Synchronous Reluctance Motor Research Articles

Analytical Calculation of Magnetic Field and Electromagnetic Performance for Permanent Magnet Assisted Synchronous Reluctance Motors Considering Saturation Effect

Analytical Calculation of Magnetic Field and Electromagnetic Performance for Permanent Magnet Assisted Synchronous Reluctance Motors Considering Saturation Effect

Optimal Adaptive Fractional Order Integral Sliding Mode Controller-Energy Management Strategy for Electric Vehicles Based on Bald Eagle Search Algorithm

This research presents an optimal energy management system (EMS) for a lithium-ion battery-supercapacitor hybrid storage system used to power an electric vehicle. The storage systems are connected in parallel to the DC bus by bidirectional DC-DC converters and feed a synchronous reluctance motor through an inverter. The proposed energy management strategy is built on the idea to take full benefits of two combined methods: the bald eagle search algorithm and fractional order integral sliding mode control. To evaluate the effectiveness of the suggested optimal energy management strategy, an urban dynamometer driving schedule (UDDS) driving cycle is considered. The obtained results are compared to a classical fractional order integral sliding mode control-based energy management strategy in terms of voltage ripples, overshoots, and battery final state of charge. The ultimate results approve the ability of the proposed energy management system to enhance the power quality and enhance battery power consumption at the same time. Comprehensive processor-in-the-loop (PIL) cosimulations were conducted on the electric vehicle using the C2000 launchxl-f28379d digital signal processing (DSP) board to assess the practicability and effectiveness of the proposed EMS.

Energy management of electric vehicle using a new strategy based on slap swarm optimization and differential flatness control

Optimal energy management of electric vehicles using slap swarm optimization and differential flatness control has been proposed. A battery–supercapacitor power system is adopted. Each source is connected in parallel to the DC-bus using DC–DC bidirectional converters and supplies a synchronous reluctance motor (SynRM) based drive. The proposed EMS fundamental forces lie in using a combination of complementary proprieties of two approaches, a Slap Swarm optimization Algorithm and Differential Flatness (DF). With a fast optimization mechanism, the Slap Swarm optimization algorithm allows adapting in real-time conditions the DF gains to optimize the system performances. On its side, DF uses predefined trajectories respecting the physical proprieties of the system, which is a powerful tool to guarantee the dynamic constraints of the sources when ensuring desired robust control proprieties. To check the feasibility and performance of the suggested EMS, comprehensive processor-in-the-loop co-simulations of the electric vehicle were carried out using the C2000 launchxl-f28379d DSP board. The main goal of the proposed EMS is to guarantee the DC-bus stabilization, reducing the DC-bus voltage ripples (Δv = 5 V) and the voltage overshoots 15 V (3.2%), respect the source dynamics, and satisfy the SynRM motor power demand. Furthermore, the algorithm minimizes induced harmonics by the drive (10.49%), reducing the battery current ripple by 17.15A, thereby enhancing the battery lifecycle.

A hybrid approach for PV based grid tied intelligent controlled water pump system

SummaryThis article proposes a hybrid POA‐RBFNN approach for PV (photovoltaic) based grid tied intelligent controlled water pump system. The proposed method is the hybrid wrapper of Pelican Optimization Algorithm (POA) and Radial Basis Function Neural Network (RBFNN) and later it is termed as POA‐RBFNN method. On the basis of bidirectional power grids, this research presents bidirectional power flow control for PV systems. The water pump is driven through a three‐phase synchronous reluctance motor (RSM). A novel Cuk integrated Landsman converter can operate at low duty cycles to provide larger DC voltages with negligible switching losses is used. In addition, to enhance the pumping system reliability, solar panels and electric pumps can be used to their maximum potential. Despite fluctuating weather conditions, the system supplies nominal displacement all over the day and surplus energy to the grid. Furthermore, if one of the sources fails, the pump performance is unaffected. Switching losses are minimized since the Voltage Source Inverter (VSI) operates at a fundamental frequency. In all operational modes, this control delivers unique grid‐side power quality and unity power factor functioning. Here, the performance of the proposed hybrid system is implemented in the MATLAB and is compared with several existing methods.

Dual-Sided Rotor Design for Performance Boost of Synchronous Reluctance Motors in Electric Vehicles

Increasing environmental awareness is pushing the design of electic motors to favor none rare-earth solutions (i.e., without permanent magnets), and one such example is the SyncRM 2 (or concentrated-coiled SRM2) being proposed for the electric hybrid automobile Toyota Yaris. Following on an already established line of research on this topic, this article proposes a new design that re-assigns most of the magnetic material in the stator to the rotor—resulting in the Dual-sided SyncRM (a variant of the SRM2). The detrimental effect (caused by the extra gap) of slightly reducing the aligned inductance is overwhelmingly outweighed by the beneficial effect of drastically reducing the unaligned inductance. Extensive back-to-back FEMM analysis was conducted, where the recomputed SRM2 matches previous research, providing confidence to the favorable predictions of the Dual-sided SyncRM. Both performances are compared, with the venue being available for download on an open-source database. A realistic photo-rendered three-dimensional model is displayed and also available. An important outcome is the Dual-sided SyncRM torque (and power) increased by 29% (with respect to the SRM2), achieving a saliency ratio of 10 and an efficiency boost to 91% (at the rated operational speed of 1200rpm).

