Search Results (1,743)

At higher current densities, the bubble effect in the anode flow field of the PEM electrolyzer (PEM EL) worsens mass transfer losses and energy consumption. This study employs a moderate increase in the water flow rate to remove accumulated bubbles under fluctuating electrical input, thereby improving PEM EL system efficiency. An enhanced PEM EL equivalent circuit model incorporating bubble over-potential based on the oxygen volume fraction is developed. Considering the energy consumption of auxiliary equipment and the reduction in losses from mitigating the bubble effect, a numerical simulation evaluates the impact of flow rate variations on overall electrolysis energy consumption, leading to a comprehensive energy consumption model for the PEM EL system, incorporating electrical, chemical, and thermal energy conversions. The control objective is to maximize system efficiency by optimizing the water flow rate, with a performance-preset-based controller implemented in MATLAB/Simulink. The simulation results show that the controller can accurately track the target flow rate, and the dynamic regulation time improved by 1.5 s compared to the traditional performance constraint function, better matching the rate of change in electrical energy. Under the water flow control mode, hydrogen production increased by 6.6 L within 130 s of the simulation, available energy increased by 8.32 × 10⁶ J, and the efficiency of the PEM EL system improved by 2.79%. Full article

Unmanned aerial vehicle (UAV) technology has recently experienced increasing development, leading to the creation of a wide variety of autonomous solutions. In this paper, a guidance strategy for straight and orbital paths following fixed-wing small UAVs is presented. The proposed guidance algorithm is based on a reference vector field as desired, with 16 courses for the UAV to follow. A sliding mode approach is implemented to improve the robustness and effectiveness, and the asymptotic convergence of the aircraft to the desired trajectory in the presence of constant wind disturbances is proved according to Lyapunov. The algorithm exploits the banking dynamics and generates reference signals for the inner-loop aileron control. A MATLAB&Simulink^® simulation environment is used to verify the performance and robustness of the compared guidance algorithms. This high-fidelity model considers the six-degrees-of-freedom (DoF) whole-flight dynamics of the UAV and it is based on experimental flight test data to implement the aerodynamic behavior. Full article

In this paper, the performance of a Dual-Stator Winding Synchronous Reluctance Generator (SynRG) suitability for off-grid wind power generation is analyzed. The rotor of the SynRG has a slitted-rotor core to improve selected vital performance parameters. The SynRG with a slitted-rotor core was modeled using a two-dimensional (2D) Finite Element Method (FEM) to study the electromagnetic performance of key parameters of interest. To validate the FEA results, a prototype of the SynRG with a slitted rotor was tested in the laboratory for no-load operation and load operation for unity, lagging, and leading power factors. To evaluate the capability of the SynRG with a slitted-rotor core to operate in a wind turbine environment, the machine was modeled and simulated in Matlab/Simulink (R2023a) for dynamic responses. The FEA results reveal that the SynRG with a slitted-rotor core, compared with the conventional SynRG with the same ratings and specifications, reduces the torque ripple by 24.51%, 29.72%, and 13.13% when feeding 8 A to a load with unity, lagging, and leading power factors, respectively. The FEA results also show that the induced voltage on no-load of the SynRG with a slitted-rotor core, compared with the conventional SynRG of the same ratings and specifications, increases by 10.77% when the auxiliary winding is fed by a capacitive excitation current of 6 A. Furthermore, the same results show that with a fixed excitation capacitive current of 6 A, the effect of armature reaction of the SynRG with a slitted-rotor core is demagnetizing when operating with load currents having a lagging power factor, and magnetizing when operating with load currents having unity and leading power factors. The same patterns have been observed in the experimental results for different excitation capacitance values. The Matlab/Simulink results show that the SynRG with a slitted-rotor core has a quicker dynamic response than the conventional SynRG. However, a well-designed pitch-control mechanism for the wind turbine is necessary to account for changes in wind speeds. Full article

The transition to renewable energy sources is vital for achieving sustainability, and photovoltaic (PV) systems play a key role in this shift. However, their performance can be significantly affected in snowy conditions, where the irradiation and energy production are limited. This study addresses a critical gap in the literature by developing a MATLAB/Simulink model that considers the impacts of snow layering and removal on roof-mounted photovoltaic arrays. This study investigates various module interconnection schemes—including Series, Series-Parallel, Total-Cross-Tied, Bridge-Linked, and Honey-Comb—to determine their impact on energy efficiency in snowy environments. Based on the results, when the modules are fully covered by uniform snow, the power losses can increase from 38.9% to 93.2% for all interconnection schemes by increasing the accumulated snow from 1 cm to 5 cm. When the modules are covered by nonuniform snow and the snow removal is considered the TCT scheme has the minimum power losses and the maximum efficiency, depending on the accumulated snow pattern. For the worst scenario, the power loss is 70.1% for TCT, 71.7% for SP, 72% for HC, 72.3% for BL, and 76.7% for series interconnection. For the other scenarios, almost a similar trend can be observed where the TCT interconnection has the maximum efficiency, and the series interconnection has the minimum efficiency. Full article

