RESUMO
Recycling the valuable metals found in spent permanent magnets (REPMs) poses a significant global challenge for the future. This study examines the efficiency of back extraction of rare earth elements (REEs) by oxalic acid solution from di-(2-ethylhexyl) phosphoric acid (D2EHPA) in recycling REPMs. To evaluate the efficiency of this process, several experiments were carried out using designed BOX-Behnken methodology to investigate the effects of various operational and chemical parameters, including stripping solution to loaded organic phase volume ratio (in the range of 1.0-2.0), oxalic acid concentration (ranging from 0.25 to 0.75 M), the stirring rate (ranged between 150 and 350 rpm), and stripping time (ranging from 15 to 45 min) on the REEs recovery and the purity of final production. Analysis of variance was applied to rigorously examine the results statistically. The results showed that more than 85 % of light and 80 % of heavy REEs can be recovered under optimal conditions. Moreover, the final product contained 43.5 % REEs and approximately 0.1 % iron. The stripping experiment using phosphoric acid as the reagent demonstrated â¼57 % light and â¼4 % heavy REEs recovery. Additionally, the recyclability of the organic phase showed its effective reuse for up to four cycles. This study underscores significant progress in the selective recovery of rare earth elements through a relatively straightforward process consuming mild reagents.
RESUMO
This research paper introduces the Double Stator (DS) Hybrid Excitation (HE) Halbach Permanent Magnet (HPM) Flux Switching (FS) machine. The machine construction and its optimization specifically designed for electric vehicle (EV)/hybrid electric vehicle (HEV) traction applications are investigated. The optimization using a multi-objective Genetic Algorithm is conducted following a sensitivity analysis-based identification of key optimization parameters and constraints. The finite element results are compared with the performance of a state-of-the-art benchmark FSPM machine having identical PM volume and winding current densities. The proposed design is shown to outperform the benchmark with 16.2% increase in back-electromotive force and 14.7% reduction in cogging torque. Furthermore, the average torque is improved at flux-enhancing operation by 20.8%, and the torque ripple is reduced by 9.9%. Notably, the proposed machine also is capable of flux regulation thereby having the ability to operate in a wide speed range. A detailed explanation of the reasons for the significant improvements in the proposed machine structure is provided to offer a comprehensive understanding of its rationale. These research findings indicate that this innovative DS-HE-HPM-FS machine can enhance the performance of EVs and HEVs.
RESUMO
In this study, the use of an Unscented Kalman Filter as an indicator in predictive current control (PCC) for a wind energy conversion system (WECS) that employs a permanent magnetic synchronous generator (PMSG) and a superconducting magnetic energy storage (SMES) system connected to the main power grid is presented. The suggested UKF indication in the hybrid WECS-SMES arrangement is in charge of estimating vital metrics such as stator currents, electromagnetic torque, rotor angle, and rotor angular speed. To optimize control strategies, PCCs use these projected properties rather than direct observations. To control the unpredictable wind energy's nature, SMES must be regulated to minimize fluctuations in the DC-link voltage and power output to the main grid. Fractional order-PI (FOPI) controllers are used in a novel control structure for the SMES system to regulate the output power and DC-link voltage. An artificial bee colony optimization approach is employed to optimize the FOPI controllers. Three commonly utilized indicators, including sliding-mode, EKF, and Luenberger, were evaluated using "MATLAB" to evaluate the performance of the UKF estimate. Assessment criteria such as mean absolute percentage error and root mean squared error were used to gauge the accuracy of the estimates. Simulation findings showed the efficiency of fractional order-PI controllers for SMES and the proposed UKF indication for predictive current control, especially in the presence of measurement noise and over a variety of wind speeds. An improvement in estimation accuracy of up to 99.9 % was demonstrated by the UKF indicator. Moreover, the stability of the suggested UKF-based PCC control for the hybrid WECS-SMES combination was confirmed using Lyapunov stability criteria."