Variable-Angle Random High-Frequency Voltage Injection Strategy with Cross-Saturation Effect Compensation for Sensorless Synchronous Reluctance Motor Drives

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.

Electromagnetic analysis of permanent magnet-assisted synchronous reluctance motor based on magnetic equivalent circuit

As rare-earth permanent magnet prices continue to fluctuate, interest in non-rare-earth permanent magnet-assisted synchronous reluctance motors (PMa-SynRMs) is increasing. However, non-rare-earth PMa-SynRMs have a multi-layer structure with interior permanent magnets to compensate for the low magnetic fields. Therefore, the rotor has several design parameters, and electromagnetic analysis is time-consuming. To overcome these challenges, magnetic equivalent circuit analysis was used to perform fast electromagnetic analysis of non-rare-earth PMa-SynRMs. In addition, the validity of the proposed method was confirmed through a comparison of the obtained results with those of finite element analysis.

A Parametric Model of a Synchronous Reluctance Motor with a TLA Rotor in Steady-State and Transient Modes

A Parametric Model of a Synchronous Reluctance Motor with a TLA Rotor in Steady-State and Transient Modes

Displacement Self-Sensing Control of Permanent Magnet Assisted Bearingless Synchronous Reluctance Motor Based on Least Square Support Vector Machine Optimized by Improved NSGA-II

In order to solve the problems of low integration, low reliability, and high cost caused by mechanical sensors used in bearingless synchronous reluctance motor (PMa-BSynRM) control system, a novel displacement self-sensing control method using a least square support vector machine (LSSVM) left inverse system is proposed. Firstly, the working principle of the PMa-BSynRM is introduced and the mathematical model of the PMa-BSynRM is derived. Secondly, the observation principle of the left-inverse system of the PMa-BSynRM is explained and the left-invertibility of the displacement subsystem is proved. Thirdly, the improved NSGA-II algorithm is utilized to optimize the the regularization parameter and the bandwidth of LSSVM, and the displacement self-sensing control system is constructed. The simulations of speed variation and anti-interference are performed, which proves the dynamic tracking performance of the displacement. Finally, the static suspension, speed variation and anti-interference experiments are carried out. The feasibility and reliability of the proposed displacement self-sensing method are verified.

Rare‐earth‐free Al‐Ni‐Co hybrid PMa‐SyRM for an air‐conditioner compressor

AbstractA hybrid ferrite‐Al‐Ni‐Co permanent magnet assisted synchronous reluctance motor (PMa‐SyRM) for an air‐conditioner compressor is proposed. Al‐Ni‐Co PMs have high residual flux density similar to rare‐earth PMs such as Nd‐Fe‐B and Sm‐Co. Therefore, the performance parameters of the PMa‐SyRM such as power factor, efficiency etc., with Al‐Ni‐Co PMs can be improved without significantly increasing the cost of the motor. However, Al‐Ni‐Co PMs have a steep IInd‐quadrant B‐H curve, and the challenge lies in addressing their demagnetisation issues. In the proposed hybrid PMa‐SyRM, the rotor geometry is suitably optimised for placing the Al‐Ni‐Co PMs in the centre flux barriers to address the demagnetisation issues. Further, an analytical magnetic circuit is presented to design the proposed PMa‐SyRM. Later, 2‐D finite element analysis of the proposed motor including the demagnetisation analysis of PMs and stress analysis of the rotor is carried out and presented. A prototype is fabricated, experimental validation is carried out, and the results of the performance and cost are compared with that of ferrite and hybrid ferrite‐Nd‐Fe‐B PMa‐SyRM.

Simplified thermal model for open type 1.5 kW synchronous reluctance motor using thermal equivalent circuit and finite element method

In this study, two thermal models, the thermal equivalent circuit (TEC) and finite element method (FEM), were used for the transient thermal analysis of an open-type synchronous reluctance motor. Both the transient TEC method and the FEM were carried out for longer than 3 h after the motor was driven to reach a steady state. The results were compared with experimental results to verify the feasibility of the two thermal models. When the experimental results were compared with the TEC method results, the average temperature difference of all the parts was within 9 %. When the experimental and FEM results were compared, the average temperature difference of all the parts was within 7 %. Therefore, both thermal models are suitable for predicting the motor temperature.

