Simulink Model Research Articles

The Effect of Tuned Mass Damper Mass Ratio on Wind Turbine Vibration Mitigation

This paper examines the efficacy of Tuned Mass Dampers (TMDs) in mitigating vibration in wind turbines under diverse excitation force conditions. The impact of TMD on the response of a wind turbine exposed to sinusoidal and random wind forces, at varying mass ratios μm: 0.02, 0.05, 0.10, and 0.20, was assessed through the use of a MATLAB SIMULINK model. The findings indicate that TMDs markedly attenuate vibration when subjected to sinusoidal forces, particularly at higher TMD mass ratios. In contrast, the reduction in vibration level in the presence of random wind forces is relatively modest, becoming more pronounced at higher TMD mass ratios. In addition, the internal forces generated by incorporating the TMD into the system were calculated for different mass ratio values. It was noted that these forces increased in proportion to the mass ratio, although they remained within reasonable limits. However, an increase in the TMD mass ratio has been observed to result in a corresponding increase in these forces. This underscores the importance of meticulous mass ratio selection for the optimal functioning of TMD systems. It suggests that dealing with complex, broadband excitation may entail inherent limitations. The findings of this study may prove valuable in enhancing the understanding of the stability and lifetime of wind turbines under dynamic wind conditions.

Design of levitation controller for EMS maglev train with compensation of eddy current effect

ABSTRACT The Electro magnetic suspension (EMS) maglev train uses active control to achieve levitation stability, and the eddy current effect of the levitation electromagnet can make it difficult to adjust the control parameters of EMS maglev train, even affecting the levitation stability of EMS maglev train. Aiming at the control parameters of EMS maglev train under eddy current effect, an analytical expression of the levitation force considering eddy current effect was derived, and a single electromagnet levitation model was established. The influence of eddy current effect in the stability of open-loop levitation system was compared and analyzed. A fitting levitation control parameter was determined through a single levitation frame bench test, and the Simulink model of a single levitation frame was established. The different levitation control parameters effects considering eddy current effects at 200 km/h was studied comparatively, and a BP-PID adaptive controller was designed to adjust the controller parameters of EMS maglev train. The research results showed that the proposed BP-PID controller can effectively adjust control parameters to achieve effective compensation and optimization of the balance working point of the air gap caused by eddy current effect.

System-level Prognostics and Health Management for Complex Industrial Systems

Prognostics and health management (PHM) has become essential to guarantee aware and safe system operation and to inform economic decision-making. However, due to the nature of detection, diagnostics, and prognostic methods, applications have mainly been limited to the component level. In practice, most industrial systems consist of multiple interacting components whose partial degradation could lead to the system's failure (or subsystems).This research addresses the limitations of traditional component-level PHM techniques by proposing a novel system-level framework. By implementing a hierarchical structure of components and subsystems, we will select an optimal method for each subsystem to aggregate its component health assessments. The overall system health can then be estimated by further combining the obtained estimates. The research considers simplified and holistic modeling techniques, margin-based methods, and hybrid graphical models. This approach aims to provide reliable system health predictions and online components' sensitivity measures to enhance maintenance decision-making. We consider an application in the context of the nuclear industry, characterized by strict safety and economic requirements. Using a SIMULINK model to approximate a Pressurized Water Reactor (PWR) with real industrial inputs, we plan to add component degradation modules and use simulated sensor data and reliability information to test the proposed framework. Initial results on artificial case studies show the feasibility of integrating component-level health predictions.

Analysing the Swing Equation using MATLAB Simulink for Primary Resonance, Subharmonic Resonance and for the case of Quasiperiodicity

The swing equation plays a significant role in the analysis of stability and frequency response various power systems and mechanical systems. MATLAB Simulink simulates and analyses different systems, including synchronous generators with various excitation methods. This research aims to study the swing equation by modelling the system in Simulink. Swing equation analysis can be applied to tackle power instabilities in the electrical grid, to avoid power outages by monitoring the small disturbances that occur within the system. This paper shows the time series, phase portraits, and Poincar´e maps generated using data from the simulated model. It highlights the occurrence of period doublings which lead to loss of synchronisation and the resulting instability in the system that descends into chaos when the variables are changed in the Simulink model. The integrity diagrams were also identified for primary resonance, subharmonic resonance, and quasiperiodicity, offering valuable information to understand the system’s nonlinear behaviour. Using the swing equation in MATLAB Simulink provides a robust tool for analysing, simulating, and optimising systems. Hence this study provides an enhanced understanding of the system’s behaviour in Simulink for primary resonance, subharmonic resonance and for the case of quasiperiodicity. Additionally, it validates the analytical and numerical findings from prior works by the same authors.

Modeling the effect of external load variations on single, serie and parallel connected microbial fuel cells

This paper presents a microbial fuel cell (MFC) model designed to analyze the effect of the external load on MFC performance. The model takes into account the voltage and the chemical oxygen demand (COD) dependence on the external load. The value of the model parameters were calibrated by means of the voltage relaxation method tests using a controlled load current. Laboratory measurements and MATLAB Simulink model computations were used to validate the proposed model. The tests results demonstrated that the proposed model accurately predicts the voltage and COD evolution during the batch cycle of the MFC. The root mean square error (RMSE) was used to assess the fitting goodness of the model. The RMSE of COD and voltage generation was in all the cases lower than 4%, predicting accurately the behaviour of single MFC as well as MFC connected in series or parallel.

MIWO based MPPT of PV system for induction motor driven water pumping system

Renewable energy source-based Water Pumping Systems (WPSs) have gained popularity for drinking, agricultural, and industrial purposes. Locally situated standalone Photovoltaic (PV) powered WPS can provide a viable water supply solution, especially with induction motors (IM) due to their advantages over other motor types. However, solar PV energy output is greatly influenced by weather conditions, necessitating energy storage systems like batteries, which increase costs and require maintenance. This research proposes an efficient energy management system for a PV-powered IM-driven WPS that does not rely on batteries. The system handles Partial Shading Conditions (PSC) effectively, thanks to a sensorless speed controller combining a Modified Invasive Weed Optimization (MIWO) mechanism with the Perturb and Observe (P&O) method. This controller uses the inverter as an MPPT circuit, eliminating the need for a distinct converter to follow the MPP. The hybrid P&O-MIWO method's outcomes are compared with those of P&O hybridization with GA, PSO, and GWO to assess efficiency under various PSCs. TS-Fuzzy controllers are employed for voltage control at the DC-link and motor speed. The proposed system is analyzed across different scenarios and validated using a Simulink model in MATLAB. Results indicate that the hybrid P&O-MIWO mechanism enhances energy generation from the PV unit without relying on energy storage devices, providing a cost-effective solution for PV-based WPS implementation.

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.

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.

Real Time Prediction and Modelling of Power Grid System Stability and Load Balancing

Abstract The extensive geographical distribution of the power system determines its highly complex structure. The system includes key components such as generators, substations, transmission and distribution grids, and users. This system has characteristics such as nonlinearity, time-varying, and parameter uncertainty. Power system stability is inherently linked to its regular operational performance. This article uses Simulink models to simulate the working state of generators and circuit breakers during faults. Under the conditions of a synchronous generator with a rated power of 350MW, a voltage of 10.5KV, a three-phase parallel RLC load rated voltage of 115KV, and a power consumption of 300MW, when a short occurs on line, the speed and relative angle of the generator tend to a fixed value, and the system remains stable. When a fault occurs in the circuit within 0.1 seconds, the circuit breaker will cut off the faulty line within 0.6 seconds. Avoiding the occurrence of oscillations and unstable states in typical dynamic 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.