The onboard circuits of EV chargers comprise heat-producing electronic devices such as MOSFETs and diodes for switching and power conversion operations. A heatsink must dissipate this generated heat to extend the devices’ life and prevent component thermal stress or failure. This study primarily investigates the optimal heatsink geometry and pin configuration, which offers the most efficient temperature versus cost performance. MATLAB/Simulink (R2024a) was used to model a Level 1 charger using eight MOSFETs and four diodes. Various heatsink geometries were modeled using the ANSYS (2024 R1) Workbench and Fluent software to optimize the sink’s thermal performance. The analyses were performed under transient conditions using natural and forced cooling scenarios. The 2 mm wide plate fin heatsink with 44 fins yielded the best result. Further enhancement of the best-performing naturally cooled model improved the switches and diodes temperatures by 14% and 4%, respectively. The performance of the heatsink was further improved by applying a cooling fan to achieve an up to 25% diode and 40% MOSFET thermal dissipation efficiency. The results of this study show that the most efficient cooling performance and cost are realized when the optimum combination of fin spacing, proximity from the cooling fan, and fin geometry is selected. Full article

DC micro-grids are emerging as a promising solution for efficiently integrating renewable energy into power systems. These systems offer increased flexibility and enhanced energy management, making them ideal for applications such as heat pump (HP) systems. However, the integration of intermittent renewable energy sources with optimal energy management in these micro-grids poses significant challenges. This paper proposes a novel control strategy designed specifically to improve the performance of DC micro-grids. The strategy enhances energy management by leveraging an environmental mission profile that includes real-time measurements for energy generation and heat pump performance evaluation. This micro-grid application for heat pumps integrates photovoltaic (PV) systems, wind generators (WGs), DC-DC converters, and battery energy storage (BS) systems. The proposed control strategy employs an intelligent maximum power point tracking (MPPT) approach that uses optimization algorithms to finely adjust interactions among the subsystems, including renewable energy sources, storage batteries, and the load (heat pump). The main objective of this strategy is to maximize energy production, improve system stability, and reduce operating costs. To achieve this, it considers factors such as heating and cooling demand, power fluctuations from renewable sources, and the MPPT requirements of the PV system. Simulations over one year, based on real meteorological data (average irradiance of 500 W/m², average annual wind speed of 5 m/s, temperatures between 2 and 27 °C), and carried out with Matlab/Simulink R2022a, have shown that the proposed model predictive control (MPC) strategy significantly improves the performance of DC micro-grids, particularly for heat pump applications. This strategy ensures a stable DC bus voltage (±1% around 500 V) and maintains the state of charge (SoC) of batteries between 40% and 78%, extending their service life by 20%. Compared with conventional methods, it improves energy efficiency by 15%, reduces operating costs by 30%, and cuts CO₂; emissions by 25%. By incorporating this control strategy, DC micro-grids offer a sustainable and reliable solution for heat pump applications, contributing to the transition towards a cleaner and more resilient energy system. This approach also opens new possibilities for renewable energy integration into power grids, providing intelligent and efficient energy management at the local level. Full article

The fiber-optical current transformer (FOCT) is the core measuring equipment of the flexible DC converter station, which affects the operation control of the system. In order to solve the problem of the influence of the abnormal FOCT on the operation of the converter valve being unclear, the common fault modes of temperature and optical path of the FOCT are analyzed in this paper. Then, based on the traditional optical current transformer (OCT) model and considering the influence of temperature parameters on the FOCT, the FOCT dynamic model considering multiple factors is constructed. Finally, the simulation analysis is carried out on the MATLAB 2021b/Simulink platform, and the results show that (1) when the FOCT temperature compensation is abnormal, the transmission power of the converter valve increases with the increase in temperature, but the increase in temperature change is small; (2) when the FOCT light source compensation is abnormal, the light source attenuates, the converter valve active power decreases, and the reactive power increases; and (3) when the optical fiber sensing ring is broken, the transmission power increases and seriously deviates from the preset value (the active power increases by about 87.5% and the reactive power increases by about 90%). It can be seen that the abnormal FOCT in the converter station has a serious influence on the operation of the converter valve. Full article

