Simulink Model Research Articles

COMPUTER MODELING OF TRANSIENT ELECTROMECHANICAL PROCESSES IN A WIND POWER PLANT WITH A MAGNETIC GEARBOX

In this work, a computer Simulink model of a wind power plant has been developed, which uses a magnetic gearbox instead of a mechanical gearbox and also contains a synchronous permanent magnet generator. A separate Simulink model of a magnetic gearbox built on the basis of a modulated magnetic field in the air gap was developed, which al-lows to study the stability of its operation both in steady-state and transient modes. Calculations of various dynamic modes of the wind power plant’s operation were carried out, based on the developed model, such as the starting mode, an instantaneous increase in the wind speed acting on the wind turbine, and an increase in the load of the electric gen-erator. According to the results of the calculations, it is shown that in transient modes, when short-term overloads oc-cur, both rotors of the magnetic gearbox can fall out of synchronous motion for a certain period of time and then, de-pending on the parameters of the gearbox (as well as its other elements), the electromechanical system either reaches a certain operating steady-state mode or loses the ability to transfer mechanical power from the wind turbine to the gen-erator. It has been shown that the use of a more powerful magnetic gearbox, with an increased value of the maximum magnetic torque, allows of a more overload-resistant operation of both: a gearbox and the wind plant as a whole. Ref-erences 9, figures 10.

Modified Arithmetic Optimization Algorithm (MAOA) based torque ripple minimization for a sensorless BLDC motor

ABSTRACT Permanent magnet brushless DC (PM BLDC) motor drives outperform the induction motor drives in terms of performance and improved efficiency. Recent advancements in power electronics technology have improved the application of BLDC drives in a variety of home applications. However, the BLDC motor drives suffer from torque ripple, which causes machine vibration, speed oscillations, and acoustic noise, limiting the application range. In this prelude, an optimization tuning algorithm, namely Modified Arithmetic Optimization Algorithm (MAOA) is suggested in this paper for torque ripple minimization in a sensorless BLDC drive. In this paper, the cuk converter topology with PAM scheme is proposed for the sensorless BLDC drive, and MAOA algorithm is used to improve the gain of the controller. A MATLAB Simulink model is used to validate the results of MAOA tuned BLDC drive.

Hybrid Neuro-Fuzzy Based Improved Control Design of Electro-Pneumatic Clutch Actuation Control System for Heavy Duty Vehicles

The application of hybrid Neuro-Fuzzy principles of clutch actuation control in enhancing the performance of electro-pneumatic clutch actuation system for heavy duty vehicles is the aim of this presentation. Neuro-Fuzzy is a hybrid design that accommodates the principles of fuzzy Logic and Neural Network in a manner that take advantage of their positive sides. The inability of some heavy-duty vehicles to operate optimally on hilly terrains and which often results in road mishaps are traceable to the inadequacies in conventional clutch actuation control mechanisms. These conventional actuation control techniques provide for routine calibration of clutch actuators after maintenance. Often times, this important requirement of calibration is neglected with attendant ugly consequences. To stem this tide of manual calibration and its obvious defects, an intelligent method of clutch actuation modelled in a hybrid Neuro-Fuzzy control is implemented. Conventional data obtained for errors, speed, torque and power from Mercedes Benz Actros Truck model MP 2, 2031 provided the reference points. These data were embedded into a Simulink block and cascaded into a designed Neuro-Fuzzy Simulink model. Both conventional and Neuro-Fuzzy Simulink model controllers were also simulated. Different percentages of improvements were recorded for piston error, angular speed, engine torque and power respectively. The level and percentage of improvements stood at 0.4821mm or 33.04% decrease for error, increases of 334.1 RPM or 33% for angular speed, 0.0594NM or 33.26% for torque and 2.79W or 16.53% for power respectively.