RESUMO
Permanent magnet synchronous machine (PMSM) has proven to be a more economical traction drive system for electric vehicle (EV) applications owing to increased efficiency and high-power density. However, the drive system requires more efficient control schemes to deliver better dynamic performance irrespective of dynamic changes in the motor speed, machine parameters and disturbances. Hence, to tackle the dynamic changes, to enhance the wider operating speed, to achieve precise speed tracking capability, and improved efficiency, a novel control algorithm for the PMSM based EV is proposed in this paper. The control algorithm is implemented by adopting the merits of conventional proportional resonance (PR) and proportional integral (PI) controller. The proposed control strategy is designed with an outer PI speed regulator and the inner enhanced PR (EPR) current regulator. The uniqueness of the proposed EPR controller is that the controller is designed to damp the torsional mode oscillation owing to dynamic changes such as speed and torque regulation evading the additional control loop. The effectiveness of the control scheme is tested in MATLAB Simulink and hardware-in-loop (HIL) real time simulator RT5700. To validate the effectiveness of the proposed control scheme the results are compared with the conventional control schemes. The results presented show that the proposed control technique successfully enhances the static and dynamic performance, and resilience of the EV system. Also, the proposed scheme significantly reduces the flux ripples, torque ripples, current jitter, peak overshoot, undershoot compared to the conventional current controllers.
RESUMO
We propose a method to control the motion of a capsule endoscope (CE) in the stomach utilizing either a single external permanent magnet (EPM) or dual EPMs to extend the examination of the upper gastrointestinal tract. When utilizing the conventional magnetic navigational system (MNS) with a single EPM to generate tilting and rotational motions of the CE, undesired translational motion of the CE may prevent accurate examination. We analyzed the motion of the CE by calculating the magnetic torque and magnetic force applied to the CE using the point-dipole approximation model. Using the proposed model, we propose a method to determine the optimal position and orientation of the EPM to generate tilting and rotational motions without undesired translational motion of the CE. Furthermore, we optimized the weight of dual EPMs to develop a lightweight MNS. We prototyped the proposed MNS and experimentally verified that the developed MNS can generate tilting and rotational motions of the CE without any translational motion.
RESUMO
The more effective use of readily available Ce in FeNdB sintered magnets is an important step towards more resource-efficient, sustainable, and cost-effective permanent magnets. These magnets have the potential to bridge the gap between high-performance FeNdB and hard ferrite magnets. However, for higher degrees of cerium substitution (>25%), the magnetic properties deteriorate due to the lower intrinsic magnetic properties of Fe14Ce2B and the formation of the Laves phase Fe2Ce in the grain boundaries. In this paper, sintered magnets with the composition Fe70.9-(CexNd1-x)18.8-B5.8-M4.5 (M = Co, Ti, Al, Ga, and Cu; with Ti, Al, Ga, and Cu less than 2.0 at% in total and Cobal; x = 0.5 and 0.75) were fabricated and analyzed. It was possible to obtain coercive fields for higher degrees of Ce substitution, which previous commercially available magnets have only shown for significantly lower degrees of Ce substitution. For x = 0.5, coercivity, remanence, and maximum energy product of µ0Hc = 1.29 T (Hc = 1026 kA/m), Jr = 1.02 T, and (BH)max = 176.5 kJ/m3 were achieved at room temperature for x = 0.75 µ0Hc = 0.72 T (Hc = 573 kA/m), Jr = 0.80 T, and (BH)max = 114.5 kJ/m3, respectively.
RESUMO
A fuzzy coefficient q-axis current increment flux weakening (FCCIFW) control method is proposed in interior permanent magnet synchronous motor (IPMSM) drives. The proposed FCCIFW not only simplifies the calculation of flux weakening coefficient according to the derived formula, but also avoids the saturation of current regulator. In FCCIFW, the theoretical calculation formula of conversion coefficient is derived firstly, and then the fuzzy rule base is established according to the formula. FCCIFW not only refrains the use of complex flux weakening calculation formula or fixed control parameters, but also refrains the problem of out-of-control in the process of deep flux weakening control, so as to improve the overall performance in the process of flux weakening. The results show that the proposed method has an effective and correct calculation process and results, Compared with different control methods in the operation process, it shows that the proposed method has more stable control effect, which has great application value in engineering.
RESUMO
Bonded permanent NdFeB magnets are useful in numerous applications, including electric vehicles, and the demand is steadily increasing. A major drawback is corrosion due to inadequate wetting of the magnetic particles by liquid polymers such as polyphenylene sulfide or polyamide. Recently reported methods for corrosion inhibition are summarized, and their applicability is critically evaluated. The phosphorylation of magnetic particles inhibits corrosion but does not enable appropriate properties in harsh environments. The same applies to metallic coatings, which usually contain aluminum and zinc. Advanced epoxy adhesives are a promising solution, although some authors have reported inadequate corrosion resistance. The application of composite coatings seems like an appropriate solution, but the exact mechanisms are yet to be studied.
