Simulink Environment Research Articles

Comparison of passive and semi-active piezoelectric transducer damping of cantilever oscillation

The aim of this work is the analysis of passive and semi-active damping methods on the model woven beam with a piezoelectric (PZ) layer. The mathematical model of the PZ layer on cantilever beam is derived. For modeling, real product parameters of PZ layer are used, and through simulation find the optimal values to dampen it. The resistive-inductance passive model, and State-Switch Damping SSD semi-active model are used in this work. The models are processed in the MATLAB Simulink environment and the results of the behavior of the models compared to each other. The program involving passive and semi-active systems, where analyze the behavior of the model for different parameters and the damping capabilities of individual methods are compared. The simulation results show the effectiveness of the semi-active system in comparison with the passive systems, also it shows the passive method is not so effective at low frequency as it in high frequency, and the semi-active method is not optimal for high frequency vibration.

Implementation of NLC‐SHM based novel PWM scheme on packed U‐cell multilevel inverter

AbstractThis article introduces a novel integrated nearest level controller (NLC) combined with selective harmonic mitigation (SHM) control approach aimed at efficiently suppressing lower‐order harmonics has been introduced. The proposed methodology is implemented on the PUC‐7 inverter topology, leveraging the combined benefits offered by both NLC and SHM controllers through a hybrid model. The proposed method demonstrates the capability to reduce lower‐order harmonics up to the 49th harmonic from the load voltage. The particle swarm optimization algorithm is employed to determine optimal switching angles and their corresponding nearest levels, thereby reducing implementation time, computational complexity, and overall system intricacy. The performance analysis of the proposed control strategy across various scenarios, including fluctuations in modulation index and monitoring diverse parameters such as load dynamics has been performed. This approach yields a significant reduction in total harmonic distortion in both load voltage and current. A comparative analysis between NLC, selective harmonic mitigation (SHM), and the integrated NLC‐SHM approach is carried out on the PUC‐7 inverter. The integrated SHM‐NLC control is implemented and validated using the MATLAB Simulink environment, complemented by hardware‐based experimentation, to ascertain its effectiveness.

Experimental Validation of a Novel Hybrid Equilibrium Slime Mould Optimization for Solar Photovoltaic System

Maximizing Power Point Tracking (MPPT) is an essential technique in photovoltaic (PV) systems that guarantees the highest potential conversion of sunlight energy under any irradiance changes. Efficient and reliable MPPT technique is a challenge faced by researchers due to factors such as fluctuations in irradiance and the presence of partial shading. This paper introduced a novel hybrid Equilibrium Slime Mould Optimization (ESMO) MPPT-based algorithm combining the advantages of two recent algorithms, Slime Mould Optimization (SMO) and Equilibrium Optimizer (EO). The ESMO algorithm is compared with highly efficient MPPT-based techniques such as SMO, EO, Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), and Whale Optimization Algorithm (WOA), both under a Simulink environment and a real-time experimental laboratory setup using a Dspace1104 controller and PV emulator. The comparison focuses on performance under several irradiance cases, including instant irradiance change, partial shading, complex partial shading, and dynamic partial shading. The key advantage of ESMO is the fact that it has a single tunable parameter, which makes implementation much easier and, at the same time, reduces the computational resources that are required by the control system. Extensive testing proves the superiority of ESMO over all other techniques, the average efficiency of which is 99.98% under all conditions. Additionally, ESMO provides fast average tracking times of 244 ms under simulation experiments and 200 ms for real-time experiments. These results show that ESMO can be very important for future implementation in large-scale solar PV systems.

A novel dual hysteresis controller for the management of a three phase dynamic voltage restorer

In this work a novel control scheme for the three-phase dynamic voltage restorer has been proposed and validated. The proposed control strategy guarantees the source current waveform to be sinusoidal and at near unity power factor. Further, the voltage sag and swell occurring in the source are overcome and the load gets a smooth power supply at a voltage closer to the rated voltage even in the face of voltage sag or swell occurring in the source. The proposed system uses a power factor corrected front end rectifier that regulates a defined voltage in a DC link. The DVR derives power from the DC link. The PFC rectifier and the DVR converter both are controlled by individual PI and hysteresis current controllers. Further the control system has been adopted in per phase method with actual current estimation system for each phase of the rectifier and the DVR sides done individually. The main advantage of the proposed system is that it does not require the usually required DQ transformation scheme. The proposed idea has been proved to be suitable for balanced and unbalanced loads. The proposed idea has been validated with dynamic simulations carried out in the MATLAB SIMULINK environment and with a scaled down experimental prototype.