A Simplified Dynamic Model of DFIG-based Wind Generation for Frequency Support Control Studies

In recent years, wind generation has been fast growing and become one of the major generation resources in power systems. Since the wind generation does not inherently equip with frequency support functions, the power system frequency response degrades as the wind penetration increases. Therefore, frequency support control of wind generation has gained increasing focus. However, the dynamic models of wind generation systems, which are required by the control design and analysis, are commonly very complicated and difficult to obtain, especially for the doubly-fed induction generator based wind turbine (DFIG-WT). In this paper, the authors propose a simplified dynamic model for the DFIG-WT. The proposed analytical model is derived from the detailed model by selectively neglecting very fast dynamics while keeping the critical ones. It is suitable for frequency control studies. The model accuracy is first validated against the detailed DFIG-WT model in Simulink. Then, the wind frequency control function is studied based on the proposed model.

Innovative Hybrid Energy Storage Systems with Sustainable Integration of Green Hydrogen and Energy Management Solutions for Standalone PV Microgrids Based on Reduced Fractional Gradient Descent Algorithm

This paper investigates innovative solutions to enhance the performance and lifespan of standalone photovoltaic (PV)-based microgrids, with a particular emphasis on off-grid communities. A major challenge in these systems is the limited lifespan of batteries. To overcome this issue, researchers have created hybrid energy storage systems (HESS) along with advanced power management strategies. This study introduces innovative multi-level HESS approaches and a related energy management strategy designed to alleviate the charge/discharge stress on batteries. Comprehensive Matlab Simulink models of various HESS topologies within standalone PV microgrids are utilized to evaluate system performance under diverse weather conditions and load profiles for rural site. The findings reveal that the proposed HESS significantly extends battery life expectancy compared to existing solutions. Furthermore, the paper presents a novel energy management strategy based on the Reduced Fractional Gradient Descent (RFGD) algorithm optimization, tailored for hybrid systems that include photovoltaic, fuel cell, battery, and supercapacitor components. This strategy aims to minimize hydrogen consumption of Fuel Cells (FCs), thereby supporting the production of green ammonia for local industrial use. The RFGD algorithm is selected for its minimal user-defined parameters and high convergence efficiency. The proposed method is compared with other algorithms, such as the Lyrebird Optimization Algorithm (LOA) and Osprey Optimization Algorithm (OOA). The RFGD algorithm exhibits superior accuracy in optimizing energy management, achieving a 15% reduction in hydrogen consumption. Its efficiency is evident from the reduced computational time compared to conventional algorithms. Although minor losses in computational resources were observed, they were substantially lower than those associated with traditional optimization techniques. Overall, the RFGD algorithm offers a robust and efficient solution for enhancing the performance of hybrid energy systems.

Optimizing COP by RSM and MATLAB model of mini refrigerator based on thermoelectric units driven by solar photovoltaic

AbstractEnergy scarcity in the world and the pollutants resulting from excessive use of conventional energy aroused the need for sustainable alternatives that are environment friendly. A multi-use thermoelectric refrigerator powered by solar energy to obtain the lowest consumption with the highest efficiency. The designed refrigerator is based on the Peltier effect using Peltier units where a temperature difference is created between the junctions by applying a voltage difference across the junction. This study investigates the performance of a refrigerator cooling system powered by a photovoltaic (PV) system. The research aims to assess the efficiency, effectiveness, and feasibility of utilizing solar energy to drive refrigeration, particularly in off-grid or environmentally conscious applications. Through a comprehensive experimental setup and data analysis, the study examines energy consumption, cooling efficiency, and overall system performance under varying conditions. The findings contribute valuable insights into the potential of PV-powered refrigerators as sustainable cooling solutions. It relies on a control unit that measures the resulting temperature to determine the appropriate connection mode to give the highest cooling efficiency. The average solar radiation when operating for 8 h, for the different seasons of the year was 149.5, 67.5, 119.3, and 118.3 w/m2 in summer, winter, spring, and fall, respectively. The average cooling energy consumption was 107.25, 137.04, 107, and 138.08 w for temperatures (20 ± 1, 15 ± 1, 20 ± 2, and 15 ± 2) °C respectively that proof solar radiation is sufficient to produce energy for the summer of cooling temperatures up to 15 °C, while in the spring and fall it is sufficient to 20 °C. The Fast not Eco mode is the least energy consuming and the fastest cooling, it can be used for rapid cooling at a short time less than an hour. The best mode in the case of continuous operation is the case of as next Eco mode cooling temperature of 20 ± 0.1 °C. The MATLAB Simulink model was developed to reduce the design cycle and facilitate the integration of solar photovoltaic with the TEC. The optimal operating point is identified through simulation and validated through experimental analysis, the optimal COP was 71.089% by Response surface methodology (RSM).

