Rotor Position Research Articles

Enhancing the solar water pumping efficiency through Beta MPPT method-controlled drive

This paper presents an innovative approach to achieve efficient solar water pumping through the integration of a Photovoltaic (PV) array and a Brushless Direct Current (BLDC) motor water pumping system. The system incorporates a Voltage Source Converter (VSC) with six switches, utilized to facilitate commutation. The inherent solar radiation is harnessed by the PV array, capitalizing on its renewable nature to generate electricity. By dynamically adjusting the switching states of the six VSC switches, the speed of the BLDC motor is modulated in response to the varying levels of available solar radiation. The BLDC motor's hall sensor signals play a crucial for determining the rotor's position and they are employed to generate precise commutation signals. The control strategy integrates the Incremental Conductance (INC) Maximum Power Point Tracking (MPPT) algorithm, which initially governs the commutation signals. To enhance adaptability to rapidly changing solar irradiation conditions, the control strategy dynamically updates the commutation signals using the innovative Beta MPPT algorithm. To assess the efficiency of the proposed control strategy, a comprehensive comparison between the INC and Beta MPPT algorithms is conducted using MATLAB Simulink. The performance of the BLDC motor under these algorithms was evaluated in terms of its ability to optimize energy extraction. The graphical analysis of these algorithms, considering the temporal aspect, substantiates the identification of the superior MPPT algorithm for BLDC motor control in solar water pumping applications. This study contributes to the advancement of solar water pumping systems by introducing a novel control approach that combines PV array utilization, VSC-based commutation, and a dual-step MPPT algorithm. The results demonstrate the effectiveness of the Beta MPPT algorithm by enabling the system to respond promptly to fluctuating solar irradiation conditions, thereby enhancing the overall efficiency of the solar water pumping process.

Investigation on the Aerodynamic Performance and Flow Mechanism of Transonic Ultra-Highly Loaded Tandem-Rotor Stage

The compressor serves as a crucial component that influences the performance of the gas turbine engine. Researchers have been endeavoring to explore compressor types that possess a high loading level and high-efficiency characteristics concurrently. In this study, tandem blade technology was applied to a transonic ultra-highly loaded axial compressor, and the Baseline single-blade rotor was replaced by a tandem rotor to take into account the loading level and compressor performance. Detailed investigations were carried out to identify the effects on the aerodynamic performance of the ultra-highly loaded stage and the fundamental flow mechanism within the tandem-rotor stage. This paper presents original design maps for the tandem-rotor stage, and the selection criteria for tandem parameters in tandem-rotor stage are refined. The results indicate that the peak efficiency improved by 0.83%, the stall margin increased by 2.16%, and the choke flow rate rose by 0.30% for the optimal tandem-rotor configuration. The meridional division position of the rotor primarily affects the ratio of loading of the front and rear blades, while the circumferential relative position of the tandem rotor mainly influences the channel types formed by the front and rear blades. Larger values for the meridional division position parameter and smaller values for circumferential relative position parameter should be selected for the tandem rotor design to optimize both the isentropic efficiency and total pressure ratio. This investigation offers the theoretical foundation for the design of a transonic ultra-highly loaded tandem-rotor compressor.

Theoretical characterization and its application of electromagnetic anisotropy in high-temperature superconducting bulks under rotated postures

The electromagnetic anisotropy of high-temperature superconducting (HTS) bulks limits their levitation ability in the applied magnetic fields from the permanent magnet guideway (PMG), thus impeding the enhancement of load-carrying capacity in HTS pinning maglev systems. Developing a suitable matching scheme between bulk orientation and magnetic field direction is a valuable way to relieve this restriction. In this paper, a method for characterizing bulk anisotropy in a rotating coordinate system is proposed to explore the best bulk orientation. The method is based on the concept of equivalent resistivity tensor and its eigenvectors, and includes an extended description of two types of anisotropy: conductivity anisotropy and magnetic field angle dependence. It provides a theoretical foundation for simulating anisotropic bulks under any rotated posture. Experimental investigations on the levitation force distribution of cylindrical bulks with different c-axis orientation were conducted, through which the accuracy of the characterization method and calculated results were validated. Analysis of current distribution reveals that aligning the c-axis parallel to the external magnetic field helps achieve the best match between the bulk and the PMG. Additionally, considering that the two types of anisotropy have opposite effects on levitation force distribution trends, prioritizing conductivity anisotropy when analyzing anisotropic bulk is recommended. This research not only offers a theoretical framework for simulating the anisotropy of rotated HTS bulks but also provides guidance for matching the optimal bulk orientation in applied magnetic fields.