Intelligent Efficient Routing and Localization in the Underwater Wireless Sensor Network to Improve Network Lifetime

The inefficiency of the localization process mostly causes delays and operational difficulties in wireless sensor network (WSN) topologies. When localization is suboptimal, the time required for path creation significantly increases, leading to reduced network lifetime and diminished routing efficiency. To address these critical issues, our research focuses on developing a novel procedure that optimizes routing and localization. In this context, localization is the initial step for reaching sensor terminals, followed by activating the routing mechanism. To tackle these issues in Underwater Wireless Sensor Networks (UWSN), the proposed work presents the Elman Bat-based Hello Routing (EBbHR). The primary objective of our research is to locate wireless sensor nodes within the designed UWSN effectively. The process is initiated to achieve this by creating the necessary wireless sensor hubs within the MATLAB Simulink environment. Subsequently, the novel EBbHR function is activated to facilitate the precise localization of all sensor hubs, thereby enhancing the overall data transmission. The success of the designed EBbHR is assessed by considering UWSN factors, and a comparison with current approaches is carried out to show the advancements made by the model.

Optimal Control Strategy to Analyse the Networked Control System Stability

It is crucial to preserve the networked control systems (NCS) transient performance and stability because adding uncertain parameters degrades system performance and introduces instability. Thus, the analysis of NCS system performance under uncertain conditions, such as disturbance, is the focus of this paper. The performance of NCS is demonstrated using control action and some appropriate stability conditions. The simulation diagram in result section displays effectiveness of proposed methodology and shows a comparative analysis of the response signal with and without control action along with disturbance in NCS. Experiments conducted in the MATLAB Simulink environment demonstrate the efficacy of the suggested methodology.

A novel differential protection scheme for AC microgrid based on loss function

Differential protection stands out as the optimal choice for protecting AC microgrids, compared to overcurrent and distance-based schemes, because of its adaptability to different network topologies, ability to manage bi-directional power flow, and better selectivity for system transients and variable fault current. However, high impedance faults, time synchronization error, and high bandwidth communication requirements are significant challenges faced by differential protection schemes. Considering such issues, this paper has proposed a novel differential protection scheme based on loss function (Percentage Bias Error), evaluated by using line's both end superimposed positive and negative sequential currents magnitude, which enhances the sensitivity in identifying internal fault that occurs in either grid-connected or islanded microgrid mode of operation. Its effectiveness is validated on ring and radial distribution networks with high impedance fault (500 Ω) at different fault locations. Additionally, the relaying scheme is stable under different system transients, CT error in noisy environments, and robust for time synchronization error. Moreover, the proposed scheme is compared with the existing techniques to illustrate its high sensitivity, fast operation (within one cycle), and high accuracy. The proposed scheme is simulated in a MATLAB Simulink environment, and results are validated using a laboratory-level hardware setup.

Rule‐based energy management system for autonomous voltage stabilization in standalone DC microgrid

AbstractThis paper presents a rule‐based energy management system (EMS) designed for a standalone DC microgrid incorporating solar photovoltaic (PV), fuel cell, battery energy storage system (BESS), and electric vehicle. The unpredictable nature of renewable energy sources and the instability of loads pose challenges for maintaining DC bus voltages and power‐sharing arrangements, impacting the microgrid's smooth operation. The proposed EMS aims to ensure power balance between generation and demand, mitigating vulnerabilities of the DC bus to voltage instability caused by fluctuations from both the load and source sides. This is achieved through an autonomous DC bus voltage stabilization strategy, involving the maintenance of a nominal state of energy (SoE) for the BESS and hydrogen fuel consumption for the fuel cell within predefined lower and upper limits. By regulating these two factors, the EMS algorithm facilitates optimal performance of the PV, battery, and fuel cell components. Consequently, the EMS provides decision‐making instructions to each individual energy source, ensuring efficient operation under various conditions. The effectiveness of the proposed EMS is evaluated through hardware‐based testing on a DC microgrid and simulations in the MATLAB Simulink environment across multiple operating scenarios.

