Switching Algorithm Research Articles

Experimental Validation and Efficiency Analysis of Sensorless PR based 15PUC (fifteen level Packed U Cell) MLI for Commercial & Residential Applications with Novel Switching Algorithm

Experimental Validation and Efficiency Analysis of Sensorless PR based 15PUC (fifteen level Packed U Cell) MLI for Commercial & Residential Applications with Novel Switching Algorithm

Generalized Distribution Feeder Switching with Fuzzy Indexing for Energy Saving

The objective of this study is to analyze feeder loss minimization and load balance under given constrains. Effective methods are required for feeder switching/reconfiguration. Feeder switching is a mixed-integer large-scale combinatorial problem for optimization, not easily solvable with classical optimization techniques, especially involving a great number of switches. This paper proposes a fuzzy indexing algorithm for feeder switching, with membership functions defined for switches such as thermometers or indices. The optimal switches can be determined through fuzzy index operations. With membership functions defined, the developed method used numerical operations for indices instead of the “set” operation or the min-max operations of traditional fuzzy algorithms. The optimization problem becomes a simple numeric calculation instead of a large-scale sorting problem and is much faster than most algorithms. It greatly reduces the computation time and enhances efficiency, which is suitable for either planning or operation purposes. Many algorithms were tested with three typical examples chosen for illustration, including the “optimal” results with an exhausted search. It shows that the proposed algorithm is very effective and can balance the load to reduce the loss and costs in obtaining the solution.

Indoor and Outdoor Seamless Positioning Technology Based on Artificial Intelligence and Intelligent Switching Algorithm

Navigation and positioning is a new growth point of wireless services. And seamless positioning is the current development trend of navigation and positioning services. In view of the problems that dynamic handover cannot be performed during site movement, STA only selects the optimal AP according to the indication of received signal strength, and the handover delay is too long. This paper proposes a research on indoor and outdoor seamless positioning technology based on artificial intelligence and intelligent switching algorithm. The purpose is to study the influence of reducing the positioning data with too large error on the final positioning result. The method of this paper is to propose an intelligent switching algorithm and then discuss the research status and development direction of indoor positioning technology and outdoor positioning technology, respectively, and point out the switching methods between them. The role of these methods is to analyze the current situation of indoor and outdoor navigation technology, especially the development route of seamless positioning technology. It determines the strategy of integrating heterogeneous positioning systems to build a seamless positioning system to maximize the use of existing positioning system resources. This paper studies the design and implementation of the seamless positioning system through the simulation experiment of the intelligent switching algorithm and finally tests the system through the experimental vehicle. The online experiment results show that the system can achieve high positioning accuracy in indoor and outdoor environments, especially at its junction, and the positioning errors in all directions are within 0.2 m.

Sustainable photovoltaic based protective environment controlled farming technology as economy boosters for agro-sectors

In view of boosting the agro-economy of low-income group of farmers, a design initiative and its field validation for photovoltaic based protected environment-controlled farming technology (PV_PECFT) is important, especially for farms without access to the public electricity grid. This paper presents for the first time the PV_PECFT concept with adequate automation having three segments: (a) Agro-process automation embedded in a microcontroller with opto-isolated interfaced sensors with the functionality of managing boundary-based value-control. (b) Unique control algorithm for load-based strategic PV array switching and power control for minimized electrical and thermal losses by adapting add on modular hardware (AOMH) concept. It enables maximum power point operation for maximized energy yield from PV arrays inclined in opposite direction at the rooftop of a hut structure. (c) An energy equilibrium state monitoring index (E2SMI) based model is attempted for energy saving during inside climate control via opto-isolated Si-MOSFET based hardware against external non-linear variation of weather conditions. This PV_PECFT concept has been validated for 97 days; considering criteria of crop leaf area index comparison in the field tried experimental prototype and that in an open land field (1.44 to 1.58 times higher) and comes out with a low budget farming, yet high-tech, scalable technology for a targeted size of the farm with special focus on ease of operation and handling in cultivation.