Development of an electric drive for personal light electric vehicles

Problem. The article addresses the challenge of enhancing inclusive mobility and environmental cleanliness by developing a traction electric drive for personal light electric vehicles. A study was conducted on modern electric drive systems for personal light electric vehicles. Goal. The aim is to boost inclusive mobility and environmental cleanliness through the development of a traction electric drive for a personal light electric vehicle, specifically based on a tricycle. Methodology. The methodology involves scientific analysis and synthesis of traction electric drives for electric vehicles. An assessment of the nominal capacity of the battery module from the Nissan Leaf electric car was conducted using both partial discharge procedures and the Leaf Spy Pro program. Results. Based on an analysis of existing electric drive systems, a traction electric drive for a tricycle was developed. A functional diagram of the electric bicycle drive was generated. A control system for a sensorless brushless motor was developed, determining rotor position by measuring EMF in the free phase. This led to the creation of a stable voltage electrical circuit with a virtual midpoint. The tricycle's electric drive utilizes two 10-inch motor wheels on the rear wheels, enabling high speed and efficiency. Controllers specifically designed for electric wheel motors with a power of 350 W were selected to control the traction electric drive. Modules from the 2015 Nissan Leaf electric car's battery, which had depleted 20% of their capacity, were chosen to power the electric drive. The battery health status is 77.95%. A model of the battery's electrical equivalent circuit was constructed, and partial discharge graphs of the Nissan Leaf battery module were analyzed. Originality. The results provide a comprehensive insight into the development of a traction electric drive for personal light electric vehicles, using a tricycle as an example. Practical value. The research led to the development of an electric drive for a three-wheeled vehicle, with two motor wheels of 350 W nominal power each. The power supply voltage ranges from 36 V to 48 V, powered by six battery modules from the Nissan Leaf electric car, totaling 48 V. The energy capacity of one battery module is 0.3898 kWh, resulting in a total energy capacity of 2.3388 kWh for the vehicle's battery. However, the realizable capacity does not exceed 1.871 kWh, providing a travel distance of approximately 75 km on one battery charge. These findings demonstrate the feasibility of reusing batteries from electric cars with diminished capacity to power light electric vehicles. The results are relevant for scientific and technical professionals involved in electric vehicle development.

RoUIE: A Method for Constructing Knowledge Graph of Power Equipment Based on Improved Universal Information Extraction

The current state evaluation of power equipment often focuses solely on changes in electrical quantities while neglecting basic equipment information as well as textual information such as system alerts, operation records, and defect records. Constructing a device-centric knowledge graph by extracting information from multiple sources related to power equipment is a valuable approach to enhance the intelligence level of asset management. Through the collection of pertinent authentic datasets, we have established a dataset for the state evaluation of power equipment, encompassing 35 types of relationships. To better suit the characteristics of concentrated relationship representations and varying lengths in textual descriptions, we propose a generative model called RoUIE, which is a method for constructing a knowledge graph of power equipment based on improved Universal Information Extraction (UIE). This model first utilizes a pre-trained language model based on rotational position encoding as the text encoder in the fine-tuning stage. Subsequently, we innovatively leverage the Distribution Focal Loss (DFL) to replace Binary Cross-Entropy Loss (BCE) as the loss function, further enhancing the model’s extraction performance. The experimental results demonstrate that compared to the UIE model and mainstream joint extraction benchmark models, RoUIE exhibits superior performance on the dataset we constructed. On a general Chinese dataset, the proposed model also outperforms baseline models, showcasing the model’s universal applicability.

