Step Variation Research Articles

The Efficiency of The Gaver-Stehfest Method Transient Response of A Spiral Fin

In this study, a practical combined approach was applied by the Gaver-Stehfest method to examine the impermanent reaction of a spiral fin whose tip is isolated with the base tip exposed to changes in fluid temperature. The heat transmission of the fin under the stable temperature effect of the base is examined. The environment temperature is saved stationary and no heat source or sink is available. Results are improved for minor- and major -time worth when the base is exposed to the unit step variation form in temperature. The changes in heat flux and temperature at the base formed depending on the parameters that make up the spiral fin are graphically shown. The available numerical results show that it is fully consistent when compared with the literature.

Interacted collective intelligence based energy harvesting of centralized thermoelectric generation systems under non-uniform temperature gradient

A novel interacted collective intelligence (ICI) algorithm was developed in this work for maximum power point tracking (MPPT) of centralized thermoelectric generation (TEG) systems at non-uniform temperature gradients (NTG), upon which waste heat recovery ability can be considerably enhanced to enhance resources utilization efficiency. As centralized TEG system often exists numerous local maximum power points (LMPPs) under NTG, ICI is adopted to effectively seek global maximum power point (GMPP), upon which energy exploitation and utilization can be efficiently improved. To achieve a higher searching efficiency, a sub-optimizer with the best solution from all sub-optimizers is dynamically selected during each iteration to guide others. Although multiple sub-optimizers based ICI might lead to a higher computation complexity, a wider global search and more stable convergence can be achieved compared with single meta-heuristic algorithm. Four case studies, e.g., start-up test, step variation of temperature, stochastic temperature variation, and sensitivity analysis, validate the effectiveness and superiority of ICI. Simulation results indicate that ICI based MPPT can produce the largest energy with minimum power fluctuation under NTG compared against other five sub-optimizers, e.g., 109.24%, 112.54%, 108.61%, 107.10% and 116.75% to that of dragonfly algorithm (DA), firefly algorithm (FA), salp swarm algorithm (SSA), moth flame optimization (MFO) and multi-verse optimization (MVO) respectively in the step variation of temperature.

Wavelet neural learning-based type-2 fuzzy PID controller for speed regulation in BLDC motor

In brushless direct current (BLDC) motors, speed control is a prominent operation based on which these motors are widely used in higher-end industrial applications including robotics, aeronautics, disk drives, factory automation, consumer electronics, transport and military applications. A novel wavelet neural learning (WNL)-based type-2 fuzzy system controller is devised in this paper to accomplish effective speed control of the BLDC motor with the set specifications. The performance characteristics of the BLDC motor are simulated and analysed based on the wavelet neural learning-based type-2 fuzzy proportional–integral–derivative (PID) controller. This work employs wavelet neural learning to provide inputs to the constructed new type-2 fuzzy PID controller model, and this drives the BLDC motor mechanism. The gain values of the PID controller are tuned with the developed WNL-based type-2 fuzzy system to carry out most operational speed regulation process for the motor mechanism. The developed speed controller model for the BLDC motor is tested for its superiority by performing step variations of the input signal and also for load disturbances. In WNL, to derive the output a wavelet function is applied and this drives the operation of the type-2 fuzzy system PID controller and attains better gain values for speed control operation. The classic slime mould algorithm is used in this contribution to tune the weight coefficients during wavelet neural learning process and due to which the delayed convergence is controlled. Results attained during the simulation process prove the effectiveness and superiority of the proposed speed controller for the design specifications of the BLDC motor in comparison with the earlier literature contributions made.