RESUMO
Hydrogenation-Disproportionation-Desorption-Recombination (HDDR) Nd2Fe14B particles have excellent magnetic properties, but the magnetic properties of powder are not uniform across different particle sizes. The remanence and maximum magnetic energy products of samples with a particle size of 120 µm are 14.0 kGs and 41.35 MGOe, while the products of samples with a particle size of 60 µm are only 13.3 kGs and 36.31 MGOe. The macroscopic morphology of HDDR Nd2Fe14B particles and the gradient distribution of microstructures in different micro-regions were observed. By modifying the macroscopic morphology of the particles, the poorly oriented clusters on the surface of the particles were precisely eliminated, and the remanence and maximum magnetic energy products of the particles increased to 14.5 kGs and 45 MGOe, respectively. Compared with the original particles, the samples after mechanical grinding had better grain arrangement. The effects of the nanocrystalline c-axis and field misalignment angle θ on the magnetic properties of HDDR Nd2Fe14B particles were investigated through micromagnetic simulation. The targeted removal of macroscopic defects on the particle surface contributed to a 3.6% increase in remanence and an 8.8% increase in the maximum magnetic energy product, offering a promising approach to enhance the microstructure of high-performance HDDR Nd2Fe14B particles.
RESUMO
We present two magnetic particle imaging (MPI) systems with bore sizes of 75 mm and 100 mm, respectively, using three-dimensionally arranged permanent magnets for excitation and frequency mixing magnetic detection (FMMD) coils for detection. A rotational and a translational stage were combined to move the field free line (FFL) and acquire the MPI signal, thereby enabling simultaneous overall translation and rotational movement. With this concept, the complex coil system used in many MPI systems, with its high energy consumption to generate the drive field, can be replaced. The characteristic signal of superparamagnetic iron oxide (SPIO) nanoparticles was generated via movement of the FFL and acquired using the FMMD coil. The positions of the stages and the occurrence of the f1 + 2f2 harmonics were mapped to reconstruct the spatial location of the SPIO. Image reconstruction was performed using Radon and inverse Radon transformations. As a result, the presented method based on mechanical movement of permanent magnets can be used to measure the MPI, even for samples as large as 100 mm. Our research could pave the way for further technological developments to make the equipment human size, which is one of the ultimate goals of MPI.
RESUMO
Permanent magnet synchronous motor (PMSM) systems have gained popularity in various fields due to their advantages such as high speed, high accuracy, low maintenance, and high reliability. This paper presents the speed tracking control of a permanent magnet synchronous motor (PMSM) using a hybrid fractional order PI and type 2 fuzzy control with fractional order PD control (FOT2F-FOPD). The SRF-PLL observes the motor speed and estimates the rotor's position by interpreting the input voltages of the motor instead of using a sensor. Then, the controller parameters (gain, µ and λ) are tuned based on a novel optimization algorithm called Incomprehensible but Intelligible-in-time (IbI) Logics algorithm (ILA). The proposed controller enhances the performance of the system and regulates the speed of the motor under parameter variations such as the speed and the load. So, the proposed ILA (FOT2F-FOPD) controller is assessed using MATLAB/Simulink simulation and compared with other controller techniques. The proposed technique reduces the settling time, steady state error and overshoot by at least 65%, 54% and 53% respectively under load conditions compared with (PSO, optimized FOPD, FOPI and PI). While at no load condition, the settling time and the error are reduced by 31% and 12.5% respectively with no overshoot in output response. The results show a significant improvement in the performance of motors used with the application of the proposed controller and the employment of the (ILA) optimization compared with FOPI and PI controllers.
RESUMO
Sensor faults are one of the most common faults that cause performance degradation or functional loss in permanent magnet traction drive systems (PMTDSs). To quickly diagnose faulty sensors, this paper proposes a real-time joint diagnosis method for multi-sensor faults based on structural analysis. Firstly, based on limited monitoring signals on board, a structured model of the system was established using the structural analysis method. The isolation and detectability of faulty sensors were analyzed using the Dulmage-Mendelsohn decomposition method. Secondly, the minimum collision set method was used to calculate the minimum overdetermined equation set, transforming the higher-order system model into multiple related subsystem models, thereby reducing modeling complexity and facilitating system implementation. Next, residual vectors were constructed based on multiple subsystem models, and fault detection and isolation strategies were designed using the correlation between each subsystem model and the relevant sensors. The validation results of the physical testing platform based on online fault data recordings showed that the proposed method could achieve rapid fault detection and the localization of multi-sensor faults in PMTDS and had a good application value.