A new solution for tackling mismatching losses in solar PV array via image encryption

Solar photovoltaic systems may undergo changes in power generation due to environmental factors such as partial shadowing, resulting in losses due to mismatch. This can ultimately lead to a decrease in the efficiency of the system's power conversion. While current solutions are both cost-effective and efficient, there is potential for novel approaches to further enhance system performance by improving consistency, power production, and minimizing mismatch losses. To address these limitations, this paper proposes the utilization of a highly efficient generalized Arnold's cat Map technique, commonly used in the image encryption process, to reconfigure the PV array. The effectiveness of these proposed approaches is evaluated in a MATLAB Simulink environment, specifically for a symmetrical (8x8) PV array, under various benchmark conditions such as Long wide; Short wide, Long Narrow, and Short Narrow shading conditions. The results obtained from these evaluations are then compared to prominent strategies such as Total-cross-tied and the recently reported Chaotic Baker's Map reconfiguration techniques. Furthermore, extensive analysis is conducted using different performance indices to gain a comprehensive understanding of the proposed approaches.

Accurate design, simulation and implementation of AC/DC inductors for power electronic converters

AbstractThis article proposes a holistic and improved methodology for the inductors' design in power electronic circuits operating at high frequencies. This methodology includes an analytical design, a finite element modeling of the electromagnetic behavior with JMAG software, a simulation analysis in a Simulink environment, and experimental verification of the effectiveness of inductor design in a laboratory‐scale step‐up boost power converter prototype. The holistic approach allowed us to achieve all target specifications such as maximum power (300 W), minimum voltage (60 V), inductance (1.77 mH), and maximum current ripple (1 A). It guarantees the losses' minimization in core and copper (21.47 W), and marginal errors below 4% between the analytical, simulated, and experimental values.

Review and modeling on hydrogen fuel cells electric vehicle (HFCEV), in comparison with battery electrical vehicle (BEV) using MATLAB environment. Case study: Postal car

This research puts forward the modeling of a Hydrogen Fuel Cell Electric Vehicle (HFCEV) and its validation, in comparison with battery electrical vehicle (BEV) based on a postal vehicle and its subsystems. The main investigation parameters are the amount of hydrogen consumed, and the change in the state of charging of the battery. For the profile of the same speed route, an HFCEV model and a BEV model, consisting of multiple subsystems, were developed, and simulated in the MATLAB® Simulink environment. We make use of various sources of drive cycles to obtain our outcomes such as the New European Diving Cycle (NEDC). By running simulations for different stages, we are able to generate simulation results. The discrepancies in the graphs and the visual demonstrations guided us to variable conclusions on how different factors affect an electric vehicle’s performance and efficiency. The simulation result shows that the (BEV) is 30% more effective for NEDC drive cycle comparing with (HFCEV).

Innovative real-time deloading approach to wind systems with applications in primary frequency control

The integration of wind systems into the electrical grid faces a significant challenge due to the absence of inertia, a fundamental characteristic of this system. This lack of internal inertia directly impacts frequency stability. To address this challenge, various techniques have been developed, including storage systems, inertia emulation, and deloading methods, among others. Among these approaches, the latter method appears to be more suitable. This study introduces a novel deloading approach that offers several advantages. The proposed strategy is an online technique that is easy to implement. It does not necessitate mathematical models, estimations, prior knowledge of wind turbine (WT) characteristics, or the use of an extra sensor, thereby simplifying the approach. This approach is based on a WT cycle consisting of two consecutive operating modes: a maximum power measurement (MPM) mode and a power reserve (PR) mode. These modes are controlled by two controllers: a pitch angle controller (PAC) and a perturb and observe (P&O) algorithm controller. The cycle is managed and initiated using a monitoring signal with multiple configurations, providing various solutions and implementation possibilities. The effectiveness of this approach has been verified through numerous simulation tests conducted on both finite and isolated grids. These simulations employ theoretical and actual wind speed signals in the MATLAB Simulink environment, confirming the practicality and reliability of the proposed method.