Reduced belowground allocation of freshly assimilated C contributes to negative plant-soil feedback in successive winter wheat rotations

Abstract Aims Successive winter wheat (WW) rotations are associated with yield reduction, often attributed to the unfavorable soil microbes that persist in the soil through plant residues. How rotational positions of WW affect the allocation of freshly assimilated carbon (C), an energy source for soil microbes, above and belowground remains largely unknown. Methods A 13CO2 pulse labeling rhizotron experiment was conducted in the greenhouse to study freshly fixed C allocation patterns. WW was grown in soil after oilseed rape (W1), after one season of WW (W2), and after three successive seasons of WW (W4). We used an automatic manifold system to measure excess 13C of soil respiration at six depths and five different dates. Excess 13C was also measured in dissolved organic C (DOC), microbial and plant biomass pools. Results There was a strong yield decline in successive WW rotations accompanied by distinct changes in root growth. Higher excess 13C of soil respiration was measured in W1 compared to W4, especially in the topsoil during at later growth stages. Higher excess 13C of the DOC and the microbial biomass was also traced in W1 and W4 compared to W2. Less 13C was taken up by successive WW rotations. Conclusions Our study demonstrates a mechanism through which the rotational position of WW affects the allocation of freshly assimilated C above and belowground. WW after oilseed rape sustains belowground allocation of freshly assimilated C for a longer time than successively grown WW and incorporates more of this C to its biomass.

Dynamic Performance Evaluation of a Brushless AC Motor Drive Using Different Sensorless Schemes

The presented study concerns with evaluating the dynamic performance of an isotropic sinusoidal brushless motor drive while utilizing different sensorless schemes. Three estimation algorithms are considered: the first depends on extracting the speed and position via comparing two values of motor's voltage in two co-ordinate systems; the second extracts the speed and position signal via comparing two different values of motor's current defined in two co-ordinates; while the third depends on estimating the motor's flux and use it to get the speed and position. The vector control is adopted to manage the drive dynamics. The detailed mathematical derivations for all system components are presented to facilitate the performance analysis. The theoretical base of each sensorless scheme is also described in detail. The target of the provided comparative analysis is to outline the weakness and strength points of each adopted sensorless schemes while estimating the speed and rotor position for a wide operating speed range. The judgment is measured in terms of the speed and rotor position estimation errors and the dynamic response as well. The performance evaluation process is carried out using MATLAB/Simulink software in which all system parts are simulated using their mathematical models. The findings from the study state that when it comes to dynamic speed behaviour, the voltage-based sensorless technique dominates, while the current-based sensorless approach gives stability in speed estimate priority. Alternatively, the third adopted sensorless scheme offers an acceptable high-speed performance and respectable performance at lower speeds. Statistically, it is found that the voltage-based estimation technique gives respectively lower speed and position estimation errors with percentages of 35% and 10% lower than their values under the current-based estimation technique, and with percentages of 35% and 30% lower than their values under the third adopted scheme.

An analytical fast field solver for surface permanent magnet co‐axial magnetic gears

AbstractA mathematical model of co‐axial magnetic gears is given for the prediction of magnetic field distribution and the magnetic forces. The modelling approach is based on the separation of variables method (SVM), Sturm–Liouville problem, and spectral analysis. This method is computationally more efficient and has the ability to account for finite permeability of magnetic saliency. An finite element method (FEM) validation is performed for a case study, and the results are observed to be almost matched. The computational time of the analytical model has been almost in the same order of that of the FEM for a specified rotor position (both in a matter of a second or less); however, when 100 number of rotor positions were accounted in the simulation, the computational time of FEM was increased to 82 s, while the computational complexity of SVM was almost unaffected.

Development of an adjustable patient-specific rigid guide to improve the accuracy of external ventricular catheter placement.

