International Journal of Power Electronics and Drive Systems (IJPEDS)
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Artificial neural network-based predictive control for three-phase inverter systems with RLC filters
Get PDFModel predictive control (MPC) is becoming more and more popular in power electronics applications, yet its practical implementation faces challenges due to computational complexity and resource demands. To address these issues, a novel MPC control approach using an artificial neural network (ANN-MPC) is put forth in this research. Using a real-time circuit modeling environment, a power converter with a virtual MPC controller that can regulate both linear and nonlinear loads is first created and run. The input-output data gathered from the virtual MPC is then used to train an artificial neural network (ANN) offline, enabling a simplified mathematical representation that significantly reduces computational complexity. Moreover, the ANN-MPC controller’s adaptability to input variations enhances robustness against system uncertainties. We offer a thorough explanation of the ANN-MPC's fundamental idea, ANN architecture, offline training approach, and online functioning. The suggested controller is validated by simulation with MATLAB/Simulink tools. Performance evaluation of the novel MPC-ANN controller is performed across various scenarios, including linear and nonlinear loads under various operational conditions, and a comparative analysis with conventional MPC is presented
Direct torque control technique for BLDC motor drive in electric vehicle applications
Get PDFIn the field of electric vehicles (EV), the hunt for the appropriate choice of motor and its control technique would be a never-ending process. The brushless DC (BLDC) motors are deployed in electric vehicles on account of higher efficiency, long life, compact size, and higher torque capacity in comparison to other types of motors. The recent advancements in power electronics have assisted in the deployment of BLDC motors in electric vehicles. These applications demand a control mechanism for the motoring mode as well as the regenerative braking mode. During the motoring mode, the power delivered to the motor is controlled, and during the regenerative braking mode, the charging of the battery takes place. Speed control strategy during motoring mode is essential to guarantee the required performance. This paper presents a direct torque control (DTC) technique for BLDC motor control for electric vehicles. The control technique and drive setup are developed to cater to the motoring mode as well as regenerative braking operation as desired for electric vehicles. MATLAB simulation and results are discussed for both modes of operation. Also, the dynamic response of the system is analyzed, which shows an average 1.1 ms response time for a 100 RPM change in speed during speeding up and 0.76 ms response time while speeding down
Optimization of ANN-based DC voltage control using hybrid rain optimization algorithm for a transformerless high-gain boost converter
Get PDFThis paper introduces an adaptive voltage regulation technique for a transformerless high-gain boost converter (HGBC) integrated within standalone photovoltaic systems. A neural network controller is trained and fine-tuned using the rain optimization algorithm (ROA) to achieve improved dynamic behavior under variable solar conditions. The proposed ROA-ANN framework continuously updates the duty cycle to ensure output voltage stability in real time. Validation was carried out using MATLAB–OrCAD co-simulation under multiple scenarios. Comparative results highlight superior performance of the ROA-ANN controller in terms of convergence speed, overshoot minimization, and steady-state response, outperforming conventional PID and ANN-based methods
Effect of gas flow rate on ionizing power characteristics of penning type ion source
Get PDFAn experimental observation on the effect of hydrogen gas flow rate value on ionization power characteristics of penning type ion source has been conducted. The experiments were conducted in the range of gas flow rate values between 3 and 8 sccm, which is a range of discharge that is generally used in cyclotron operations. The characteristic of ionization power is the change in power which is determined from the cathode voltage and cathode current that occurs when the gas flow rate is varied. The fixed operating parameter is the magnetic field at a value of 1.29 T. The characteristic data is presented in graphs and analyzed theoretically. The experiment was conducted at the DECY-13 cyclotron. The results of the analysis show that the effect of increasing the gas flow rate does not significantly affect the characteristics of ionization power. However, further analysis shows that the increase in gas flow rate will have a significant effect on the increase in ion formation rate in the ionization chamber due to a significant increase in the increase in gas pressure in the chamber. The benefit of the results of this study is as an initial capital to increase ion productivity from ion sources
Improvement of DSIM control using fuzzy third-order sliding mode approach optimized by MOA
Get PDFThis study focuses on the contribution of a new hybrid controller based on the sliding mode technique associated with fuzzy logic and optimized by an innovative approach called the mayfly optimization algorithm (MOA) to improve the drive of the dual star induction motor (DSIM). The performance and robustness of this system are analyzed under different operating conditions with three proposed strategies and compared with each other under the MATLAB/Simulink environment. Through the simulation results obtained, we realize that the method that integrates the MOA with a hybrid controller associating the third order sliding mode with fuzzy logic (MOA-FTOSMC) makes a significant contribution to research work in this field and offers the best dynamic performance and adequately manages the uncertainty and variation of the system parameters under different operating regimes
Comparative analysis of various rotor types BLDC motor for residential elevator application