RESUMO
The efficient design of Permanent Magnet Synchronous Motors (PMSMs) is crucial for their operational performance. A key design parameter, cogging torque, is significantly influenced by various structural parameters of the motor, complicating the optimization of motor structures. This paper proposes an optimization method for PMSM structures based on heuristic optimization algorithms, named the Permanent Magnet Synchronous Motor Self-Optimization Lift Algorithm (PMSM-SLA). Initially, a dataset capturing the efficiency of motors under various structural parameter scenarios is created using finite element simulation methods. Building on this dataset, a batch optimization solution aimed at PMSM structure optimization was introduced to identify the set of structural parameters that maximize motor efficiency. The approach presented in this study enhances the efficiency of optimizing PMSM structures, overcoming the limitations of traditional trial-and-error methods and supporting the industrial application of PMSM structural design.
RESUMO
Considering the high-speed and high power density technical specifications of new energy vehicle motors, there is a growing demand for rotor strength as motor peak speeds reach 20,000 r/min and beyond. The utilization of non-oriented silicon steel with a high yield strength in rotors has emerged as a promising approach to increase motor speed. However, the magnetic and mechanical properties of high-strength silicon steel under variable temperature conditions have not been fully explored, particularly in regards to their impact on motor torque, efficiency, and speed. This manuscript investigates the behavior of high-strength silicon steel before and after annealing and at different temperatures, analyzing its influence on high-speed motor performance. The validity and feasibility of this study are confirmed through prototype testing, providing a comprehensive reference for engineering design.
RESUMO
Achieving precise control over the motion position and attitude direction of magnetic microrobots remains a challenging task in the realm of microrobotics. To address this challenge, our research team has successfully implemented synchronized control of a microrobot's motion position and attitude direction through the integration of electromagnetic coils and permanent magnets. The whole drive system consists of two components. Firstly, a stepper motor propels the delta structure, altering the position of the end-mounted permanent magnet to induce microrobot movement. Secondly, a programmable DC power supply regulates the current strength in the electromagnetic coil, thereby manipulating the magnetic field direction at the end and influencing the permanent magnet's attitude, guiding the microrobot in attitude adjustments. The microrobot used for performance testing in this study was fabricated by blending E-dent400 photosensitive resin and NdFeB particles, employing a Single-Layer 4D Printing System Using Focused Light. To address the microrobot drive system's capabilities, experiments were conducted in a two-dimensional and three-dimensional track, simulating the morphology of human liver veins. The microrobot exhibited an average speed of 1.3 mm/s (movement error ± 0.5 mm). Experimental results validated the drive system's ability to achieve more precise control over the microrobot's movement position and attitude rotation. The outcomes of this study offer valuable insights for future electromagnetic drive designs and the application of microrobots in the medical field.
RESUMO
The Permanent Magnet Synchronous Motor (PMSM) is the power source maintaining the stable and efficient operation of various pieces of equipment; hence, its reliability is crucial to the safety of public equipment. Convolutional Neural Network (CNN) models face challenges in extracting features from PMSM current data. A new Discrete Wavelet Transform Convolutional Neural Networks (DW-CNN) feature with fusion weight updating Long Short-Term Memory (LSTM) anomaly detection is proposed in this paper. This approach combines Discrete Wavelet Transform (DWT) with high and low-frequency separation processing and LSTM. The anomaly detection method adopts DWT and CNN by separating high and low-frequency processing. Moreover, this method combines the hybrid attention mechanism to extract the multi-current signal features and detects anomalies based on weight updating the LSTM network. Experiments on the motor bearing real fault dataset and the PMSM stator fault dataset prove the method's strong capability in fusing current features and detecting anomalies.