A hybrid evolutionary algorithm for stability analysis of 2-area multi-non-conventional system with communication delay and energy storage

The integration of renewable energy with the grid is essential given the environmental and economic constraints. In this work, the dynamic performance of Automatic Generation Control (AGC) was studied with a dynamic steam turbine and renewable sources. A 2-area multi-non-conventional source (Thermal-Hydro-Solar-wind-Gas-battery storage) system with communication time delay (τ) is implemented with the proposed cascaded PID (C-PID) controller scheme. The parameters of the C-PID controller were tuned by a hybrid Improved Teaching Learning Based Optimization and Differential Evolution (hITLBO-DE).Root locus, Bode plot, and eigenvalue analysis were used to demonstrate the stability of the system. Various controllers (i.e. I, PI, PID, and C-PID) were implemented with the designed system under varying operating conditions of step (1% to 10%) and dynamic load variation (1%, ±1%). The C-PID controller is able to maintain a stable system response even for τ of 4 s. Finally, the obtained Amelioration (%) of 55.93%, 49.03%, and 72.84% for Over Shoot emphases the efficacy of the proposed C-PID controller and hITLBO-DE algorithm.

FPGA Based Tsunami Wave Propagation Calculator

The authors continue to use hardware acceleration to calculate tsunami wave propagation in a few seconds at modern PC. The goal of this work is to develop original implementation the FPGA-based algorithm for nested-grids computations of tsunami wave propagation. The FPGA-based Calculator, for regular grid has been proposed and numerically tested earlier. Use of the nested grid approach makes it possible to calculate wave propagation almost until the shore line. Numerical tests are based on the real digital bathymetry at southern part of Japan. Mesh step variation of the gird is from 180 m to just 7 m. Realistic shape of the initial sea surface displacement at tsunami source was used. The detailed distribution of wave height maxima around and inside the Onahama port have been issued as a result of tsunami generated by a model source located along the Japan deep-water trench. The superfast FPGA calculator provides an opportunity to obtain the calculated wave parameters inside ports and harbours even before arrival of tsunami wave.

Integrated predictive control and fault diagnosis algorithm for single inductor-based DC-DC converters for photovoltaic systems

PurposePower converters are an integral part of the energy conversion process in solar photovoltaic (PV) systems which is used to match the solar PV generation with the load requirements. The increased penetration of renewable invokes intermittency in the generated power affecting the reliability and continuous energy supply of such converters. DC-DC converters deployed in solar PV systems impose stringent restrictions on supplied power, continuous operation and fault prediction scenarios by continuously observing state variables to ensure continuous operation of the converter.Design/methodology/approachA converter deployed for a mission-critical application has to ensure continuous regulated output for which the converter has to ensure fault-free operation. The fault diagnostic algorithm relies on the measurement of a state variable to assess the type of fault. In the same line, a predictive controller depends on the measurement of a state variable to predict the control variable of a converter system to regulate the converter output around a fixed or a variable reference. Consequently, both the fault diagnosis and the predictive control algorithms depend on the measurement of a state variable. Once measured, the available data can be used for both algorithms interchangeably.FindingsThe objective of this work is to integrate the fault diagnostic and the predictive control algorithms while sharing the measurement requirements of both these control algorithms. The integrated algorithms thus proposed could be applied to any converter with a single inductor in its energy buffer stage.Originality/valuelaboratory prototype is created to verify the feasibility of the integrated predictive control and fault diagnosis algorithm. As the proposed method combine the fault detection algorithm along with predictive control, a load step variation and manual fault creation methods are used to verify the feasibility of the converter as with the simulation analysis. The value for the capacitors and inductors were chosen based on the charge-second and volt-second balance equations obtained from the steady-state analysis of boost converter.

A Nonlinear Model for the Rapid Prediction of the Magnetic Field in Eccentric Synchronous Reluctance Machines

This article introduces a novel numerical model for the fast characterization of concentric and eccentric synchronous reluctance motors (SynRMs) used in electric vehicles (EVs) applications. Regarding the high impact of the air gap and permeance function on the modeling accuracy, a step variation function is used to consider the flux barriers' effect on the air gap. Then, different types of eccentricity, including static, dynamic, and mixed eccentricity, are modeled. Besides, this model considers the magnetic saturation and the stator slots effect. Numerical computation for the motor inductances is applied to avoid any approximation in the permeance function. The air-gap flux density, electromagnetic torque, and radial force on the rotor are then calculated. This model can be used for the preliminary design of SynRMs to analyze the motor performance in different conditions and accelerate the design procedure. The model is simply adjustable to different configurations. For instance, a four-pole single-layer distributed winding machine with 36-slot and three-flux barriers per pole is investigated. In order to verify the proposed model, the obtained results are compared with finite-element analysis (FEA) and experimental tests. The accuracy of the proposed model for eccentricities up to 30% is 98%, and for higher degrees, it is about 95%.