A New Integrated Multilevel Inverter Topology for Renewable Energy Transformation

This paper presents a new three-phase integrated module multilevel inverter (IMMLI) with reduced component count which is suitable for low, medium and high voltage renewable energy systems. The proposed inverter is a resultant structure of a number of integrated module and each module is configured with a number of series connected basic blocks. Each block consists of a dc voltage source, a blocking diode and a semiconductor switch. A computational combination and summation among the dc sources from different blocks results in a high number of levels within the output voltage. This task is performed by controlling the switches equipping appropriate switching algorithm. Thus, a high level of output is obtained employing reduced number of components. Since the topology owns two degree of modularity, the total stress voltage (TSV) of the system is low and distributed among the switches. Hence, the proposed topology allows to be implemented in high power systems with reduced amount of costs. The inverter also offers enhanced efficiency, as the number of simultaneously conducting switch is low. Additionally, in order to operate the presented inverter with optimum ac power quality, a multi-carrier based level shifted PWM scheme is addressed in this paper. This paper also shows how to prepare balanced dc sources that are required to implement the inverter using high-frequency magnetic-link. The operating principle of the IMMLI is explained with the help of a fifteen level (15-L) single phase unit and its performance is evaluated in MATLAB/Simulink considering different conditions. Experimental validation is also presented to support the simulation results and to evaluate its superiority over the existing.

Optimal reconfiguration of distribution network based on deep fuzzy c-means clustering algorithm

This study examines the best distribution network reconfiguration to enhance distribution network safety and reduce active power loss. Distribution networks can be reconfigured using a deep fuzzy C-means (FCM) clustering method with the objective of the least amount of active power loss. By creating a novel framework, the size of the neural network is lowered by modifying the number of neurons in input layer. With the simulations tested on IEEE 33-bus distribution network, the outcomes of traditional approaches, such as the Branch-and-Cut and the switching algorithms, are contrasted with the simulation results. The comparative results clearly show advantages to employing the suggested framework for distribution network reconfiguration, such as a quick turnaround time far quicker than the alternatives. These characteristics demonstrate how well the suggested paradigm may be applied to distribution network real-time reconfiguration.

Existence of hidden attractors in nonlinear hydro-turbine governing systems and its stability analysis

This work studies the stability and hidden dynamics of the nonlinear hydro-turbine governing system with an output limiting link, and propose a new six-dimensional system, which exhibits some hidden attractors. The parameter switching algorithm is used to numerically study the dynamic behaviors of the system. Moreover, it is investigated that for some parameters the system with a stable equilibrium point can generate strange hidden attractors. A self-excited attractor with the change of its parameters is also recognized. In addition, numerical simulations are carried out to analyze the dynamic behaviors of the proposed system by using the Lyapunov exponent spectra, Lyapunov dimensions, bifurcation diagrams, phase space orbits, and basins of attraction. Consequently, the findings in this work show that the basins of hidden attractors are tiny for which the standard computational procedure for localization is unavailable. These simulation results are conducive to better understanding of hidden chaotic attractors in higher-dimensional dynamical systems, and are also of great significance in revealing chaotic oscillations such as uncontrolled speed adjustment in the operation of hydropower station due to small changes of initial values.

A coupled Eulerian interface capturing and Lagrangian particle method for multiscale simulation

A new Eulerian–Lagrangian coupling on a staggered fluid mesh is proposed to simulate multiscale atomization. This coupling relies on a sharp interface capturing method (ICM) to transport the resolved fluid structures and a Lagrangian tracking algorithm to model the under-resolved Eulerian droplets. The Lagrangian droplets momentum is spread to the source terms of the incompressible fluid momentum equations through a spatial filtering operation, and the flow velocity around the Lagrangian droplets is corrected to account for their local flow disturbance. This allows accurate transport of Lagrangian droplets that are both smaller and larger than the fluid mesh spacing. The implementation of the algorithm for switching from and to Eulerian toward Lagrangian framework is discussed, along with criteria validating a transformation. Then the Eulerian–Lagrangian coupling is applied to several test cases from the literature, and is compared to our in-house pure ICM solver on the atomization of a liquid jet. The results show that the Eulerian–Lagrangian coupling improves the physical analysis of the atomization, and achieves more accurate results for poorly resolved droplets.