RESUMO
Because the magnetic properties of an amorphous alloy (AA) obviously change with the change of temperature, a finite element simulation method for a motor, considering the effect of temperature, is proposed in this paper. In the early design stage of the high-speed permanent magnet synchronous motor (PMSM), the simulation of motor performance is mainly based on the magnetic performance test data at room temperature provided by the material's manufacturer. However, the influence of the temperature rise during the actual operation of the motor will lead to large errors between the simulation results and the measured results. Therefore, it is of great practical significance to measure the magnetic properties of the AA at different temperatures and use them for simulation purposes. In this paper, the magnetization characteristics and iron loss characteristics of the AA and silicon steel (ST100) used for comparison are measured at different temperatures, and the iron loss separation of the two materials at different temperatures is completed, and the hysteresis loss coefficient and eddy current loss coefficient at different temperatures are obtained. On this basis, the performance simulation of a motor model is carried out. The more accurate simulation method proposed in this paper can provide a reference for the design of AA motors in industry.
RESUMO
Achieving accurate position tracking for robotics and industrial servo systems is an extremely challenging task, particularly when dealing with control saturation, parameter perturbation, and external disturbance. To address these challenges, a predefined time convergent sliding mode adaptive controller (PTCSMAC) has been proposed for a permanent magnet linear motor (PMLM). A novel sliding mode surface (SMS) with predefined time convergence PDTC has been constructed, which ensures that the error converges to zero within the prescribed time. The system not only meets the expected performance standards but also has a uniformly bounded motor speed. The trajectory tracking error in SMS is proven to converge to zero within the predefined time. This predefined time stability of the closed-loop system has been demonstrated by using the Lyapunov stability criterion with PDTC. The convergence time (CT) can be arbitrarily set, and the upper bound of it is not affected by the initial value and control parameters of the system. A new updated version of extreme learning machine (ELM) is introduced to approximate the uncertain part of the system based on PDTC. The ELM is also provided with the hyperbolic tangent function to estimate the saturation constraint. This is done by converting the function into a linear function concerning the unconstrained control input variable. Then, based on established stability, a novel sliding mode adaptive controller (PTCSMAC) with predefined time convergence is designed. The convergence time (CT) of the controller is unaffected by the initial conditions as well as the control parameters. The rigorous numerical simulations on the PMLM model with complex disturbances verify the strong robustness and high-precision tracking characteristic of the proposed control law.
RESUMO
Field Oriented Control (FOC) effectively realizes independent control of flux linkage and torque, and is widely used in application of Permanent Magnet Synchronous Motor (PMSM). However, it is necessary to detect the phase current information of the motor to realize the current closed-loop control. The phase current detection method based on a sampling resistor will cause a measurement error due to the influence of parasitic parameters of the sampling resistor, which will lead to the decrease in PMSM control performance. This paper reveals the formation mechanism of the current sampling error caused by parasitic inductance and capacitance of the sampling resistor, and further confirms that the above error will lead to the fluctuation of the electromagnetic torque output by simulation. Moreover, we propose an approach for online observation and compensation of the current sampling error based on PI-type observer to suppresses the torque pulsation of PMSM. The phase current sampling error is estimated by the proportional and integral (PI) observer, and the deviation value of current sampling is obtained by low-pass filter (LPF). The above deviation value is further injected into the phase current close-loop for error compensation. The PI observer continues to work to keep the current sampling error close to zero. The simulation platform of Matlab/Simulink (Version: R2021b) is established to verify the effectiveness of online error observation and compensation. Further experiments also prove that the proposed method can effectively improve the torque fluctuation of the PMSM and enhance its control accuracy performance of rotation speed.
RESUMO
This paper focuses on the speed control of a permanent magnet synchronous motor (PMSM) for electric drives with model uncertainties and external disturbances. Conventional sliding mode control (CSMC) can only converge asymptotically in the infinite domain and will cause unacceptable sliding mode chattering. To improve the performance of the PMSM speed loop in terms of response speed, tracking accuracy, and robustness, a hybrid control strategy for a fixed-time-convergent sliding mode controller (FSMC) with a fixed-time-convergent sliding mode observer (FSMO) is proposed for PMSM speed regulation using the fixed-time control theory. Firstly, the FSMC is proposed to improve the convergence speed and robustness of the speed loop, which can converge to the origin within a fixed time independent of the initial conditions. Then, the FSMO is used as a compensator to further enhance the robustness of the speed loop and attenuate sliding mode chattering. Finally, simulation and experimental results show that the proposed method can effectively improve the dynamic performance and robustness of the PMSM speed control system.