Определение диссипативных потерь в гидравлическом приводе газораспределительного механизма двигателя внутреннего сгорания

Controlling the opening and closing times of intake and exhaust valves can improve the efficient parameters of an internal combustion engine and reduce the toxicity of combustion products. The valves are moved by an electronically controlled hydraulic drive. The energy consumption for the operation of a hydraulic valve drive is greater than when using a traditional mechanical drive. The dissipative energy losses in the accumulator one-way hydraulic valve drive are investigated. The working fluid of the hydraulic drive is SAE 5W-30 motor oil. The oil pressure behind the pump is 8 MPa, the diameter of the hydraulic cylinder is 16 mm. The main items of energy consumption are identified, and a methodology for their determination is proposed. The assessment of the efficiency of the hydraulic drive was based on the law of conservation of energy. To determine energy costs, a hydraulic drive model was compiled in the Simulink environment. A law of valve movement similar in shape to trapezoidal was obtained. The maximum speed of valve movement during the opening process is 4 m/s, during the closing process 3.8 m/s. During the period when the valve is held near the maximum lift of 14 mm, free oscillations with an amplitude of about 1 mm are observed. The energy consumption for a single actuation of the valve, which has a progressively moving mass of 0.5 kg, amounted to 25.9 J. Of this, a little more than 70% is spent on filling the hydraulic cylinder with liquid, the rest is spent when emptying it. As a result of throttling the fluid flow in the hydraulic cylinder rod stroke limiter and hydraulic brake, 56% of the energy is lost. Large energy losses are observed between the hydraulic accumulators and the hydraulic cylinder. When the cylinder is filled, 21.1% is lost here, and when it is emptied, 10.4%. Increasing the capacity of the supply and drain lines between hydraulic accumulators and hydraulic cylinders allows you to increase the speed of opening and closing valves. The main ways to increase the energy efficiency of the drive are to shift the hydraulic accumulators to the hydraulic cylinder, increase the diameter of the connecting lines, and increase the throughput of the solenoid valves.

PV system applied on the new PUC-NPC inverter

In this article, the authors present a new competitive Packed-U-cell and neutral point clamped (PUC-NPC) 9-level converter that utilizes a small number of power switches and passive components. Only seven switches are added to a single DC source. However, the proposed converter takes benefits of the neutral point clamped (NPC) converter’s capability to connect capacitors in series, all with a simple control that enables the algorithm associated to the proposed inverter operate correctly in an open loop operation. A technique of pulse width modulation (PWM) is employed to maintain capacitor voltage at desired values. The proposed inverter produces an almost sinusoidal waveform output voltage, as result, a perfectly sinusoidal charge current with minimal impact on the economy and energy consumption are optioned. The converter has been integrated with a photovoltaic system to minimize its impact on the electricity supply and enhance energy efficiency. In order to take a maximum power from the photovoltaic panel, authors employ a maximum power point tracking (MPPT) technique based on disturbance and observe (P and O). When combined with the proposed control technique, it offers a competitive system suitable for standalone use or as an energy source, eliminating the need for PI regulators or additional investments. The proposed 9-level converter has been validated through simulation, utilizing the MATLAB Simulink environment to model the proposed system. Dynamics of this later were verified by changing the load charge.