Synthesis and comparative analysis of three model-based observers for normal load and friction estimation in intelligent tyre concepts

Recently, the growing trends towards autonomous driving and full automation of terrestrial vehicles have intensified the need for intelligent and interconnected systems to collect and communicate reliable data in real-time. Since the tyres represent the primary sensing system between the vehicle and the ground, it comes natural to designate them to acquire information about their interaction with the road. Intelligent or smart tyre technologies can, indeed, be used to estimate both vehicle’s performance and environmental conditions, leading to handling, NVH and comfort improvements. Inspired by some encouraging results found in previous works, in this investigation we present three model-based estimators to detect the forces acting in the contact patch for an intelligent tyre. The underlying mathematical foundation is the Flexible Ring Tyre Model (FRM), which is able to describe the in-plane dynamics of intelligent tyre systems. More specifically, it represents the tyre treadband by means of a flexible ring restrained at its mean radius by a viscoelastic foundation. Due to its relatively simplicity, the FRTM allows to obtain a closed-form solution for the treadband displacements, accelerations and circumferential strain, whilst being accurate enough to capture all the relevant phenomena concerning the tyre dynamics. The governing Partial Differential Equations (PDEs) of the system are reduced to a set of coupled Ordinary Differential Equations (ODEs) by performing the Fourier series expansion. An optimal observer is then designed based on the Unscented Kalman Filter to account for the nonlinearities which arise when the vertical load acting on the tyre and the friction coefficient are included in the augmented state space representation. The three different technologies considered in this study are: strain, displacement, and acceleration-based intelligent tyres. All of them are shown to be capable of estimating the quantities of interest – the actual state of the system, the normal force and the adhesion coefficient – with high accuracy in very short times. Furthermore, the robustness of the proposed approach is validated by considering a step variation in both the vertical load and the available friction. The performances of the observers are finally compared by using the RSS and MSE indices.

Modeling of Mechanical Properties and High Temperature Wear Behavior of Al7075/SiC/CRS Composite Using RSM

The study focuses on preparing hybrid composites with aluminium alloy strengthened with solid waste Crushed Rock Sand (CRS) and SiC through the stir casting process. The weight portion of reinforcement is diverse from 0 to 6% with a step variation of 3%. The mechanical properties such as hardness, ultimate tensile strength, impact strength, flexural strength, density, and porosity were investigated on prepared composites at room temperature. Central composite design-based response surface methodology (RSM) was espoused for computing and optimizing of the weight percentage of reinforcements considering mechanical properties as responses. An arithmetical model was developed to predict the mechanical properties and the adequacy of the model was verified using analysis of variance (ANOVA). The wear behavior associate with the composite is investigated at 28˚C and 350˚C. The specific wear rate and coefficient of friction of all samples shall be correlated with the above-mentioned temperature state. The maximum density of 2.766 g/cc is recorded for a sample with 3% wt. of SiC. The level of improvement in hardness, tensile strength, impact strength, and flexural strength is 59.7%, 45.9%, 16.9%, 58.7% relative base alloy. The specific wear rate, frictional force, and coefficient of friction decrease with elevated temperature due to the creation of oxide films. The depth and width of grooves at elevated temperatures are smaller.