A New Topology for Electric All-Terrain Vehicle Hybrid Battery Systems Using Low-Frequency Discrete Cell Switching

This article presents an investigation into the feasibility of a novel discrete-switched topology for an electric all-terrain vehicle (e-ATV) hybrid battery system (HBS) that avoids expensive and bulky dc–dc converters using a simpler discrete-switched structure together with an intelligent low-frequency switching algorithm. Hardware is simplified at the expense of more complex control. The algorithm switches cells in and out of series strings, based on their state of charge relative to other cells in the pack and the power being drawn from the pack. The principles are demonstrated using a simulated model combining lithium-titanate-oxide (LTO) and lithium-iron-phosphate (LFP) cells together in an e-ATV battery pack. Despite its simplicity, the intelligent switching algorithm successfully allocates power to different elements of the battery and ensures that the state of charge remains broadly balanced throughout discharge, with the pack ending up in good balance: the LFP cells are in balance to within 0.01% of each other and the LTO cells within 0.1% of each other. While the article focuses on the essential feasibility of the concept, it also identifies future research for including thermal effects, uncertainties in state estimation, cell aging and nonuniformly, and consideration of other powertrain components, for example, motor and power electronics.

Automated clustering and switching algorithms applied to semantic verbal fluency data in schizophrenia spectrum disorders

ABSTRACT In the cognitive assessment of Schizophrenia Spectrum Disorders (SSD), the standard scoring method for Verbal Fluency (VF) tasks is the number of correct words produced. Finer-grained measures, such as the size of semantic clusters and the number of transitions between them, have been proposed to characterise the cognitive functions involved, but results based on human ratings are heterogeneous. The objective of this study was to develop a computational procedure based on Vector Space Models (VSMs) to assess the predictive ability of these fine-grained measures for class membership in SSD. A semantic VF task was administered to thirty-five people with SSD and a matched group of healthy participants, and their VF productions were characterised manually and using a set of ad-hoc algorithms. Computational estimates consistently showed higher predictive accuracy than models built on VF measures computed by a human rater and models built on the sole total number of words.

An Online Condition-Based Parameter Identification Switching Algorithm for Lithium-Ion Batteries in Electric Vehicles

Safely and reliably managing the lithium-ion batteries in electric vehicles for daily operations relies on accurate state-of-charge estimation. To pursue accurate state-of-charge estimation, battery electric circuit model-based algorithms demand minimized modeling error from accurate parameter identifications. Typical online parameter identification algorithms: least square fitting approach and recursive least square fitting are commonly adopted but have their limitations and issues with continuously providing accurate identification results. To overcome their problems and utilize their strengths, this paper proposes a condition-based parameter identification switching algorithm. The proposed algorithm accurately and robustly identifies the lithium-ion batteries' parameters based on the battery data condition and the adoption of Bollinger bands. By minimizing the modeling error, the accuracy of the state-of-charge estimation is thus improved. The electric vehicle simulation results indicate that the proposed algorithm can improve the parameter identification accuracy by an average of 70.80% and 44.95% reduction in the mean absolute parameter identification error, compared to typical least square fitting and recursive least square fitting approaches. With the help of the minimized modeling error, the state-of-charge estimation accuracy can thus be improved, rendering an average of 62.44% and 21.49% improvement.

Controlling the dynamics of a COVID‐19 mathematical model using a parameter switching algorithm

In this paper, the dynamics of an autonomous mathematical model of COVID‐19 depending on a real bifurcation parameter is controlled by the parameter switching (PS) algorithm. With this technique, it is proved that every attractor of the considered system can be numerically approximated and, therefore, the system can be determined to evolve along, for example, a stable periodic motion or a chaotic attractor. In this way, the algorithm can be considered as a chaos control or anticontrol (chaoticization) algorithm. Contrarily to existing chaos control techniques that generate modified attractors, the obtained attractors with the PS algorithm belong to the set of the system attractors. It is analytically shown that using the PS algorithm, every system attractor can be expressed as a convex combination of some existing attractors. Interestingly, the PS algorithm can be viewed as a generalization of Parrondo's paradox.

Research on the network handoff strategy based on the best access point name decision.

To improve the network switching performance and efficiency of mobile phone terminals and establish an efficient mobile communication network connection, this paper constructs the SDN+MPTCP+CP (Software Defined Network, Multi-Path TCP, and Mobile Terminal) mobile communication network model and designs a network switching algorithm with a preselected available access point name (APN) based on the potential game method. The constructed network model integrates a 5G mobile communication network, satellite communication, the SDN network, and the MPTCP multi-way communication technology. APN access point is preselected by using Kalman filtering theory, and dual problems are resolved with the Lagrange function. To determine the MPTCP sub-flow transmission path, the differential derivative calculation is introduced. The performance of the network switching strategy is evaluated based on the Jacobian matrix. Then, the game coefficient is designed, and the game function is calculated. A potential game balance point is found, and an updating strategy is formulated to determine the best APN access point. The simulation network model is constructed, and the parameters of the performance evaluation are defined to find the performance comprehensively. The experimental results demonstrated the extreme reliability, stability, and compatibility of the proposed algorithm.