Derating factor determination of the three‐phase induction motor under unbalanced voltage using pumping system

AbstractA novel method is presented for determining the derating factors of a three‐phase induction motor under the condition of the unbalanced supply voltages. In this method, a mechanical system is used which consist of the a centrifugal pump, two valves, a DC motor, which are connected to the shaft of the three‐phase induction motor. A sliding mode control system is used for position control of the DC motor for adjusting the valve angle for derating the induction motor. The authors present the results of an experiment in which a three‐phase induction motor was subjected to various unbalanced voltage conditions. The results of simulations were used to look into what happened when there were different levels of imbalanced voltage. This was done to determine how these situations changed an induction motor's speed, torque, and efficiency. For this system, the stator current would be greater than the rated current if there was an imbalance in the supply voltage. Therefore, to reduce the amount of power that the three‐phase induction motor can produce, the control system uses a DC motor to reduce the angle of one of the two valves. This decreasing angle continues until the root mean square value of the stator current returns to the rated current. At this point, the derating factor may be calculated by dividing the output power of the three‐phase induction motor in the unbalanced condition by the output power when there are ideal sinusoidal. The MATLAB SIMULINK environment is utilised to perform simulations of the proposed system.

Modeling electric Vehicle's and improving battery lifetime using AI tools case study: Postal cars

The rapid development in the field of electric vehicles requires a careful evaluation of the design process. The presence of a simulation model of the electric vehicle can effectively detect many faulty areas during the development process without risks. The MATLAB and Simulink environment is considered one of the most important tools used in the simulation process. In this paper, we will present the model of electric car used for transporting postal parcels (postal cars). The model includes simulating the operation of a permanent magnet synchronous electric motor. We will assume that the car is moving according to a driving cycle. The results will show the torque forces required to achieve the required speed. We will further calculate the traction and the resistance forces during the driving cycle and the engine efficiency in addition. Perhaps the most important problem facing electric car designers is calculating the amount of energy consumed from the battery or hydrogen fuel, and this is what was achieved as the result of the simulation process in this research. In the end, use one of the artificial intelligence tools (fuzzy controller) to improve battery life by providing the electric car driver with an alert system that will increase the ability to monitor the battery condition and thus increase battery life. The benefit of this paper emerges in realizing the importance of modeling and using simulation using artificial intelligence in developing the design of the electric car, specially the electric motor and battery size, and thus achieving one of the most important goals of the United Nations of preserving the environment and reducing carbon emissions.

Frequency stabilization in microgrid with PV system based on maximum power extraction: A sliding mode approach

The article addresses the critical issue of frequency regulation in microgrids (MG) integrated with solar photovoltaic (PV) systems, which rely on maximum power point tracking (MPPT) using sliding mode control (SMC). The frequency stability of MGs is a significant concern due to the inherent variability of renewable energy sources, making frequency regulation challenging. This research proposes a dual-objective control strategy. Firstly, it ensures the solar PV system maximizes power extraction via a buck-boost converter controlled by SMC. Simultaneously, it maintains frequency regulation in the MG under load disturbances using SMC. The SMC technique guarantees precise convergence to the maximum power operating point and minimizes frequency deviations in the MG. The proposed solution demonstrates effective maximum power extraction under varying irradiance levels and reliable frequency regulation despite system parameter uncertainties and nonlinearities such as generation rate constraints (GRC) and governor deadband (GDB). Additionally, the SMC-based design achieves faster convergence compared to traditional proportional-integral (PI) controllers optimized using intelligent techniques. Stability analysis, performed using Bode and Nyquist plots, further confirms the robustness of the proposed system. The model was developed and tested in the MATLAB Simulink environment, showcasing its efficacy and reliability.

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.

Swarm of Drones for Surveillance Monitoring of a Grounded Target: An event-triggered approach

In this paper, we present a novel formation control approach in the framework of Event-Triggered (ET) control to provide a solution to the surveillance problem. To do this, we identify two main challenges which are the switching topology of the drones and the limited bandwidth of the communication network, which are also valid in formation applications. To provide a solution to switching topologies, we propose a networked continuous controller that is robust in the presence of connection switching between drones and the target. Then, we propose a networked controller with ET communication in some aperiodic instants which reduces the required bandwidth and load within the communication network. We guarantee the stability of the developed ET controller and prove that the Zeno behavior cannot occur. To validate the method, we present realistic 3D simulation results conducted in the Simulink environment of Matlab® for different scenarios. The results of the study show the effectiveness of the proposed controller, especially for limited bandwidth channels as the ETC scheme has decreased the load within the communication network while resulting in a robust and efficient formation performance. We also considered moving target scenarios with missing possibilities to validate the robustness of the proposed method.

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.