MATLAB Simulink Research Articles

Design, development, and testing of active valve piezo-hydraulic pump

Valves play a major role in rectifying the fluid flow through piezo-hydraulic pumps, which may be active or passive. Passive valves operate due to changes in the fluid pressure whereas active valves are operated through control signals. This paper presents a novel design of an active valve chamber assembly for a piezo-hydraulic pump. It is a novel design since none of the research publications has addressed the application of a Flexurally amplified piezoelectric actuator (FAPA) for valve actuation in active valve chamber assembly. The piezo-hydraulic pump design is done using solid edge design software. FAPA’s are used for pumping and valve actuation. Structural analysis with experimental verification for the valve chamber component is presented. The valve opening and the pumping displacement are mathematically modeled in MATLAB Simulink software. Also, mathematical simulations for pump flow rates at different actuation frequencies and voltage are discussed. The piezo-hydraulic pump components are fabricated and assembled with the actuators. Experimental investigations on the flow rate performance of the active valve piezo-hydraulic pump are carried out with changing frequency and voltage amplitude of actuators. The interpretation of results is done by comparing the experimental and simulation results. During experiments, the pump delivered a maximum flow rate of 4.5 ml min−1 at 140 V when actuated at 0.25 Hz actuation frequency.

Performance evaluation of an automatic resonant switched capacitor-based voltage balancing circuits for series connected batteries

Electrical energy storage (EES) plays a crucial role in various power applications. Voltage imbalance is a common issue that can negatively affect the efficiency, reliability, and safety of EESs. Several types of voltage balancing (VB) circuits have been proposed in much of the literature. Among these VB circuits, switched capacitor (SC)-based circuits have attracted significant interest due to their efficiency, cost-effectiveness, compact size, and ease of control, but their balancing performance is not yet satisfactory. As a result, structural modifications in SC-based circuits have been widely proposed to improve balancing performance. However, not all of these circuit structures have been implemented into a resonant switched capacitor (RSC)-based voltage balancing, which has higher efficiency. Hence, this study aims to assess the efficiency of RSC-based VB circuits by conducting analog simulation using the Matlab Simulink software. This research evaluates the performance of the VB circuit not only in terms of its speed and efficiency, but also in terms of its energy distribution. The results show that the delta structure is the fastest in terms of balancing speed when completing the balancing process, followed by the mesh structure and the parallel structure. The best energy distribution is produced by a parallel structure, as indicated by the change in voltage of all battery cells always moving towards a convergent value, regardless of the variations in initial imbalance conditions. Meanwhile, other circuit structures distribute energy randomly, allowing the voltage of the battery cells to change not directly towards a convergent value. Lastly, the paper summarizes the balancing speed, efficiency, circuit complexity, and quality of energy distribution.

Heuristic power management of hybrid source electric vehicle based on PV-battery-PEMFC

Renewable energy sources are now being focused on for usage in electric vehicles. Although majority of electric vehicles run solely on batteries, they have eliminated local emissions but not pollution. To tackle this issue, this research looks into the performance and power management aspects of an electric vehicle's hybrid power system, with a particular emphasis on the interactions between fuel cells, batteries, and photovoltaic (PV) cells. Stable operation is ensured via a bi-directional buck-boost converter, which maintains the voltage from all sources around reference 430 V. Initially, the fuel cell supplies electricity under low light conditions. The PV system and battery take over when the irradiance surpasses 100 W/m2, with the battery first draining and then charging in tandem with the increase in irradiance. 1750 RPM is the constant motor speed that is reached after making the required torque adjustments. A model full electric vehicle with multiple sources has been proposed with an efficient power management algorithm. When the battery is in stationary mode and the state of charge (SOC) is less than 100%, extra solar power is used to charge the battery. The model also takes into consideration using the car for entertainment or gadget charging when the ignition is off. The biogas output can be regulated using an inferential control technique using artificial neural network (ANN) based on the fuel demand or consumption. The system also includes anaerobic digestion of organic waste to provide hydrogen for the fuel cell sustainably from biogas. Power, current, SOC profiles, motor performance graphs, and other validations show that the extensive simulations exhibit efficient power management and a strong model for hybrid electric car power systems. The model has been simulated in the MATLAB Simulink environment and has been tested under realistic conditions.