A New Single-Stage 48-V-Input VRM Topology Using an Isolated Stacked Half-Bridge Converter

A buck-derived transformer-isolated converter topology has been proposed in this article for the single-stage 48-V voltage regulator module (VRM) application. The proposed converter uses a switched-capacitor voltage divider derived stacked half-bridge circuit in the primary side of the transformer. This simplifies the transformer structure and reduces device voltage ratings compared to the conventional half-bridge or a full-bridge circuit. Detailed circuit operation, analysis, and design of the proposed converter are presented. Further circuit modification is proposed to avoid unequal average inductor current sharing due to unequal resistances of the inductors in the secondary-side current doubler rectifier and consequent load-dependent dc shift in the transformer magnetizing current. An averaged small-signal ac equivalent circuit model of the converter is derived and validated against SIMPLIS simulation results. Finally, experimental results from a GaN device-based 45-A laboratory prototype demonstrates a maximum efficiency of 92.7%, which is higher than that of the state-of-the-art solution for the selected specifications, and exhibits faster dynamic response against load step variations.

The density-speed correlated mesoscopic model for the study of pedestrian flow

In this study, we developed a mesoscopic evacuation model driven by the density-speed correlations. In this model, the evacuation space is discretized into cells of multiple sizes, and the dynamic field method is extended into the mesoscopic scale. Psychological impatience was introduced to calculate the dynamic field. Instead of tracking individual movement, this approach directly computed the dynamic changes of crowd density in cells. To demonstrate the feasibility of this model, we firstly applied it to a typical scenario (i.e., a square room with a single exit) and conducted a parameter sensitivity study of time step and the impatience level of pedestrians. The simulation results indicated that the mesoscopic model is insensitive to the time step variations. Compared with the case without considering congestion degree, the dynamic method could shorten the evacuation time because the entire exit can be fully utilized. The model makes it possible to acquire key information (e.g., bottleneck areas) directly from the dynamic density map. We used commercial software Pathfinder to evaluate the model. Results showed that the mesoscopic model leads to a slower and smoother evacuation process. Moreover, we also conducted evacuation experiments to evaluate this model in a classroom under single exit and two exits condition. The comparisons revealed that the numerical results in low impatience level agree well with the experimental results in terms of evacuation time and the number of pedestrians choosing each exit. This study shows the potential of this model for predicting evacuation processes.

Transient Thermodynamic Modeling of Air Cooler in Supercritical CO2 Brayton Cycle for Solar Molten Salt Application

Abstract Supercritical carbon dioxide Brayton power cycle is getting commercially attractive for power generation due to numerous advantages like zero water usage, compactness, low environmental emission, and potential to reach high thermal efficiency at lower costs. A typical recuperated closed cycle consists of three heat exchangers (main heat exchanger, cooler, and recuperator) and two turbomachinery (turbine and compressor). Rapid changes in ambient temperature, operating loads, start-ups, and shutdowns affect the performance and operation of the turbomachinery and heat exchangers. The purpose of this research article is to study the thermodynamic parameters of the air cooler during transient operations by running dynamic simulations. Magnitude of change in carbon dioxide temperature due to change in air temperature is calculated. The simulation is a setup by having a steady-state design of 100 MWe cycle with operating temperature of 700 °C and pressure of 250 bar. Dynamic simulations are done using lms amesim. Transients studied in this article include: (i) step variation, (ii) standard variation, and (iii) linear variation of air temperature. This study thus serves as a framework to develop a design and control basis governed by transient scenarios.

An Experimental Transient Response of a Heat Exchanger with the Al2O3/Water Nanofluid Mass Flow and Temperature Step Variations

Experimental study on using nanofluid in a cross-flow minichannel heat exchanger (MICHX) to investigate its transient behavior was completed. Step changes of temperature and flow rate in the hot liquid were applied and the dynamic performance of the heat exchanger was analyzed. Results of nanofluid were compared to water and demonstrate an enhancement of 19% in heat transfer when using 2.5 wt% concentration Al2O3/water nanofluid. Parameters such as the transient effectiveness, heat balance, response time, and outlet temperatures of both liquid and air were also studied. The empirical correlations are developed for the temperature and mass flow step variations in a MICHX to predict the hot fluid outlet temperature in the dimensionless parameters. Nanofluid showed shorter response time for temperature and mass flow step changes compared to water. The outcome of this work is of interest to designers for process control, thermal testing, characterization, and performance enhancement of compact heat exchangers.

