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Solar energy EV charging system using integrated Zeta-Luo converter

Journal of engineering and Applied Science 2024年第1期71卷 147页

作者： Kancherla, Ananda Babu Prasad, N. Bhanu Kishore, D. Ravi Department of Electrical & amp Electronics Engineering GIET University Gunupur Orissa India Department of Electrical & amp Electronics Engineering GIET Rajahmundry Andhra Pradesh India

This paper focuses on a grid-incorporated solar electric vehicle (EV) charging station that maximizes the acceptance of EVs in agricultural areas and reduces the over-reliance on the grid of urban cities. Since photovoltaic (PV) systems are widely available and easy to install, they are an excellent choice for EV charging applications. Hence, the aim of this work is to combine PV and EV, in order to achieve the objectives of both decarbonized energy generation and transportation. A Modified Zeta Integrated Luo Converter (MZILC), which provides a large conversion range combined with lower voltage stress, is proposed intending to increase the voltage level of the PV system. Furthermore, the converter generates a stable output devoid of fluctuations with the usage of the Grey Wolf–Grasshopper Optimized Proportional Integral (GW-GOPI) controller. Electricity for BLDC motors is generated by PV power during the day and supplied by a single-phase grid at night. The efficiency of the suggested grid-connected PV-based EV charging station is examined in MATLAB environment. © The Author(s) 2024.

关键词： Solar energy

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A heuristic approach for insertion of multiple-complex coefficient-filter based DSTATCOM to enhancement of power quality in distribution system

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Multimedia Tools and Applications 2025年第17期84卷 17741-17767页

作者： Kumar, Rajesh Ashfaq, Haroon Singh, Rajveer Kumar, Rajeev Electrical Engineering Department Jamia Millia Islamia New Delhi India Electrical and Electronics Engineering Department KIET Group of Institutions Ghaziabad India

The advent of non-linear systems has resulted in several power quality challenges, including harmonics, power losses, and voltage swings. To solve these issues, flexible alternating current transmission system components are employed;a distribution static compensator is a key compensatory component of this system. However, under some circumstances, the conventional techniques for deploying distribution static compensators might not always work as well as they should. To address this, a multiple-complex coefficient filter-based optimal design and implementation of a distributed static compensator is suggested. For effective reduction of power losses and improvement of voltage profiles in the distribution system, the suggested solution seeks to position the distribution static compensator effectively. The distribution static compensator is positioned as efficiently as possible using the prairie dog optimization technique, guaranteeing higher power quality. The performance is tested and validated using the MATLAB platform with the IEEE 34 bus test system. With the IEEE 34 bus system under fault conditions with a distribution static compensator, the active power loss is measured at 111.25 kW. The reactive power loss during the distribution static compensator fault is recorded at 80.466 kVAR. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Power quality

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Reconfigurable intelligent surface-empowered MIMO systems

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National Science Review 2023年第8期10卷 11-12页

作者： Ertugrul Basar Department of Electrical and Electronics Engineering Koc University

Fifth-generation(5G) wireless networks,which are being deployed massively worldwide these days, provide higher flexibility and spectrum/energy efficiency compared with their earlier counterparts. However, sixth-generation(6G) wireless networks that are expected to roll out in around 2030 will require more radical communication paradigms,especially at the physical layer of the communication stack.

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A Multilevel Boost DC-DC Converter With MPPT Algorithm For The Rooftop PV System Of The Urban Railway Nhon - Hanoi Station

Journal of Applied Science and Engineering

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Journal of Applied Science and engineering 2025年第11期28卷 2127-2138页

作者： Cuong, Tran Hung Anh, An Thi Hoai Thu Faculty of Electrical & Electronics Engineering Thuyloi University Viet Nam Department of Electrical Engineering University of Transport and Communications Viet Nam

Photovoltaic generators constantly change their maximum power point (MPP) because solar radiation and temperature at different times of the day are always different. The boost DC-DC converter used in energy conversion is controlled when solar radiation and environmental temperature changes are complex. These difficulties make it challenging to design control laws. Fast and reliable step-up DC-DC converters face many obstacles when applied in the field of high-capacity urban trains, causing the current quality of the conversion process to be limited. This paper proposes a multilevel boost DC-DC converter based on MMC configuration, applying the PWM modulation method and INC maximum power point tracking (MPPT) algorithm. MMC boost DC-DC converter can provide an N times conversion ratio and has a much lower operating frequency than conventional Boost Converter. The process of evaluating the effectiveness of the proposed converter configuration and the algorithm is performed on Matlab/Simulink software, and the output parameters of the conversion process are compared with a conventional Boost DC-DC converter based on published analyses. © The Author(’s).