Get PDFBrushless DC (BLDC) motors are widely used in applications where high efficiency is crucial. With advancements in permanent magnet technology, BLDC motors are increasingly suitable for high-torque applications such as residential elevators. Known for their high efficiency, low maintenance, and excellent controllability, BLDC motors are ideal candidates for this research. However, the challenge lies in identifying the most efficient rotor structure that can deliver the required torque for residential elevator applications while maintaining cost-effectiveness and compact design. This paper addresses this problem by simulating various rotor types of BLDC motors using the finite element method (FEM), Ansys Maxwell. four different rotor structures have been analyzed to evaluate their back electromotive force (EMF) and torque. The model generating the highest torque will be selected for manufacturing as a motor for residential elevators. Among the models studied, BLDC-ERA rotor structures produced the highest torque of 28 Nm, while BLDC-HR type generates the lowest torque. To ensure practicality and cost-effectiveness of installing elevators in double-story houses or smaller residences, the selected motor must be compact and affordable, enabling senior citizen to maintain their independence. This research not only aids other researchers in designing suitable motors for elevator applications but also contributes to societal well-being by promoting accessibility and independence for the elderly
Fuzzy logic-based adaptive PLL switching strategy for voltage control in DVR assisted grid tied PV systems
Get PDFThis study aims to enhance power quality in grid-connected photovoltaic (PV) systems by introducing an intelligent fuzzy logic-based adaptive control strategy for dynamic PLL switching in a DVR-supported configuration. A 100-kW grid-tied PV system is modeled with a digital phase-locked loop (DPLL), a conventional synchronous reference frame PLL (CTPLL), and a dynamic voltage restorer (DVR). A Mamdani-type fuzzy inference system (FIS) performs real-time PLL selection based on phase-wise real-time fault monitoring. The system was tested under symmetrical and asymmetrical 20% sag and swell conditions, evaluating voltage stability at both PCC and load, total harmonic distortion (THD), recovery time, and synchronization accuracy. Results show that the proposed method reduces unnecessary DVR voltage injection from ~50 V to ~5-6 V under healthy conditions, maintains a near-unity power factor (< 0.95), and achieves up to 15% THD reduction in inverter current and PCC currents compared to DPLL-only operation. Recovery times improved by up to 25%, with stable synchronization maintained in all fault cases. The integration of adaptive PLL switching and targeted DVR activation offers a novel, hardware-efficient approach to harmonic suppression, voltage stabilization, and fault resilience in medium-scale PV systems
Adaptive ANFIS-based MPPT for PV-powered green ships with high gain SEPIC converter
Get PDFTo align with global climate goals, the International Maritime Organization (IMO) has enforced strict measures to reduce greenhouse gas emissions from the shipping industry by promoting energy efficiency and cleaner propulsion methods. Ship engines remain major contributors to environmental pollution due to their dependence on fossil fuels and inefficient propulsion systems, highlighting the need for clean and sustainable alternatives. This study aims to design a renewable energy-based marine power system that effectively stores and utilizes solar energy, improving overall efficiency and reducing emissions for process innovation. A hybrid setup was developed using photovoltaic (PV) panels, batteries, and a bidirectional DC-DC converter to enable flexible power flow during both charging and discharging cycles. An adaptive neuro-fuzzy inference system (ANFIS)-based maximum power point tracking (MPPT) algorithm was employed alongside a SEPIC converter to enhance energy extraction from the PV system under dynamic conditions. The integrated system achieved a power extraction efficiency of 97.12%, confirming the effectiveness of the ANFIS-based MPPT strategy and showcasing the viability of intelligent renewable energy solutions in maritime applications
An analytical technique for failure analysis and reliability assessment of grid daily outage performance in distributed power system
Get PDFThis paper modeled and analyzed the reliability performance of the 132/33 kV substation in Abuja, Nigeria through the historical data collected from the APO substation using MATLAB 2021b. The probability distribution model was applied to determine the daily feeder’s outage using Reliability, availability, mean time to repair (MTR), Failure rate, distribution indices, and mean time between failures (MTBF). Due to the application of smart energy meters, the use of prepaid energy meters has helped to regulate energy demand, reduce network overloading especially during peak hours, and minimize the cost of energy consumed. There are more forced failures in the distribution system due to the switchgear and Transformer failures. There are more forced failures in the distribution system since 2013, which caused a reduction in the number of interruptions even with an increase in several customers linked to the transmission network. The result shows that the system was most available in the year 2015 with an average service availability index (ASAI) value of 98.9971%. The system was least available in year 2011 with an ASAI value of 98.6558%. The paper recommended that there should be interconnections between different feeders through proper configuration of switches or reclosers, to reduce failure occurrence in the network
Design and simulation of an electric vehicle charging system with battery arrangement and control parameters optimization
Get PDFThe development of electric vehicle (EV) charging technology requires efficient, reliable, and economical systems to address users' concerns about battery drain. This study presents a simplification of EV charger design with an isolated model and optimal battery mode setting. The research method integrates step-up Y-Δ transformers, AC-DC converters, boost DC-DC converters, integral proportional control, and battery configurations. Series (S) - parallel (P) - series (S) battery arrangement pattern to maximize system performance. The test results using a 130 mF capacitor with the S40-P2-S6 and S80-P2-S3 array patterns produced an output voltage of 946 V, while the S100-P2-S3 array pattern achieved an output voltage of 1,182 V. The system is capable of fast charging with a time of 0.2 to 2 hours for a battery capacity of 30 to 100 kWh at a charging power of 50 to 150 kW with an efficiency of up to 97%. The combination of the use of an isolated model on the charger array and the EV battery setting pattern is proven to produce stable voltage values with minimal overshoot levels, thus addressing the complex charger design challenges and battery setting needs in the 800 to 1,100 V voltage range