Classifying changes to LabVIEW and simulink models via changeset metrics

Classifying changes to LabVIEW and simulink models via changeset metrics

Load Frequency Optimal Active Disturbance Rejection Control of Hybrid Power System

The widespread adoption of the power grid has led to increased attention to load frequency control (LFC) in power systems. The LFC strategy of multi-source hybrid power systems, including hydroelectric generators, Wind Turbine Generators (WTGs), and Photovoltaic Generators (PVGs), with thermal generators is more challenging. Existing methods for LFC tasks pose challenges in achieving satisfactory outcomes in hybrid power systems. In this paper, a novel method for the multi-source hybrid power system LFC task by using an optimal active disturbance rejection control (ADRC) strategy is proposed, which is based on the combination of the improved linear quadratic regulator (LQR) and the ADRC controller. Firstly, an established model of a hybrid power system is presented, which incorporates multiple regions and multiple sources. Secondly, utilizing the state space representation, a novel control strategy is developed by integrating improved LQR and ARDC. Finally, a series of comparative simulation experiments has been conducted using the Simulink model. Compared with the LQR with ESO, the maximum relative error of the maximum peaks of frequency deviation and tie-line exchanged power of the hybrid power system is reduced by 96% and 83%, respectively, by using the proposed strategy. The experimental results demonstrate that the strategy proposed in this paper exhibits a substantial enhancement in control performance.

Techno-economic assessment of vertical axis wind turbine driven RO desalination with compressed air energy storage for remote communities

Renewable energy desalination is gaining much attention in remote off-grid communities facing challenges in accessing clean water. Typically, batteries ensure the continuous operation of small-scale renewable reverse osmosis (RO) desalination systems; however, they are expensive and have relatively shorter lifespans. This study investigates the implementation of a compressed air energy storage (CAES) system coupled with a vertical axis wind turbine (VAWT) to directly drive small-scale RO desalination, potentially replacing batteries and reducing energy conversions. A Simulink model was developed to simulate the performance of a VAWT-driven CAES operating RO units, adaptable for both technical and economic assessments. Parametric studies have identified the optimal configuration. The most cost-effective configuration, utilising eleven VAWTs and a pressure exchanger (PX), achieves a levelised cost of water (LCOW) of 1.63 US$/m3 and an annual water production of 9400 m3. The normalised daily water production per square metre of turbine swept area at the study site is 0.19 m3/m2/day at an average wind speed of 5 m/s. While this configuration has a higher initial capital cost, it yields the lowest LCOW. The CAES system effectively addresses the intermittency challenges of wind energy. This study presents a novel, battery-free VAWT-CAES-RO system as a sustainable desalination solution for remote communities, offering a promising approach to address water scarcity in an environmentally friendly manner.