关键词： MATLAB

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Classification of human target movements behind walls using multi-channel range-doppler images

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Multimedia Tools and Applications 2024年第18期83卷 56021-56038页

作者： Acar, Yunus Emre Ucar, Kursad Saritas, Ismail Yaldiz, Ercan Department of Electrical and Electronics Engineering Faculty of Technology Selcuk University Konya42075 Turkey Department of Electrical and Electronics Engineering Faculty of Engineering and Natural Sciences Konya Technical University Konya Turkey

Range-Doppler images represent one of the most informative radar data forms, providing range and frequency information. This study explores the performance of machine learning and deep learning techniques in classifying human activities behind walls using Range-Doppler images. Therefore, we input the HOG features of Range-Doppler images into various machine-learning approaches. Although the HOG feature enhances the performance of machine learning methods, we observe the superior performance of Convolutional Neural Network (CNN) architectures in a more complex scenario in which the number of target activity classes is higher. To obtain sufficient data for the CNN architecture, we combine the Uniform Linear Array (ULA) and stepped-frequency continuous-wave (SFCW) structures, enabling the acquisition of multi-channel data. The experimental results demonstrate both the improvement of the machine learning accuracy from 95.33% to 98.67% through the HOG + Range-Doppler approach and an approximately 6% enhancement in CNN performance achieved through the SFCW-ULA combination. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023.

关键词： Convolutional neural networks

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Artificial intelligence based succored power prediction in stand alone PV system

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Australian Journal of electrical and electronics engineering 2025年第1期22卷 66-79页

作者： Sayeed, Farrukh Ahmed, K. Rafeeq Swamy, S.M. Department of Electrical and Electronics Engineering ACE College of Engineering Thiruvananthapuram India Department of Electronics and Communication Engineering School of Engineering Presidency University Bangalore India Department of AI&ML RT Chennai India

Accurate forecasting of solar power generation is crucial for effective management of renewable energy resources. This literature review emphasises the effectiveness of Artificial Neural Networks (ANNs) in predicting solar energy potential. While traditional ANNs with single hidden layers and predefined neuron configurations have shown success in various applications, they are not suitable for predicting nonlinear time-series databases in the context of this research. The limitations of traditional ANNs in predicting solar power potential necessitate the exploration of alternative approaches. Configuring the structure of traditional ANNs for solar power prediction is a time-consuming process that often requires manual or trial-and-error methods. To address this issue, optimisation techniques are incorporated into the ANN model. Various traditional methods have been explored in this research, but none has achieved satisfactory performance. Drawing from experiences with traditional techniques, a novel Evolution of Cub to Predator (ECP) technique is proposed. The investigation results demonstrate that the incorporation of optimisation techniques yields superior performance compared to traditional ANNs. The proposed ECP technique achieves an impressive prediction accuracy of 97.2%, surpassing existing optimisation techniques. These findings highlight the potential of the ECP technique for accurate solar power prediction and its contribution to optimising renewable energy resource management. ©, Engineers Australia.

关键词： Solar power generation

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Symmetric Parkour Learning for Robust Quadruped Robot Control on Challenging Terrain

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Journal of Institute of Control, Robotics and Systems 2025年第2期31卷 106-113页

作者： Kim, Dong-Ju Park, Jihoon Lee, Inho Department of Electrical and Electronics Engineering Pusan National University Korea Republic of

Parkour tasks on various terrains are challenging for quadruped robots, requiring high levels of adaptability and robustness. This paper presents a novel approach to enable quadruped robots to perform parkour tasks on challenging terrain through symmetric reinforcement learning. We propose a modified PPO (Proximal Policy Optimization) that leverages the robot’s symmetry loss to enhance its stability and improve the efficiency of training convergence. This symmetric learning method brings generalization, allowing the robot to be robust even in previously unseen environments. The effectiveness of our approach is demonstrated through results showing both learning convergence efficiency and robust performance on new, challenging terrains when applying the trained model. © 2025, Institute of Control, Robotics and Systems. All rights reserved.