Second-order sliding mode voltage-regulator for improving MPPT efficiency of PMSG-based WECS

Driven by the rapidly growing use of wind power, the maximum power extraction of wind energy conversion systems (WECS) has become a significant issue. However, due to the stochastic nature of the wind, employing a nonlinear controller to provide a good tracking performance can be a viable option. In this study, a voltage mode Second-Order Sliding Mode Controller (SO-SMC) is proposed to capture maximum power from the WECSs. Optimum voltages to track are determined via a mechanical sensorless maximum power point tracker (MPPT) approach and these are transferred to the controller. In the proposed method, second-order surface is based on PID type sliding surface. The voltage-mode SO-SMC structure has not been implemented before as a voltage regulator for PMSG-based WECSs consisting of Rectifier and Boost Converter (BC). It is guaranteed that the system can be operated at maximum power point for all wind conditions thanks to the switching of the BC with only a control signal produced by the controller. The proposed method is validated by two different scenarios with different behaviors, that are realistic and step change wind speed profiles ranging from 5 m/s to 12 m/s. In addition, a conventional sliding mode (C-SMC) voltage regulator is designed and performance comparisons are made at these wind speed profiles in terms of output voltage fluctuation, steady-state error and maximum captured average power in steady-state and MPPT efficiency. From these results, it is proven that the proposed controller has a superior performance and it increases efficiency in the extraction of maximum power from WECS with the fast and robust voltage tracking. While MPPT efficiency was increased up to approximately 0.7% for the wind speed profile having the step variations, an increase up to about 1.05% was observed for the realistic wind speed profile.

Transient modelling and simulation of gas turbine secondary air system

The behaviour of the jet engine during transient operation and specifically its secondary air system (SAS) is the point of this work. This paper presents a methodological approach to develop a fast, one-dimensional transient platform for preliminary analysis of the flow behaviour in gas turbine engines secondary air system. For this purpose, different elements of the system including rotating chamber, pipe, turbine blade cooling, orifice, and labyrinth seal are modelled in a modular form. The validity of the developed models for each component is checked against experimental/publicly available data. Then, using a flow network simulation approach, the secondary air system of a two-spool turbofan engine is modelled and simulated in transient mode. The coupling effect between volume packing and swirl are considered in the simulation, under two pre-defined scenarios for step and scheduled boundary condition variations. In the step-change scenario, the boundary conditions are changed instantly to represent the flow behaviour of the SAS under extreme operating conditions (i.e. shaft fracture, flameout, etc.). In the scheduled scenario, the boundary conditions vary linearly with time to represent the performance of the SAS under normal operating conditions (i.e. acceleration and deceleration). The key findings include the fact that, under normal engine operation, the flow in the SAS varies smoothly and converges much faster than the primary flow by around one magnitude. Thus, it is reasonable to use steady-state SAS model to simulate SAS flow behaviour under these conditions. However, under extreme conditions (e.g. flameout), which could induce an abrupt change in the primary airflow properties (pressure, temperature), reverse airflow or choking conditions in SAS may be observed. This could result in a malfunction of the SAS, inducing further damages to the engine.

Plug in electric vehicle based multi-area renewable energy system for Automatic Generation Control

The work presented proposes a combination of a quick and reliable controller for the 2-area thermal system with the plug-in electric vehicle. For controlling and normalizing the system output, controlling the rotational frequency of the generator is an effective technique. A multi-constrained function is effective but the new objective function formulated is further effective and has been used in the optimization process with Intelligent Water Drops (IWD) algorithm for tuning the controllers. The performance with nPID controller in the proposed system has been compared to structures such as PID and PI for validation of the effectiveness with step and dynamic load variation. Statistical analysis such as Analysis-of-variance (ANOVA) is also performed. The work is extended by integrating wind turbines and tested with a variation of 10% in step loading and ±5% in dynamic loading of 120/80 seconds for either area. A significant improvement in response time is witnessed.