Conventional and artificial intelligence based maximum power point tracking techniques for efficient solar power generation

AbstractThe increasing global need for renewable energy sources, driven by environmental concerns and the limited availability of traditional energy, highlights the significance of solar energy. However, weather fluctuations challenge the efficiency of solar systems, making maximum power point tracking (MPPT) systems crucial for optimal energy harvesting. This study compares ten MPPT approaches, including both conventional and artificial intelligence (AI)‐based techniques. These controllers were designed and implemented using MATLAB Simulink, and their performance was evaluated under real environmental conditions with fluctuating irradiance and temperature. The results demonstrate that conventional techniques, such as incremental conductance (INC), Perturb and Observe (P&O), Incremental conductance and Particle Swam Optimization (INC‐PSO), Fuzzy Logic Control and Particle Swam Optimization (FLC‐PSO), and Perturb and Observe and Particle Swam Optimization (P&O‐PSO), achieved accuracies of 94%, 97.6%, 98.9%, 98.7%, and 99.3% respectively. In contrast, AI‐based intelligent techniques, including Artificial Neural Network (ANN), Artificial Neural Fuzzy Interference System (ANFIS), Fuzzy Logic Control (FLC), Particle Swam Optimization (PSO), and Artificial Neural Network and Particle Swam Optimization (ANN‐PSO), outperform achieving higher accuracies of 97.8%, 99.9%, 98.9%, 99.2%, and 99%, respectively. Compared to available research, which often reports lower accuracies for conventional techniques, our study highlights the enhanced performance of AI‐based methods. This study provides a comprehensive comparative analysis, delivering critical analysis and practical guidance for engineers and researchers in selecting the most effective MPPT controller optimized to specific environmental conditions. By improving the efficiency and reliability of solar power systems, our research supports the advancement of sustainable energy solutions.

An Isolated High Gain Push Pull Type DC to DC Converter for Fuel Cell Power Generation Systems

Due to their high efficiency and low environmental impact, fuel cell power generation systems have emerged as promising alternatives to traditional energy sources. However, the integration of fuel cells into practical applications necessitates the development of efficient power conversion systems. dc-dc converters play a crucial role in optimizing the power flow between the fuel cell stack and the load. In this paper, a push-pull type high gain dc-dc converter is proposed which consists of a push-pull inverter, a rectifier circuit, and C-filter. The push pull inverter produces high frequency square wave output while the full bridge rectifier and C-filter convert this square wave output into desired dc voltage. The converter boosts the 12V dc input supply to 326 V, representing a gain factor of more than 27. The isolated coupling inductor used in push pull inverter produces high gain and provides electrical isolation. Besides, the proposed topology eliminates the use of bulky grid-connected power transformers that decreases the system size and cost. To evaluate the performance of the proposed topology, a number of simulations under varying loads were carried out in the MATLAB Simulink framework. Further-more, a scaled-down prototype of 160W at 12/326 V was developed to confirm the simulation results. The findings indicate that the suggested converter can be a viable option for the hydrogen fuel cell-based power conversion system. GUB JOURNAL OF SCIENCE AND ENGINEERING, Vol 10(1), 2023 P 37-52

Modelling and performance evaluation of a parabolic trough solar water heating system in various weather conditions in South Africa

In recent years, various energy sources and methods have been used to heat water in domestic and commercial buildings. Water heating methods for large households or commercial buildings include electrical heating elements, gas heaters, and solar energy (solar concentrators, flat plate collectors, evacuated tube collectors, etc.). In recent decades, the focus of water heating has shifted to solar energy, which is abundantly available in most African countries. The weather condition of a region has a huge impact on the system's performance. South Africa is characterised by four different weather seasons (winter, spring, summer, and autumn), unlike most African countries. Therefore, this study focuses on the impact of weather seasons on the system's performance for water heating through the combined use of solar energy and solar concentrator techniques. The system performance was modelled by using Matlab Simulink®, where historical weather data for Pretoria, South Africa, was fed into the model. Based on the weather data input, the system behaviour varied per season due to the change in solar intensity. The average outlet temperatures of the absorber, in the order of magnitude, were 333, 332, 328, and 325 K during the autumn, summer, spring, and winter seasons, respectively. Similarly, the average storage tank temperatures, in the order of magnitude, were 366, 364, 363, and 360 K in spring, summer, autumn, and winter, respectively. From this study, it is concluded that the different weather seasons in South Africa, have a direct impact on the performance of the system. Irrespective of the season, the system produced the required volume of hot water required throughout the year.

