noise are simulated and analyzed, and the validity of the analysis results is verified experimentally. The analysis results indicate that the optimized motor realizes a reduction in the motor vibration and noise.