A Novel Battery Temperature-Locking Method Based on Self-Heating Implemented with an Original Driving Circuit While Electric Vehicle Driving: A Numerical Investigation

In extremely cold environments, when battery electric vehicles (BEVs) are navigating urban roads at low speeds, the limited heating capacity of the on-board heat pump system and positive temperature coefficient (PTC) device can lead to an inevitable decline in battery temperature, potentially falling below its permissible operating range. This situation can subsequently result in vehicle malfunctions and, in severe cases, traffic accidents. Henceforth, a novel battery self-heating method during driving is proposed to maintain battery temperature. This approach is ingeniously embedded within the heating mechanism within the motor driving system without any necessity to alter or modify the existing driving circuitry. In the meantime, the battery voltage can be regulated to prevent it from surpassing the limit, thereby ensuring the battery’s safety. This method introduces the dead zone into the space vector pulse width modulation (SVPWM) algorithm to form the newly proposed dSVPWM algorithm, which successfully changes the direction of the bus current in a PWM period and forms AC, and the amplitude of the battery alternating current (AC) can also be controlled by adjusting the heating intensity defined by the ratio of the dead zone and the compensation vector to the original zero vector. Through the Simulink model of the motor driving system, the temperature hysteresis locking strategy, grounded in the field-oriented control (FOC) method and employing the dSVPWM algorithm, has been confirmed to provide controllable and sufficiently stable motor speed regulation. During the low-speed phase of the China Light Vehicle Test Cycle (CLTC), the battery temperature fluctuation is meticulously maintained within a range of ±0.2 °C. The battery’s minimum temperature has been successfully locked at around −10 °C. In contrast, the battery temperature would decrease by a significant 1.44 °C per minute without the implementation of the temperature-locking strategy. The voltage of the battery pack is always regulated within the range of 255~378 V. It remains within the specified upper and lower thresholds. The battery voltage overrun can be effectively avoided.

High power low cross-talk single inductor dual output DC-DC converter for power management in PLL IC

Abstract A single inductor dual output DC-DC converter operating in CCM mode is proposed in this paper. Due to the more accuracy and complete small-signal model in Simulink and the dedicatedly designed compensation parameters, the circuit can broaden the load range of the converter through fast response and reduce the cross-talk effects between output branches during load adjustment. The converter is implemented in TSMC 0.18μm 1P6M BCD process with a chip area of 1.7mm*1.8mm. The simulation results show that the converter has a conversion efficiency of 81.3% at a maximum output power of 5W and the cross-regulation of less than 36mV/A at 1A load regulation.

Embedded ML-based locomotion control for a 12-joint four-legged robot

Reinforcement learning has developed as a promising approach for robot locomotion control, which can save engineering effort compared to conventional approaches. This article presents the implementation of Reinforcement learning on a low-cost, 12 degree of freedom robot known as a quadruped (spider) to optimize locomotion control, enabling the robot to move on different surfaces such as flat surfaces, ramps, speed bumps, and rough terrain. A MATLAB Simulink model is developed as a digital twin of the spider robot. The dynamics of the model were studied and validated using an open-loop algorithm. Then, the model is utilized in a training simulation environment to apply the reinforcement learning algorithm, showing its ability to move along a predefined path as a replacement for conventional motion control systems. Moreover, the work compares the performance and effectiveness of machine learning-based locomotion control with traditional motion control systems regarding navigation accuracy, speed, and adaptability in challenging environments. The minimum hardware requirements are also studied to move the experiment from simulation to reality.

Response Surface Methodology Approach for Modeling and Performance Optimization of a PEM Fuel Cell

A Polymer Electrolyte Membrane (PEM) fuel cell is a popular green source of electrical energy and is often used in applications like electric vehicles due to its environmentally friendly operation. This type of fuel cell has a low operating temperature, light weight, and negligible emission of greenhouse gases. However, the PEM fuel cell is a complex multivariable system with a large number of input and output factors, and most of the input factors affect output factors directly or indirectly. As a result, it is conventionally quite difficult to determine which input factor has a major effect on a particular output factor. Statistical methods are very popular for finding the individual and interaction effects of input factors on output factors. In this paper, for the first time, a simple and realistic MATLAB SIMULINK model for a PEM fuel cell is presented to conduct various experimental tests. The developed MATLAB SIMULINK model and statistical design of experiments, Response Surface Methodology (RSM), are used to develop metamodels (mathematical models of the simulation model) for the PEM fuel cell to find the individual and interaction effects of various input factors on output factors. The developed metamodels can be used to find the region for optimum operation of the presented fuel cell. The metamodels are validated by conducting four different statistical tests. The optimum point of operation is presented by calculating stationary points from the metamodels.