关键词： Adversarial machine learning

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Impact of organically modified montmorillonite clay nanofiller on free volume and electrical properties of the composites

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Materials Research Innovations 2025年第3期29卷 168-179页

作者： Aradhya, Rashmi B M, Madhu Jagannathan, Sundara Rajan Department of Electrical and Electronics Engineering Siddaganga Institute of Technology Tumakuru India

Polymer nanocomposites are increasingly used in insulation applications for enhanced electrical properties. However, there are intricate parameters that control the properties of the polymer, and hence investigations are required. This paper attempts to correlate the electrical properties of Epoxy/Organically modified montmorillonite clay composites with the free volume resulting from the incorporation of the Organically modified montmorillonite clay filler of 2, 5, and 7 weight per cent (wt.%). Positron annihilation spectroscopy has been used to compute the fractional free volume and free volume. The free volume percentage is observed to increase with the incorporation of 2 and 5 wt.% and reduces at 7 wt.%. A similar trend is observed in the average size of free volume. The filler increases the AC electric breakdown strength by 20%, arc resistance by 5%, and comparative tracking index by 10% at 5 wt.%. Thermal conductivity is seen to increase marginally with the filler. The surfaces of the composites are hydrophilic at 2 and 7 wt.%, and at 5 wt.%, it is hydrophobic. Longer durations of water diffusion render the surfaces of the nanocomposites hydrophobic. Fourier transform infrared spectroscopy investigations reveal broadening of peak, increase in peak intensity and stretching of Si–O–Si bonds at 5 wt.% of filler due to exfoliation. An attempt has been made to understand the results of electrical parameters based on the results of positron annihilation lifetime spectroscopy and thermal conductivity. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Fourier transform infrared spectroscopy

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DG allocation for radial distribution system through optimal sizing in radial power distribution network using hybrid redfox pathfinder optimization

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Multimedia Tools and Applications 2025年第16期84卷 16605-16629页

作者： Chanbasha, Shaik Jayakumar, N. Kumar, N. Bhupesh Assistant Professor Department of Electrical and Electronics Engineering Sir C R Reddy College of Engineering west Godavari Andhra Pradesh Eluru India Lecturer Department of Electrical and Electronics Engineering Government Polytechnic College Tamilnadu Ariyalur India Professor Department of Electrical and Electronics Engineering Sir C R Reddy College of Engineering Andhra Pradesh west Godavari India

To improve the effectiveness of a radial distribution system (RDS) when constant power and impedance loads are present, this research offers a novel optimal model for the placement of distributed generators (DGs). The model considers elements such actual power losses, in addition to the size and placement of the DGs required to match the load requirement. Based on real, the DG's size is chosen, and it is installed at a specified bus to satisfy the load needs. In order to place DG in a RDS with constant load demand on all buses, the bus with the least real power losses, highest accuracy, and greatest sensitivity factor is selected. The suggested method assesses the size and placement of DGs using a Hybrid Red Fox Path Finder Algorithm (RPFO). Using the IEEE 12_bus, 33_bus, and 69_bus RDS, the performance of the suggested system is evaluated and contrasted with that of traditional optimization approaches. The suggested approach is put into practice in MATLAB, and the effectiveness of it is assessed against that of other methods. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Distributed power generation

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Design of Hybrid MPC-PID Controller Based on Fractional Order Model of AMR

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IEEE Access 2025年 13卷 89556-89569页

作者： Celik, Orkan Murat Deniz, Furkan Nur Koseoglu, Murat Inonu University Institute of Science Department of Electrical and Electronics Engineering Malatya44280 Turkey Inonu University Faculty of Engineering Department of Electrical and Electronics Engineering Malatya44280 Turkey

In today's world, robots, especially autonomous mobile robots (AMR), have critical roles in domestic, medical, and industrial applications. As technology develops and the diverse demands emerge, the tasks to be completed by AMRs become more complex and challenging. AMRs need to be improved to struggle with these difficulties. So, implementing more precise and reliable control strategies for robots is becoming increasingly important. To this end, a novel hybrid control methodology, composed of a Proportional-Integral-Derivative (PID) controller and a model predictive controller (MPC), is proposed based on the fractional-order model of the AMR. The MPC optimizes the reference signal for the PID controller, enhancing overall performance. First, the fractional order model of AMR is extracted by considering the input and output data from AMR at different velocity values, eliminating the need for detailed physical modeling and technical information for AMR. After verifying the obtained model, a model reduction technique is applied to simplify the obtained transfer function to reduce the computational burden on the processor of AMR. Then, based on the simplified transfer function a hybrid MPC-PID controller is designed and implemented on Turtlebot3 Burger (TB3) AMR to improve the robot's performance. It is demonstrated that the hybrid controller, which is designed without requiring detailed equations of the system components, exhibits a good performance in minimizing errors and enhancing reliability for both angular and linear velocity values. © 2013 IEEE.

关键词： Three term control systems

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