Development of a Smart Static Transfer Switch Based on a Triac Semiconductor for AC Power Switching Control

Power system disruptions can be categorized as issues with the quality of electricity brought on by voltage sags, lightning strikes, and other system-related interferences. The static transfer switch (STS) has recently emerged as the most important technology for electric power transmission, distribution, and control systems to manage power supply during power system disruption issues, particularly in cost-effectively supplying power to critical loads and sensitive loads without interruption. In this paper, for the switching between the two AC sources during the voltage disruptions issue with low transfer time, a smart static transfer switch (SSTS) based on a digital switching algorithm and Triac semiconductor switch is proposed and experimentally tested. A digital switching algorithm based on online AC voltage sensing and zero-crossing detection is proposed and implemented inside a DSP MCU. The printed circuit board (PCB) of the proposed SSTS is designed and manufactured for the experimental performance investigation with different AC input voltage conditions. A comparative study based on the advantages and disadvantages of the proposed SSTS system with the previous works is also presented. A smart static transfer switch with a transition time of less than one cycle and a digital protection technique during fault conditions is obtained in this work.

A Novel Switching Algorithm to the Preferred Clock Skew Estimator Applicable for the PTP Case in the Fractional Gaussian Noise Environment

Recently, the same authors provided a switching algorithm for the preferred clock skew estimator appropriate for the precision time protocol (PTP) scenario. The algorithm chooses the one‐way delay (OWD) clock skew estimator for the Forward path or the Reverse path or the two‐way delay (TWD) clock skew estimator that has the best performance in the mean square error (MSE) perspective. However, the switching algorithm applies only to the Gaussian scenario. In a real system, the packet delay variation (PDV) can be characterized as an fractional Gaussian noise (fGn) process where the Hurst exponent parameter can also have values higher than 0.5. Thus, the Gaussian case‐switching algorithm may not apply in a real system where after a small set of PTP measurements, the switching algorithm should be able to switch effectively to the preferred clock skew estimator with the best performance in the MSE perspective. In this paper, the PDV is characterized as an fGn process where the Hurst exponent (H) is in the range of 0.5 ≤ H < 1. We estimate the unknown PDV variances and the Hurst exponent parameters of the Forward and Reverse paths. These estimated parameters are used for switching to the preferred clock skew estimator from the MSE perspective, even in the presence of asymmetry in the PDV or in the Hurst exponent parameters. We also detect and alarm for the unexpected load, cyber‐attack, or clock skew deviation that can occur in a real system.

Технологии и технические средства рекультивации залежных земель с регулированием уровня увлажненности почвы

An assessment of the technological feasibility of the tasks of involving fallow lands in agricultural circulation and increasing the fertility of agricultural land in the long-term period of economic activity is given. Insufficient information content of the use of yield maps for assessing the fertility of fields has been revealed. It is proposed to use maps of the relief of fields, which will allow establishing the dynamics of violation of the water-air regime of the soil. It is substantiated that in the process of involving fallow lands into circulation, it is required to introduce a technological operation of micro topographic analysis of the degree of soil moisture. An algorithm for switching on the field leveling operation (surface leveling of the field plane) using modern positioning systems has been developed. It was revealed that leveling the field with a laser level made it possible to reduce yield fluctuations by 20% within the cultivated area of the field and increase yield by 25‑30% (an example of sowing corn). Shortcomings of positioning accuracy with the use of laser and satellite positioning have been established. It is proposed to transfer digital information transmission modules to network clusters with the choice of the best digital data transmission channel by including an uninterrupted positioning module with digital data transmission over a 434 MHz and 864 MHz radio channel with a range of up to 600 meters to other digital information transmission modules of the vehicle positioning. A plan for the implementation of the concept of forming a digital field on the basis of a field experimental station of the RSAU-MAA named after C.A. Timiryazev, with the aim of creating a frontier for the sustainable development of closed life cycle technologies through the introduction of innovations using the multiplicative interaction of mechatronic systems and telematics for agro-industrial complex equipment