As a representative of multi-functional engineering machinery, the excavator is irreplaceable in the field of engineering construction. To autonomously control the excavator bucket, it is essential to control the position of the bucket hydraulic cylinder. As a consequence of the problem of position tracking control spawned from external disturbance and other factors in the self-mining servo system of excavators, a strategy of sliding mode backstepping control based on the particle swarm optimization algorithm and neural network disturbance observer (PSO-NNDO-SMBC) was recommended accordingly. Meanwhile, the complex disturbance was estimated online and compensated for by the system control input by the universal approximation property of the neural network disturbance observer (NNDO). Afterwards, the uncertainty of control parameters was optimized by the particle swarm optimization algorithm (PSO) and was fed back to the controller parameter input end. Afterwards, a co-simulation model of MATLAB/Simulink (MATLAB2023b) and AMESim (Simcenter Amesim 2304) was established for simulation analysis, and a test bench was set up for comparison and verification. As proven by the experimental results, PSO-NNDO-SMBC possessed strong anti-interference ability. In contrast to the sliding mode backstepping control based on the particle swarm optimization algorithm (PSO-SMBC), the maximum displacement tracking error was lowered by 50.5%. Furthermore, in comparison with the Proportional-Integral-Derivative (PID), the maximum displacement tracking error was decreased by 75.2%, which tremendously optimized the control accuracy of excavator bucket displacement tracking. Full article

This paper investigates the feasibility of hydrogen-powered hybrid electric vehicles as a solution to transportation-related pollution. It focuses on optimizing energy use to improve efficiency and reduce emissions. The study details the creation and real-time performance assessment of a hydrogen hybrid electric vehicle (HHEV)system using an STM32F407VG board. This system includes a fuel cell (FC) as the main energy source, a battery (Bat) to provide energy during hydrogen supply disruptions and a supercapacitor (SC) to handle power fluctuations. A multi-agent-based artificial intelligence tool is used to model the system components, and an energy management algorithm (EMA) is applied to optimize energy use and support decision-making. Real Global Positioning System (GPS) data are analyzed to estimate energy consumption based on trip and speed parameters. The EMA, developed and implemented in real-time using Matlab/Simulink(2016), identifies the most energy-efficient routes. The results show that the proposed vehicle architecture and management strategy effectively select optimal routes with minimal energy use. Full article

The significance of the Hybrid Renewable Energy System (HRES) is profound in the current scenario owing to the mounting energy requirements, pressing ecological concerns and the pursuit of transitioning to greener energy alternatives. Thereby, the modeling and design of HRES, encompassing PV–WECS–Battery, which mainly focuses on efficient power conversion and advanced control strategy, is proposed. The voltage gain of the PV system is improved using the Re-lift Luo converter, which offers high efficiency and power density with minimized ripples and power losses. Its voltage lift technique mitigates parasitic effects and delivers improved output voltage for grid synchronization. To control and stabilize the converter output, a Proportional–Integral (PI) controller tuned using a novel hybrid algorithm combining Grey Wolf Optimization (GWO) with Hermit Crab Optimization (HCO) is implemented. GWO follows the hunting and leadership characteristics of grey wolves for improved simplicity and robustness. By simulating the shell selection behavior of hermit crabs, the HCO adds diversity to exploitation. Due to these features, the hybrid GWO–HCO algorithm enhances the PI controller’s capability of handling dynamic non-linear systems, generating better control accuracy, and rapid convergence to optimal solutions. Considering the Wind Energy Conversion System (WECS), the PI controller assures improved stability despite fluctuations in wind. A Recurrent Neural Network (RNN)-based battery management system is also incorporated for accurate monitoring and control of the State of Charge (SoC) and the terminal voltage of battery storage. The simulation is conducted in MATLAB Simulink 2021a, and a lab-scale prototype is implemented for real-time validation. The Re-lift Luo converter achieves an efficiency of 97.5% and a voltage gain of 1:10 with reduced oscillations and faster settling time using a Hybrid GWO–HCO–PI controller. Moreover, the THD is reduced to 1.16%, which indicates high power quality and reduced harmonics. Full article

Test plants or laboratory prototypes are essential for developing training activities in engineering. In the field of automation and control, simulators or high-fidelity equipment models commonly used in industrial processes are necessary. These tools allow engineering trainees to gain experience working with devices similar to those they will encounter in their professional contexts. This paper presents the design and simulation of a fly-cutting plant for academic use. A 3D model was developed in SketchUp, incorporating features typical of industrial plants. The system’s simulation was carried out in MATLAB R2023b using mathematical modeling. The primary contribution of this work is the design of a low-cost, compact industrial prototype that includes a conveyor belt and a continuous cutting mechanism, enabling the understanding and operation of large-scale industrial processes. Performance tests were conducted using MATLAB, Simulink, and Code Composer Studio. Subsequently, operational and cutting tests were performed using classical control techniques. Additionally, the design features of the fly-cutting plant, which can be easily implemented for process control training activities, are detailed. Full article