The most common method for external ventricular drain (EVD) placement is the freehand approach, which has reported inaccuracy rates of 12.3%-44.9%, especially in the case of altered ventricular anatomy. Current assistive devices require added time or equipment or do not account for shifted ventricles. To improve the accuracy of emergent EVD placement in the setting of altered ventricular anatomy, the authors designed a patient-specific EVD (PS-EVD) guide. The PS-EVD guide has a tripod base and a series of differently angled inserts that lock in place at multiple rotational positions, allowing for numerous insertion angles. For testing, the authors designed a 3D-printed phantom skull with a gelatin brain analog containing ventricles simulating normal and altered ventricular anatomy. Low-resolution CT scans of the phantom were used to calculate the insertion angle in relation to the standard perpendicular entry. The corresponding insert at the correct rotational position within the base unit was positioned over the entry point on the phantom, and the catheter was inserted. Accuracy was evaluated with repeat CT scans. With normal ventricular anatomy, as well as abnormally shifted ventricles, proper use of the PS-EVD guide led to accurate catheter insertion into the ventricle in trials, as confirmed on coronal and sagittal CT images, including cases in which a perpendicular trajectory, such as with the Ghajar guide, was insufficient. The PS-EVD guide allows consistent and accurate EVD placement in phantom skulls with both normal and altered ventricular anatomy. Further trials comparing this device to the freehand approach are required.

Noise reduction in small wind turbines with optimized serrated blades

This study employs a comprehensive combination of experimental and numerical methodologies to delve into the aeroacoustic attributes of a small horizontal axis wind turbine with optimized blades. The experimental investigation is conducted within a semi-anechoic chamber, where both original and optimized geometry models are meticulously positioned to measure the sound pressure levels across a range of rotational speeds and positions. In parallel, the numerical simulations employed the large eddy simulation, complemented by the Ffowcs Williams–Hawkings analogy, facilitating detailed examinations of both aerodynamic and acoustic aspects in the original and optimized modes. The findings reveal a subtle enhancement in aerodynamic performance with the optimized serrated blade configuration when compared to the original. Nevertheless, the reduction in noise levels within the frequency domain was remarkable, culminating in an impressive overall sound pressure reduction of about 10 dB. Furthermore, an intriguing observation emerged from noise measurement in acoustic room: the noise production experiences a marked escalation as the turbine rotational speed intensifies, particularly within the downstream domain. The lateral noise level is found to be lower compared to the axial direction and the reduced noise emission for the serrated optimized blade is more dispersed in the plane of rotation than the original blade, which was pointed out to be nearly uniform. The results provide valuable insights into the interplay of aerodynamics and aeroacoustics in the context of small wind turbines with optimized blades.

Effect of Hall Errors on Current and Rotor Position of Robot Joint Motors

Effect of Hall Errors on Current and Rotor Position of Robot Joint Motors

Influence of DC-Field Current on Short-Circuit Current in Variable Flux Reluctance Machine

DC-field windings of variable flux reluctance machine are wound on the same teeth with armature winding, which increases the short-circuit probability among the armature and field windings. Therefore, in this article, the various short-circuit faults of single phase, phase-to-phase, single field and phase-to-field are illustrated, and the influence of dc-field current on short-circuit current (SCC) and braking torque (BT) with consideration of initial rotor position are investigated. The SCC with dc-field current is analytically established, where the SCC and BT in transient and steady states are analyzed. The maximum SCC and BT are comprehensively compared by finite element method. It is found that the influence of dc-field current on the SCC and BT under transient conditions can be neglected. However, when the machine under un-saturated conditions, the SCC in steady states is associated with the saturation of iron core, i.e., the more saturated of the core excited by dc-field current in prefault, the smaller of the SSC in post fault. Both the SCC and BT are accompanied by the 12/14-pole VFRM prototype experimental verification.

Research on a Sensorless ADRC Vector Control Method for a Permanent Magnet Synchronous Motor Based on the Luenberger Observer

A sensorless vector active disturbance rejection control (ADRC) method for permanent magnet synchronous motors (PMSM) utilizing a Luenberger observer is presented. This method aims to address the challenges associated with weak active disturbances, substantial steady-state speed amplitude fluctuations, and difficulty in achieving a balance between overshoot and speed control in the sensorless PMSM control system. Mathematical models of the Luenberger observer and the ADRC were analyzed, leading to the proposal of a second-order ADRC control method based on the Luenberger observer. A mathematical model of the permanent PMSM has been introduced. Additionally, the necessary conditions for the convergence of the Luenberger observer were derived and examined. The allowable range of error feedback gain values was determined, and rotor position data were acquired using a phase-locked loop. The principle of the ADRC was analyzed, and the ADRC simulation results, along with the PI simulation results, were detailed. When the target speed is 1000 r/min, the steady-state error and load disturbance resistance of the ADRC control method outperform those of the PI control method. Finally, the control method was experimentally tested on an STM32F4 chip, demonstrating the advantages of small steady-state error and strong active disturbance ability.