Predicting Solar Power Generation Utilized in Iraq Power Grid using Neural Network

The prediction of a photovoltaic (PV) energy production over time is considered the major challenge to integrate it with the utilize grid. This is because it is affected by many factors, including geographical locations and weather conditions. Hence, accurately forecasting PV generation is a crucial stage for ensuring a grid stability. In this paper, several studies are discussed between 2015 to 2023 based on various term forecasting conditions. Then, a neural network (NN) is employed to forecast a medium-term PV power generation by gathering meteorological data specific to the southern region of Iraq. The proposed NN model based on Python language is trained to find the PV power prediction for various seasons of the year using solar radiation and surrounding temperature of weather condition tests. While, the MATLAB Simulink model is designed to address the PV actual power for the same tests. The results show that the root mean square error of a PV generation test at autumn season provides the lowest percentage of 92.2119 W when compared with the other three seasons

Line to Ground Fault Detector in 400 KV Transmission Line by Using Intelligent System

The ability to locate and identify problems in power transmission lines is the most crucial component of power system engineering since it ensures the stable and efficient operation of electrical grids. to minimize downtime, prevent cascading failures, and maintain the power system's stability. problem localization helps identify the precise location of the problem and speeds up the process of restoring the power supply while minimizing the impact on consumers. This paper presents a measurement-based automatic fault localization and detection (ANFIS) technique for transmission lines. High-speed processing of real-time error localization and detection is made possible by the design and implementation of ANFIS. It is suggested that ANFIS for digital distance protection systems be able to discover issues in addition to detecting them. When a transmission experiences a three-phase malfunction Thus, the suggested method can precisely pinpoint the impacted stages. ANFIS has been trained and tested using many kinds of field data. The field data are collected by simulating faults in the Simulink Matlab model depicting the transmission line at various sites between Misan – Kut station 400 Kv along 200 Km using computer software based on Matlab. Phase current and voltage measurements are utilized as ANFIS inputs and are available at the busses. Regarding the kind and detection of defects, The output will demonstrate fault and location identification with an extremely low error percentage through simulated processes; the results also demonstrate that the approach's selectivity and speed are quite dependable and provide adequate performance for applications involving transmission and distribution monitoring; and security. The study emphasizes the criticality of promptly and precisely locating faults in power transmission lines to preserve the stability and security of the power system.

Introduction on tritium transport analysis model for HCCP breeding blanket system

In the context of implementing the He-cooled breeding blanket system for a fusion reactor, several crucial aspects need consideration. Among these, the development of a tritium transport model plays a pivotal role in ensuring safety and effective design. Given that tritium release into the environment from the breeding blanket system poses a radioactive risk, accurate calculation and prediction area essential to prevent potential incidents in a fusion reactor. To address this challenge, a collaborative effort between the Korea Institute of Fusion Energy (KFE) and the University of California, Los Angeles (UCLA) resulted in the creation of THETA-FR (Tritium/Hydrogen Enhanced dynamic Transport Analysis Tool for Fusion Reactor). THETA-FR is an integrated analysis tool that combines Matlab Simulink and COMSOL Multiphysics. Its purpose is to model and predict the dynamic transport phenomena of H isotopes (H/D/T) within the breeding blanket system. Specifically, THETA-FR focuses on transient tritium retention, permeation, and release amounts from the breeding blanket system into the environment. In this paper, we introduce the integrated system and components of THETA-FR, shedding light on various tritium behaviors within the HCCP breeding blanket FW/BU component. By leveraging THETA-FR, researchers and engineers can make informed decisions regarding tritium control and safety in fusion reactors.