Energy optimization of an electric car using losses minimization and intelligent predictive torque control

Autonomy is considered an important criterion that characterizes the performance of electric vehicles. It is represented by the distance that could be traveled by a fully electric vehicle which mainly depends on several parameters such as the vehicle model, type of battery, type of motor, etc. In this context, to improve the autonomy of electric vehicles, this paper represents an optimization study for the electric motor based on two contributions. The first devise an energy optimization algorithm to reduce the motor losses by calculation of the stator flux reference according to the electromagnetic torque and the rotation speed. The second is concerned with controller parameters adjustment using the Particle Swarm Optimization (PSO) technique to improve the efficacy and robustness of the drive. The performance of this strategy is evaluated in terms of torque, flux ripples, and transient response to step variations of the torque control. A comparative study of the designed PI controllers based on PSO with four other control algorithms and tuning methods is established in order to prove the efficiency of PI_PSO. The analysis, modeling, and simulation results are presented to verify the validity of the proposed overall optimization study.

Greedy search based data-driven algorithm of centralized thermoelectric generation system under non-uniform temperature distribution

The generation efficiency of thermoelectric generation system is relatively low, thus how maximize its power production is of great importance. This paper designs a novel greedy search based data-driven method for centralized thermoelectric generation system to achieve maximum power point tracking under non-uniform temperature distribution. In order to effectively distinguish the local maximum power points and the global maximum power point under non-uniform temperature distribution, greedy search based data-driven employs a two-layer feed-forward neural network to accurately fit the curve between the power output and the controllable variable based on the real-time updated operation data. Based on the approximation curve, a greedy search is designed to efficiently approach the global maximum power point from a shrinking search space. Cases studies such as start-up test, step variation of temperature, stochastic temperature change, and analyse of sensitivity, are implemented to prove the effectiveness and superiority of the proposed algorithm. Simulation results verify that the proposed method can generate the highest energy under non-uniform temperature distribution condition, e.g., 391.34%, 115.71%, 110.92%, and 109.43% to that of perturb and observe, particle swarm optimization, whale optimization algorithm, and grey wolf optimizer in the stochastic temperature change. Lastly, the implementation feasibility of the proposed method is demonstrated by the hardware-in-the-loop experiment based on dSpace platform.

Phased Array Shaped-Beam Satellite Antenna With Boosted-Beam Control

This communication presents a beamforming shaped-beam satellite (SBS) antenna based on a phased array technique and a boosted-beam control. The presented SBS antenna is specifically designed to cover the whole regions of Korea including the southern and northern areas. The proposed SBS antenna consists of waveguide feed network, beamforming circuits, waveguide circular polarizers, 19 radiation elements, and a boosted-beam control panel with active component calibration for temperature variation. To maximize the flexible performance, boosted-beam mode is supported to meet the required high-power signal regardless of bad weather conditions. The adjustable effective isotropic radiated power (EIRP) range was around 6 dB and there are a total of 19 beamforming units each configured by drive amplifier, phase shifter, and attenuator. Also, one extra beamforming unit synchronized with the other 19 elements is integrated for active component calibration. Each beamforming element can control relative phase shift up to 360° with 5° step and relative amplitude variation up to 10 dB with 1 dB step as well. Also, each radiation element is configured by waveguide horn and the return losses were better than 25 dB at 21 GHz.

Performance Comparison of Active Rectifier Control Schemes in More Electric Aircraft Applications

In a more electric aircraft (MEA) design, the onboard electric generators are mechanically coupled directly to the jet engines, thus producing a variable-frequency constant magnitude voltage. This wild-frequency characteristic imposes a new design challenge on the onboard power converters. In this article, an experimental performance comparison between the model predictive and the proportional–integral (PI)-based control schemes for active rectifiers in MEA applications is presented. The comparison of the aforementioned controllers is executed under the MEA variable input frequency perspective for the first time and, therefore, constitutes the main contribution of this article. This comparison mainly addresses the dynamic response of the controllers in terms of dc-bus voltage regulation and unity power factor operation under frequency ramping, frequency step changes, and load step variations. Furthermore, the robustness of the controllers is analyzed in terms of their performance degradation in the presence of parameter mismatch. Both the model predictive and PI-based controllers are experimentally tested using a 1-kW SiC-MOSFET two-level voltage-source-converter topology.