Sensorless control of permanent magnet synchronous motor based on improved sliding mode observer

Aiming at the problems of chattering and low accuracy of rotor position observation in traditional sliding mode observer sensorless control of permanent magnet synchronous motor, an improved sliding mode observer sensorless control method is proposed. First, the sigmoid function is used to replace the traditional switching function, which can effectively improve the chattering problem of the sliding mode observer. Then, an adaptive back electromotive force observer is designed to avoid the use of low-pass filter and phase compensation and reduce the high-frequency harmonics in the back electromotive force estimation. Finally, the speed and rotor position information are obtained by improving the phase-locked loop, and the fundamental harmonics caused by the inverter nonlinearity are suppressed. The simulation and experimental results show that the improved sliding mode observer can effectively weaken the chattering problem of the system, and improve the position observation accuracy and the robustness of the system.

Design of Fractional-Order Non-Singular Terminal Sliding Mode Observer Sensorless System for Surface-Mounted Permanent Magnet Synchronous Motor

A new sensorless speed control system for a fractional-order terminal non-singular sliding mode surface-mounted permanent magnet synchronous motor is proposed. The fractional terminal non-singular sliding mode surface, which can converge in finite time, is designed by combining the fractional-order control theory with the terminal attractor concept. Then, a new control rate is proposed to reduce system buffeting. Secondly, an adaptive back electromotive force filter is designed to reduce the harmonics in the sliding mode function estimation and improve the observation accuracy. In addition, the theoretical analysis of the designed system proves that the system can converge in a finite time. Then, a fraction-order phase-locked loop with variable factors is designed to make the system more capable of tracking the rotor. Finally, a simulation and experiment platform is built, and a comparison experiment is carried out, which proves that the designed algorithm has a stronger rotor position tracking ability and a better dynamic performance of the system.

Fuzzy control allocation of a positionable rotor quadrotor based on log‐barrier optimization and propulsion system fault toleration

AbstractHerein, a control system and a fault tolerance method for the rotor positionable quadrotor are proposed. Quadrotors that have a variable structure are made for different purposes. The rotor‐positionable quadrotor studied here, is a type of drone with a variable structure that has the ability to change the position of its rotors linearly along the axis of each arm. It can be seen that this capability can improve the drone robustness against disturbances and faults in comparison with regular quadcopters. Due to the over‐actuated dynamics of this type of quadrotor, the control allocation scheme based on log‐barrier optimization is employed to obtain the position and speed of each rotor. In this study, it is experimentally shown that rotor positioning not only reduces power consumption but also increases roll and pitch control inputs magnitude. Furthermore, when a fault occurs as a decrease in rotor speed, a fuzzy method is proposed to position the rotors which tolerates the fault. Finally, numerical simulations and experimental tests verified that rotor positioning can bring more robustness, reduction in power consumption, and fault tolerance in some rotor faults capabilities for quadrotors.

Experimental Identification of a Coupled-Circuit Model for the Digital Twin of a Wound-Rotor Induction Machine