On the portability of EMT models in different power system simulation software tools

This paper presents the investigation carried out on the portability and compatibility of a model in different simulation software. The offer of simulation software for power system simulation is wide, with each program having its own modelling interface and its own methods of model development. The lack of a widespread standard for portability between applications implies that the same organisation needs to carry out studies on different applications, requiring the development of a model of the same element or system for each application. This study presents an example of the integration of an inverter model in DigSilent, PSCAD and Simulink by means of the Multilink tool. Throughout the article, the differences found when performing the integration and the same simulation scenario in these three simulation tools are listed. It concludes with a comparison of the results obtained from an electromagnetic transients (EMT) simulation in the three simulation software. The results show a greater similarity between PSCAD and Simulink, with respect to the results obtained in DigSilent.

Optimal Coordinated Operation for Hydro–Wind Power System

The intermittent and stochastic characteristics of wind power pose a higher demand on the complementarity of hydropower. Studying the optimal coordinated operation of hydro–wind power systems has become an extremely effective way to create safe and efficient systems. This paper aims to study the optimal coordinated operation of a hybrid power system based on a newly established Simulink model. The analysis of the optimal coordinated operation undergoes two simulation steps, including the optimization of the complementary mode and the optimization of capacity allocation. The method of multiple complementary indicators is adopted to enable the optimization analysis. The results from the complementary analysis show that the hydraulic tracing effect obviously mitigates operational risks and reduces power losses under adverse wind speeds. The results from the analysis of capacity allocation also show that the marginal permeation of installed wind capacity will not exceed 250 MW for a 100 MW hydropower plant under random wind speeds. These simulation results are obtained based on the consideration of some real application scenarios, which help power plants to make the optimal operation plan with a high efficiency of wind energy and high hydro flexibility.

Trajectory control and optimization of PID controller parameters for dual-arms with a single-link underwater robot manipulator

ABSTRACT This paper focuses on the modeling, simulation, and control of the trajectories of a dual-arm single-link underwater robot manipulator (DS-URM), having dual arms (left and right) with a single link each. The dynamic coupling between the base and the dual arms makes trajectory control of the end effector difficult. This study attempts to simulate and control dual arms with a single-link underwater robotic manipulator using a hybrid controller. To reduce the error for a sinusoidal wave and a cycloid trajectory, a hybrid controller is the combination of the Proportional-Integral-Derivative (PID) controller and overwhelm controller. The underwater dynamic’s buoyancy, gravity, and hydrostatic forces acting on the underwater robot are modeled in an integrated SIMULINK model, including the DS-URM. The DS-URM has been investigated, revealing some significant trajectories of the left and right tips. Effective tuning methods include Ziegler-Nicholas (Z-N), genetic algorithms, Ant Colony Optimization (ACO), and Particle Swarm Optimization (PSO). The Integral of Time multiplied by Absolute Error (ITAE) criteria has been used to improve trajectory tracking via particle swarm optimization. Results show significant improvements in trajectory tracking, with ITAE error reduction by 96.44% and 98.6% for left and right arms, respectively, achieving stability in 0.000645s.

Performance Analysis of Multiple Energy-Storage Devices Used in Electric Vehicles

Considering environmental concerns, electric vehicles (EVs) are gaining popularity over conventional internal combustion (IC) engine-based vehicles. Hybrid energy-storage systems (HESSs), comprising a combination of batteries and supercapacitors (SCs), are increasingly utilized in EVs. Such HESS-equipped EVs typically outperform standard electric vehicles. However, the effective management of power sources to meet varying power demands remains a major challenge in the hybrid electric vehicles. This study presents the development of a MATLAB Simulink model for a hybrid energy-storage system aimed at alleviating the load on batteries during periods of high power demand. Two parallel combinations are investigated: one integrating the battery with a supercapacitor and the other with a photovoltaic (PV) system. These configurations address challenges encountered in EVs, such as power fluctuations and battery longevity issues. Although batteries are commonly used in conjunction with solar PV systems for energy storage, they incur higher operating costs due to the necessity of converters. The findings suggest that the proposed supercapacitor–battery configuration reduces battery peak power consumption by up to 39%. Consequently, the supercapacitor–battery HESS emerges as a superior option, possibly prolonging battery cycle life by mitigating stress induced by fluctuating power exchanges during the charging and discharging phases.