Comparative analysis of energy performance of squirrel cage induction motor, line-start synchronous reluctance and permanent magnet motors employing the same stator design

Comparative analysis of energy performance of squirrel cage induction motor, line-start synchronous reluctance and permanent magnet motors employing the same stator design

Analysis and effect of static eccentricity fault on performance indicators of a synchronous reluctance motor

Analysis and effect of static eccentricity fault on performance indicators of a synchronous reluctance motor

Electromagnetic design, sensitivity analysis, optimization and Multiphysics capability of rare-earth-free synchronous reluctance motor for electric trike vehicle

<p>As a part of last-mile transportation, electric three-wheelers, popularly known as trikes, are considered as an important aspect of the future of the auto industry. The appropriate choice of electric traction motor drive is imperative to the design of an electric motor power train. In this paper, six main types of sinusoidal-fed electric motor power trains—Ferrite-Assisted Synchronous Reluctance Motor (FASRM), Synchronous Reluctance Motor (SyncRelM), Ferrite-based Spoke motor, Ferrite-based Surface-Mounted Permanent Magnet Synchronous Motor (SMPMSM), Wound-Field Synchronous Motor (WFSM), and Induction Motor (IM)—are compared for their performance in electric trike applications. The permanent magnet machines presented here utilize ferrite magnets, in line with the recent trend of not using rare-earth magnets. The comprehensive comparative analysis establishes that SyncRelM, FASRM, and Spoke motors are superior in terms of overall electromagnetic, thermal, and vibration performance. This paper also focuses on an optimal design of the FASRM due to its high torque density, lower torque ripple, and minimal use of ferrite magnets. A Design of Experiments (DoE)-based statistical analysis tool is used to identify the key parameters needed for robust motor performance in the optimization step. Furthermore, an Extreme Learning Machine (ELM)-based interpolation technique is employed for estimating the performance parameters during each step of the optimization routine. A 1.2 kW FASR motor prototype is developed and tested. A comparison of Finite-Element-Analysis-based modeling results is presented along with Indian drive-cycle results for the FASRM for trike application.</p>

Robust compensation with adaptive fuzzy Hermite neural networks in synchronous reluctance motors

In this paper, a robust compensation scheme using adaptive fuzzy Hermite neural networks (RCAFHNN), for use in synchronous reluctance motors (SRMs), is proposed. SRMs have a simple underlying mathematical model and mechanical structure, but are affected by problems related to parameter variations, external interference, and nonlinear dynamics. In many fields, precise control of motors is required. Although the use of neural network and fuzzy are widespread, such controllers are affected by unbound nonlinear system model. In this study, RCAFHNN, based on an adaptive neural fuzzy interface system (ANFIS), was used to bound motor system model controller algorithm. RCAFHNN can be characterized in three parts. First, RCAFHNN offers fuzzy expert knowledge, a neural network for online estimation, and recursive weight estimation. Second, the replacement of the Gaussian function by the Hermite polynomial in RCAFHNN enables reduced membership function training times. Third, the system convergence and robustness compensation of RCAFHNN were confirmed using Lyapunov stability. RCAFHNN ameliorates the problems of external load and system lump uncertainty. The experimental results, in which the output responses of RCAFHNN and ANFIS (adaptive neural fuzzy interface systems) were compared, demonstrated that RCAFHNN exhibited superior performance.

Adaptive-Based Accurate Rotor Initial Position Estimation in Synchronous Reluctance Motors

Adaptive-Based Accurate Rotor Initial Position Estimation in Synchronous Reluctance Motors

Efficiency Enhancement in Synchronous Reluctance Motors by Active Flux Adjustment Based on Robust Model-Based Approaches

Efficiency Enhancement in Synchronous Reluctance Motors by Active Flux Adjustment Based on Robust Model-Based Approaches

An Impact of Switching Frequency and Model Accuracy on Model Predictive Current Control Performance for Reluctance Synchronous Motors

Abstract The present paper investigates the feasibility of utilizing the simplified prediction model for finite control set model predictive current control (FCS-MPCC) applied to reluctance synchronous motors (RSMs). The FCS-MPCC exhibits torque and current ripples, and a crucial consideration is the reduction of these ripples by increasing the switching frequency. The algorithm’s computational complexity is tied to the accuracy of the adopted model. Two approaches with varying levels of accuracy in predicting current dependencies concerning changes in the inductance of the RSM are investigated. The findings highlight the potential of employing simplified fixed inductance values for efficient control in drive systems, particularly those amenable to high switching frequencies.

Robust Sensorless Control of Synchronous Reluctance Motor Based on PDSH-KF Considering Dynamic Magnetic Saturation Effect

Robust Sensorless Control of Synchronous Reluctance Motor Based on PDSH-KF Considering Dynamic Magnetic Saturation Effect

Current Control of Electrolytic Capacitor-Less Variable Frequency Drive System for Synchronous Reluctance Motors Based on Power Balancing and Compensation

Current Control of Electrolytic Capacitor-Less Variable Frequency Drive System for Synchronous Reluctance Motors Based on Power Balancing and Compensation