A complete control structure based backstepping controller design for stacked multi-cell multi-level SPWM VSC STATCOM

Currently, the installation of FACTS (Flexible Alternative Current Transmission System) devices such as synchronous static compensators (STATCOM) represent a very useful solution to improve both network stability and power quality. The effectiveness of these devices is principally determined by the used static converter (topology and the switching strategy) and the adopted dynamic law characterizing the controller structure. This paper illustrates the stacked five-level, multi-cell STATCOM compensator performances governed by a Backstepping controller technique compared to the use of the conventional PI controller (SPWM) for controlling voltage variation (sags or overshoots) affecting a given network point. The interest in using stacked multi-cell converters topology is to increase the number of voltage levels in order to ensure a good quality voltage waveform at the specified connection point. Therefore, the proposed backstepping controller based on the use of Lyapunov control functions presents a simplified structure and a reduced computational load compared to many others advanced control approaches. The proposed system is verified by running a simulation analysis with Matlab Simulink environment. The simulation results obtained show that the proposed STATCOM configuration ensures good voltage regulation at the common connection point (PCC), correction of the unity power factor on the grid side and good response time via reactive power compensation under variable load conditions.

Passive Equilibrium Circuit for Lithium-Ion Battery State of Charge Balance

Abstract Lithium-ion batteries serve as pivotal energy storage solutions in electric vehicles and portable electronics. Precise State of Charge (SOC) estimation is crucial for optimizing battery performance and ensuring longevity. This paper introduces an innovative approach utilizing passive equilibrium circuits for enhanced SOC estimation. The passive balancing circuits actively equalize voltage levels among individual battery cells during both charging and discharging, thereby improving SOC estimation accuracy. The proposed method is implemented and simulated using Matlab Simulink, demonstrating superior performance compared to traditional methods. Simulation results reveal the effectiveness of the passive equilibrium circuit in diverse operating conditions, offering a promising solution for accurate SOC estimation. This research contributes to the advancement of battery management systems, with potential applications in renewable energy storage.

Intelligent Proportional Integral Derivative Control Design for Sampled and Delayed Output Measurements Systems

This paper considers the problem of control systems with sampled and delayed output measurements. Moreover, the considered system is Continuous Time Linear systems (CTLS) which is X-Y robot. The proposed control system design to solve this problem is called Intelligent Proportional Integral Derivative controller (IPID) which has a simple structure. Furthermore, the intelligent technique which is Genetic Algorithm is used to optimize parameters of the proposed controller. In order to restate the continuous state with non-time delay the piecewise estimator observer is utilized. Moreover, an example on MATLAB Simulink is presented to validate the proposed control approach with comparisons of the conventional Proportional Integral Derivative controller and the simulation results are provided to demonstrate its effectiveness.

SIMULACIÓN AVANZADA DE UN BRAZO ROBÓTICO CON 2 GRADOS DE LIBERTAD, CONTROLADO EN SIMSCAPE

In this project, a robotic arm was developed, modeled, and implemented using the Matlab Simulink programming platform. The robotic arm was designed with 2 degrees of freedom and equipped with three motors, allowing for precise and coordinated control of its movements. For simulating the dynamic and kinematic behavior of the arm, Simscape blocks were used, facilitating a detailed three-dimensional representation of the system. The main objective of the project was to demonstrate a simulation of the robotic arm that allows for precise control of the movement angles. Through a detailed 3D simulation in Simscape, the movement and interaction of the arm's components could be visualized, validating its capability to perform tasks with high precision and efficiency. The results obtained demonstrate the effectiveness of using Simulink and Simscape in the design and simulation of robotic systems, highlighting the importance of these tools for automated development.