Simulink Modeling and Analysis of a Three-Dimensional Discrete Memristor Map

The memristor, a novel device, has been widely utilized due to its small size, low power consumption, and memory characteristics. In this paper, we propose a new three-dimensional discrete memristor map based on coupling a one-dimensional chaotic map amplifier with a memristor. Firstly, we analyzed the memristor model to understand its characteristics. Then, a Simulink model for this three-dimensional discrete memristor map was developed. Lastly, the complex dynamical characteristics of the system were analyzed via equilibrium points, bifurcation diagrams, Lyapunov exponent spectra, complexity, and multistability. This study revealed the phenomena of coexisting attractors and hyperchaotic attractors. Simulink modeling confirmed that the discrete memristors effectively enhanced the chaos complexity in the three-dimensional discrete memristor map. This approach addresses the shortcomings of randomness, the lack of ergodicity, and the small key space in a one-dimensional chaotic map, thereby enriching the theoretical analysis and circuit implementation of chaos.

Enhanced hybrid energy storage system combining battery and supercapacitor to extend nanosatellite lifespan

The power limitations of nanosatellites, particularly during peak demand periods such as data transmission and maneuvering, hinder their operational capabilities. Traditional Electrical Power Subsystems relying solely on batteries face challenges in delivering the necessary power density and maintaining battery life, especially during eclipses. This study proposes an innovative Hybrid Energy Storage System for a 3U nanosatellite, integrating high-energy-density batteries with high-power-density supercapacitors, using an active parallel hybrid topology with two bidirectional converters and an optimal power management strategy. Using MATLAB and Simulink models, the study optimizes the Hybrid Energy Storage System by focusing on minimizing the capacity rate and depth of discharge to extend battery life. Simulation results show a 53.42% reduction in depth of discharge compared to a battery-only system, indicating a significant extension of battery life. Additionally, the proposed system allows for a minimal 2.08% increase in overall mass while maintaining enhanced performance. This research fills a critical gap in the literature by exploring active Hybrid Energy Storage System topologies for spacecraft applications, beyond the traditional passive and semi-active configurations. The innovative power management strategy ensures efficient energy utilization, significantly enhancing the reliability and efficiency of nanosatellite missions. The findings offer a practical solution to improve mission performance and extend the operational lifespan of nanosatellites, paving the way for more robust and capable small satellite deployments.

Optimized sliding mode control for improved frequency response in an Islanded microgrid system

ABSTRACT This paper presents an enhanced Sliding Mode Control (SMC) approach in an Islanded Microgrid (IMG) system for regulating its frequency. The system encounters unpredictable disturbances arising from internal and external factors such as fluctuations in generation and demand, parameter variations, time delay, and many more. These factors challenge the frequency control during load fluctuations. To overcome these challenges, an Integral Sliding Mode-Load Frequency Control (ISM-LFC) as a robust control strategy employing integral sliding surface is proposed to regulate the system frequency. Particle Swarm Optimization (PSO) technique is used for optimal performance of ISM-LFC by meticulously determining the control variable parameters. A Simulink model of the IMG system in MATLAB is developed for conducting a comprehensive simulation analysis under diverse operational scenarios. The result outcomes affirm the effectiveness of the proposed controller using Integral sliding surface and modified saturation function-based control law for improved frequency response. Furthermore, comparative analysis with other alternative control strategies validates the improved performance of optimised ISM-LFC for frequency stabilisation.