The development of monitoring and diagnostic methods for electrical machines requires the use of transient models capable of operating in real time and producing signal signatures with high precision. In this context, coupled-circuit models offer numerous advantages due to their speed of execution and accuracy. They have been successfully employed to create real-time digital twins of electrical machines. The main challenge of this modeling method lies in the preparation of the model, which involves numerous preliminary calculations and takes time to identify all its parameters. This is particularly due to the variation in inductances based on the rotor position. To determine these inductance values with great precision, the classical approach involves using finite-element field calculation software. However, the computation time quickly becomes an issue due to the large number of values to calculate and simulations to perform. This article introduces an innovative experimental approach to identify a coupled-circuit model and develop a digital twin of a wound-rotor induction machine. This method relies solely on simple electrical measurements and tests conducted at extremely low rotation speeds (1 rpm) to obtain inductance variations as a function of the rotor position. By employing this technique, the need for analytical models or finite-element field calculation simulations, which typically require precise knowledge of the machine’s geometry and materials, is circumvented. The measurement processing employs optimization methods to extract the inductances as a function of the rotor position, which are then used as input data for the coupled-circuit model. The final parameters are specific to each machine and replicate all its manufacturing imperfections such as eccentricity and geometric or winding defects. This experimental identification method significantly enhances the model’s accuracy and reduces the usually required preliminary calculation time in a finite-element-based identification process.

Turbulent Airwake Estimation from Helicopter–Ship Wind-Tunnel Data

This paper presents a stochastic approach for modeling the turbulent airwake suitable for real-time simulation of the helicopter–ship dynamic interface. This approach relies on the measurements of unsteady loads collected during a wind-tunnel test campaign with a scaled helicopter operating over the deck of simple frigate shape 1. Power spectral densities of the measured aerodynamic loads combined with the estimated frequency response functions are used to find, through an optimization algorithm, a model of airwake spectra over the range of frequencies which mainly affects the pilot workload during shipboard operations. Then, a set of autoregressive filters is designed for every particular rotor position and wind-over-deck condition, so that when driven by white noise, the spectrum of the output will reproduce those obtained from the optimization. This approach is applied to three different tested wind directions and three rotor positions by implementing the autoregressive filters into the multibody model of the experimental rotor. Frequency response analysis of the aerodynamic loads demonstrates that the turbulent airwake model obtained from the experimental data can predict the unsteadiness of loads comparable to those measured in the wind tunnel across the bandwidth of interest for pilot activities. The identified airwake models could be applied to a full-scale model to simulate the unsteady loads effectively experienced by the helicopter during a ship landing flight.

Proposed Fault Detection Algorithm with Optimized Hybrid Speed Control

The Brushless DC (BLDC) motor is a common choice for industrial applications, particularly in the automotive sector, owing to its high efficiency and robust capabilities. To detect the position of the motor rotor, hall-effect sensors can be used, but these sensors may prevent the system from operating if they fail. Consequently, fault-tolerant control (FTC) has been proposed in several studies to ensure continuity of operation in the event of sensor failure. This paper proposes an innovative method of fault detection in the hall effect sensor for a BLDC motor using combinatorial functions. This paper proposes an innovative method of hall-effect sensor fault detection for a BLDC motor using combinatorial functions. For the speed control of the BLDC under study, a hybrid adaptive neuro-fuzzy inference control (ANFIS) is implemented. In addition, the FTC signal reconstruction technique adopted has been improved to achieve motor start-up despite a fault in one of the sensors, thanks to well-defined fault detection algorithms. Simulation results are presented for each sensor failure case to test the effectiveness of the method used.

Extending Context Window in Large Language Models with Segmented Base Adjustment for Rotary Position Embeddings

In the realm of large language models (LLMs), extending the context window for long text processing is crucial for enhancing performance. This paper introduces SBA-RoPE (Segmented Base Adjustment for Rotary Position Embeddings), a novel approach designed to efficiently extend the context window by segmentally adjusting the base of rotary position embeddings (RoPE). Unlike existing methods, such as Position Interpolation (PI), NTK, and YaRN, SBA-RoPE modifies the base of RoPE across different dimensions, optimizing the encoding of positional information for extended sequences. Through experiments on the Pythia model, we demonstrate the effectiveness of SBA-RoPE in extending context windows, particularly for texts exceeding the original training lengths. We fine-tuned the Pythia-2.8B model on the PG-19 dataset and conducted passkey retrieval and perplexity (PPL) experiments on the Proof-pile dataset to evaluate model performance. Results show that SBA-RoPE maintains or improves model performance when extending the context window, especially on longer text sequences. Compared to other methods, SBA-RoPE exhibits superior or comparable performance across various lengths and tasks, highlighting its potential as an effective technique for context window extension in LLMs.