MPPT Charge Controller using Fuzzy Logic for Battery Integrated with Solar Photovoltaic System

In comparison to other Renewable Energy (RE) resources, solar energy has become the most prominent and prospective source for generating electricity, substituting conventional sources. However, solar Photovoltaic (PV) energy production is dependent on solar irradiance and cell temperature. By implementing the Maximum Power Point Tracking (MPPT) algorithm, it is achievable to maximize the power from solar PV. In spite of this, there is still a slower convergence rate, a significant fluctuation around Maximum Power Point (MPP), and a drift issue caused by rapid irradiance variations in solar PV. In order to prevent oscillation and attain a steady state and continuous output of the PV module, a Fuzzy Logic (FL)-based MPPT has been designed in this work. With the buck converter as the DC-DC converter and the lead acid battery as the input, the Perturb & Observe (P&O) MPPT method is selected. The overall design will be developed using Matlab Simulink, and the efficiency of the FL-MPPT charge controller will be evaluated under constant and step irradiance. Additionally, the battery's State of Charge (SOC) will be monitored to prevent overcharging and discharge. In addition, the effectiveness of the controller will be evaluated with and without the MPPT method. On the basis of simulation results obtained from constant and step irradiance levels, the FL-MPPT charge controller with the P&O algorithm and the lead acid battery as the load was able to maintain maximum system efficiency while extending battery life. The FL-MPPT charge controller obtained about 96% efficiency for both irradiance profiles, whereas the system without the FL-MPPT algorithm only achieved 42% efficiency.

Effect of Load Variation and Fault Resistance on the Operation Time of IDMT Overcurrent Relay

Fault can occur in power system due to many factors such as lightning, tree or crane encroachment, animal intervention, human error etc. Each fault occurrence has its own fault resistance value, and this value is unknown to the protection relay used to the protect the circuit. Besides that, the connected load in power system is dynamic where the value is changing over time. It is very important for the protection relay to be as reliable as it can so that the fault can be isolated as soon as possible when a fault occur. This paper study the effect of fault resistance value and load variation on IDMT overcurrent relay operation time. This relay is used to protect the line from fault occurrence where the higher the fault current, the faster the operation time will be. MATLAB Simulink has been used to model the transmission line, source, connected load and IDMT overcurrent relay. Faults simulations were conducted for various fault resistance and load values and the effects on relay operation time have been analysed. From the results, it was found that, the higher the fault resistance, the higher the operation time while the higher the value of connected load at the end of the line, the faster the relay operation time.

Comparative Simulation Analysis of Electric Vehicle Powertrains with Different Configurations Using AVL Cruise and MATLAB Simulink

Electric vehicles are now recognized as a crucial answer in the worldwide effort to achieve sustainable and environment-friendly transportation. As the automotive industry moves towards using electric power, it is crucial to assess and improve the powertrain configurations in electric vehicles. This study aims to meet this need by conducting an in-depth comparative analysis of single, double, and quad electric vehicle powertrain systems. The performance of these configurations is rigorously simulated by using two widely used platforms: AVL Cruise and MATLAB Simulink. This study mainly covers the analysis of energy efficiency, which is a critical factor in determining the environmental impacts and feasibility of electric vehicles. In order to conduct a thorough comparison, the energy consumption per kilometer is evaluated as a crucial performance measure. Our research primarily focuses on model validation, namely by comparing it with manufacturer data to determine the accuracy and reliability of the simulation results. The findings reveal a compelling narrative in the pursuit of sustainable transportation. The use of a dual motor setup stands out as a prominent example of energy efficiency, demonstrating remarkable outcomes in both simulation platforms. Significantly, these findings closely correspond with the manufacturer's data for the Volvo XC40, confirming the appropriateness and dependability of our simulation models. Furthermore, the quad motor configuration shows significant energy efficiency, providing helpful insight regarding its applicability and performance. The broader implications of this research go beyond powertrain configurations, including the trustworthiness of simulation models in the automotive industry. These findings improve the continuous advancement of electric vehicle design and development, indicating a more environment-friendly and energy-efficient future for the automotive industry. This study offers invaluable insights and benchmarks for the transition to environment-friendly transportation solutions, as the world advances towards sustainable mobility.