Universal Equivalent Model for Real-Time CPU/FPGA Co-Simulation of Hybrid Cascaded Multilevel Converters

Real-time simulation is important for ensuring the reliable operation of VSC-HVDC converters in power grids, particularly through the use of rapid control prototyping (RCP) and hardware-in-the-loop (HIL) based converter controllers. While real-time simulation is a common practice for modular multilevel converters (MMCs), it has been less frequently applied to the new class of hybrid cascaded multilevel converters (HCMCs). In this study, a universal equivalent model (UEM) is proposed for a range of HCMC topologies that combines accuracy and computational efficiency through the use of both CPUs and field-programmable gate arrays (FPGAs). The proposed UEM is derived using the hybrid five-level converter (H5LC), a compact, efficient, and fault-tolerant VSC within the HCMC family. The UEM relies on CPUs to simulate the main circuits and controls of the main converter, and utilizes FPGAs to calculate the instantaneous voltages of a large number of full-bridge submodules (FBSMs), flying capacitors, and DC-side pole capacitors. In addition, the FBSMs’ voltage-balancing and switching algorithms are implemented on the FPGAs. The proposed real-time CPU/FPGA-based H5LC-UEM is compared to an offline CPU-based detailed equivalent model to verify its accuracy.

Base Station Energy Management in 5G Networks Using Wide Range Control Optimization

The traffic activity of fifth generation (5G) networks demand for new energy management techniques that is dynamic deep and longer duration of sleep as compared to the fourth generation (4G) network technologies that demand always for varied control and data signalling based on control base station (CBS) and data base station (DBS). Hence, this paper discusses the energy management in wireless cellular networks using wide range of control for twice the reduction in energy conservation in non-standalone deployment of 5G network. As the new radio (NR) based 5G network is configured to transmit signal blocks for every 20 ms, the proposed algorithm implements withstanding capacity of on or off based energy switching, which in-turn operates in wide range control by carrying out reduced computational complexity. The proposed Wide range of control for base station in green cellular network using sleep mode for switch (WGCNS) algorithm toon and off the base station will work in heavy load with neighbouring base station. For reducing the overhead duration in air, heuristic versions of the algorithm are proposed at the base station. The algorithm operates based on the specification with suggested protocol-level to give best amount of energy savings. The proposed algorithm reduces 40% to 83% of residual energy based on the traffic pattern of the urban scenario.

EMeD: An Experimental Study of an Autonomous Wearable System with Hybrid Energy Harvester for Internet of Medical Things

We propose and experimentally validate a hybrid energy harvester embedded in a wearable system used to measure real‐time information, such as body temperature, heartbeat, blood oxygen saturation (SpO2), and movement (or acceleration) of human body in real time. This hybrid energy harvester, or in short eMeD, has a unique design that can improve the energy efficiency of the overall wearable system and extract more energy from ambient sources. Specifically, the wearable system is integrated with a hybrid photovoltaic‐radio frequency (RF) energy harvester as the power source to prolong its lifetime and reduce the dependence on battery energy. Experimentally, the current consumption of the wearable system with load switching and event management algorithm improved from 31 mA to 18.6 mA. In addition, the maximum conversion efficiency is 14.35%. The experimental results illustrate a sustainable and long‐term monitoring operation for Internet of Medical Things systems.

Timely and Accurate Bitrate Switching in HTTP Adaptive Streaming With Date-Driven I-Frame Prediction

In today's Internet, bandwidth dynamics are inevitable, and hence, the bitrate for live streaming applications should also be dynamically adjusted. However, in existing HTTP-based adaptive streaming (HAS), bitrate switching can only be performed at segment boundaries, making decisions unresponsive and often inaccurate. In this paper, we start from a close investigation on the impact of the segment length in HAS and accordingly present VHAS, an extension towards intelligent variable-length segmentation, which makes client-side decisions based on the massive amount of real-time information from the network and viewers. VHAS implements a smart trigger mechanism that balances accuracy and overhead for variable-length segmentation. We further develop an adaptive bitrate switching algorithm with data-driven I-frame prediction, which is tailored to individual viewers to minimize bitrate mismatches. We evaluate VHAS via extensive trace-driven simulations, and our results demonstrate that compared with state-of-the-art solutions, VHAS achieves 15% - 49% gains in QoE, with a noticeable bandwidth reduction of 37% - 57%.