The paper addresses the dynamic modeling and numerical simulation of a novel single-rotor wind system with a planetary speed increaser and counter-rotating direct current (DC) generator, patented by authors, during the transient stage from rest. The proposed analytical dynamic algorithm involves the decomposition of the wind system into its component rigid bodies, followed by the description of their dynamic equations using the Newton–Euler method. The linear mechanical characteristics of the DC generator and wind rotor are added to these dynamic equations. These equations allow for the establishment of the close-form equation of motion of the wind system and, implicitly, the time variation of the mechanical power parameters. Numerical simulations of the obtained analytical dynamic model were performed in MATLAB-Simulink in start-up mode from rest for the case study of a 100 kW wind turbine. These results allowed highlighting the time variation of angular velocities and accelerations, torques, and powers for all system shafts, both in the transient regime and steady-state. The implementation, in this case, of the counter-rotating generator indicates a 6.4% contribution of the mobile stator to the generator’s total power. The paper’s results are useful in the design, virtual prototyping, and optimization processes of modern wind energy conversion systems. Full article

Research in renewable energy sources and microgrid systems is critical for the evolving power industry. This paper examines the operational behavior of both pico- and nano-grids during transitions between grid-connected and islanded modes. Simulation results demonstrate that both grids effectively balance the power flow, regulate the state of charge (SOC), and stabilize the voltage during dynamic operational changes. Specific scenarios, including grid disconnection, load sharing, and weather-based energy fluctuations, were tested and validated. This paper models both pico-grids and nano-grids at the Singapore Institute of Technology Punggol Campus, incorporating solar PVs, energy storage systems (ESSs), power electronic converters, and both DC and AC loads, along with utility grid connections. The pico-grid includes a battery storage system, a single-phase inverter linked to a single-phase grid, and DC and AC loads. The nano-grid comprises solar PV panels, a boost converter, a battery storage system, a three-phase inverter connected to a three-phase grid, and AC loads. Both the pico-grid and nano-grid are configurable in standalone or grid-connected modes. This configuration flexibility allows for a detailed operational analysis under various conditions. This study conducted subsystem-level modelling before integrating all components into a simulation environment. MATLAB/Simulink version R2024b was utilized to model, simulate, and analyze the power flow in both the pico-grid and nano-grid under different operating conditions. Full article

Short-circuit currents in autonomous and isolated electrical complexes today are approaching the switching capacity of operated circuit breakers. Since the existing equivalents cannot ensure the necessary reliability of power supply to consumers in emergency situations, it is pertinent to assess the need for developing new types of current-limiting devices (CLDs). This paper proposes an electrical circuit of a semiconductor current-limiting device based on a step-down DC-DC converter, where the main switch is a thyristor with an artificially switched circuit. Transient processes during the operation of the device are considered in detail. A mathematical model of the device is also provided. This model was verified by modeling the CLD circuit in MATLAB Simulink. In turn, the validity of the computer model used was proven experimentally. During the experiments, the current-limiting efficiency of the circuit was demonstrated, and its proposed mathematical model was also confirmed. This research was carried out as part of the project within the State Assignment FSEG-2023-0012. Full article

The elevated penetration of renewable energy has seen a significant increase in the integration of inverter-based resources (IBRs) into the electricity network. According to various industrial standards on interconnection and interoperability, IBRs should be able to withstand variability in grid conditions. Positive sequence voltage-oriented control (PSVOC) with a feed-forward decoupling approach is often adopted to ensure closed-loop control of inverters. However, the dynamic response of this control scheme deteriorates during fluctuations in the grid voltage due to the sensitivity of proportional–integral controllers, the presence of the direct- and quadrature-axis voltage terms in the cross-coupling, and predefined saturation limits. As such, a twin delayed deep deterministic policy gradient-based voltage-oriented control (TD3VOC) is formulated and trained to provide effective current control of inverter-based resources under various dynamic conditions of the grid through transfer learning. The actor–critic-based reinforcement learning agent is designed and trained using the model-free Markov decision process through interaction with a grid-connected photovoltaic inverter environment developed in MATLAB/Simulink^® 2023b. Using the standard PSVOC method results in inverter input voltage overshoots of up to 2.50 p.u., with post-fault current restoration times of as high as 0.55 s during asymmetrical faults. The designed TD3VOC technique confines the DC link voltage overshoot to 1.05 p.u. and achieves a low current recovery duration of 0.01 s after fault clearance. In the event of a severe symmetric fault, the conventional control method is unable to restore the inverter operation, leading to integral-time absolute errors of 0.60 and 0.32 for the currents of the d and q axes, respectively. The newly proposed agent-based control strategy restricts cumulative errors to 0.03 and 0.09 for the d and q axes, respectively, thus improving inverter regulation. The results indicate the superior performance of the proposed control scheme in maintaining the stability of the inverter DC link bus voltage, reducing post-fault system recovery time, and limiting negative sequence currents during severe asymmetrical and symmetrical grid faults compared with the conventional PSVOC approach. Full article