Enhanced energy extraction from wind driven PMSG using digital twin model of battery charging system

The pressing need to meet sustainability and climate objectives has prompted a call for expanding the use of renewable energy sources, improving the intelligence and flexibility of electricity grids, and increasing the adoption of electric vehicles and other electricity-powered products. In light of their numerous benefits, widespread electrification and digital technologies can form the basis of energy and climate policy. This research presents an innovative biased transformer and digital twin battery model to support the wind energy based electric vehicle battery charging system. During periods of low and moderate wind, the biased transformer is utilized to increase the voltage for charging electric vehicles. A digital twin of the battery system creates a window into battery charging and aging levels by evaluating the data gathered based on internal resistance. Furthermore, the State of Charge estimation model and different internal resistance estimation algorithms are also exploited. A novel method for precise State of Charge (SOC) estimation in third-gen battery models is presented, integrating Collaborative Gradient Boosting and Adaptive Extended Kalman Filter (AEKF). This approach, implemented in MATLAB Simulink, combines machine learning and adaptive filtering, enhancing accuracy and adaptability for efficient battery management. The functionalities and resilience of both hardware and software of the proposed system are validated under field operation.

SIMULATION STUDY ON PARAMETRIC MODELLING OF MAGNETORHEOLOGICAL DAMPER SYSTEM

The Magnetorheological (MR) damper system serves as a semi-active suspension system designed to absorb road disturbances. This research aims to replicate the MR damper system through a parametric modeling approach, specifically employing the Simple Bouc-Wen Model, Spencer Model, and Hyperbolic-Tangent Model. The objective of this paper is to assess the effectiveness of these modeled MR damper systems with the utilization of a Fuzzy-PID controller. The simulation process is conducted within MATLAB Simulink, whereby a block diagram is devised based on equations related to the suspension system and the parametric models. The inputs for the system encompass sinusoidal and bump road profiles. The outcomes from the modeled MR damper systems reveal that the semi-active suspension system outperforms the passive suspension system. The primary simulation metrics under consideration include sprung displacement, sprung acceleration, and unsprung acceleration. Among the three MR damper models, the Hyperbolic-tangent model displays the most favorable performance, with a mean squared error of 51.44%, while the Bouc-Wen model exhibits the least favorable performance, registering a mean squared error of 25.96%. The integration of the Fuzzy-PID controller demonstrates an enhancement in the sprung suspension system, though the sprung acceleration remains relatively unchanged.

Analytic discrete state-space model of LLC resonant converter

The LLC resonant converter has widely been used for having high-frequency soft-switching capability which could lead to high power density power electronic solutions, and higher power conversion efficiency at lower costs. However, the presence of excessive non-linearity resulting from power conversion through the resonant tank has led to a lack of accurate and reliable large-signal and small-signal models which limits the performance optimization. This paper presents a theoretical analysis of the LLC converter using the sampled-data modeling approach to accurately convert the continuous-time-variant state equations to discrete-time-invariant state equations and solve them using switching time-segmented boundary conditions to obtain the discrete large-signal model. The small-signal model is obtained by perturbation and linearization of the steady-state model in the vicinity of the cyclic equilibrium states of the converter. Theoretical analysis results are validated by simulating a 650W LLC converter in Matlab Simulink. Based on the provided results, the proposed steady-state and small-signal models can accurately predict the dynamic behavior of the LLC converter in different operational conditions.

Performance of MT-I spherical tokamak with upgraded power supplies

This paper describes the upgradation of power supply systems for the improved performance of a small spherical tokamak (MT-I) with an aspect ratio of 1.67 in operation at the Pakistan Tokamak Plasma Research Institute (PTPRI), Islamabad. Three mutually independent power supplies are designed to generate current pulses of desired shape and magnitude in central solenoid (CS), toroidal field (TF) and vertical field (VF) coil systems. The main parts of a power supply are capacitor banks as energy storage devices, ignitrons and thyristors as fast switches for controlled power switching. A double capacitor bank topology with enhanced second capacitor bank voltage is found to be suitable for CS to improve the plasma startup conditions. Simulations are performed in MATLAB Simulink for confirmation of the designed power supply system. The Rogowski coil and current transformers are employed to measure plasma current and the coil’s current waveforms during the experiment in the presence of hydrogen as working gas. An ocean spectrometer and a photron high-speed camera (SA-8) are used for optical measurements and fast plasma imaging. An improvement in startup conditions is observed, enhancing the plasma current duration and light emission intensity recorded in the high-speed camera masked with a Hα filter.