Ravivarman Shanmugasundaram

@vardhaman.org

PROFESSOR, EEE
Vardhaman College of Engineering



                    

https://researchid.co/ravivarmans
13

Scopus Publications

76

Scholar Citations

3

Scholar h-index

2

Scholar i10-index

Scopus Publications

  • AI-empowered smart electricity system with predictive maintenance integration
    L. Karthick, Laxmi Mishra, Ganesh Babu L., Ravivarman Shanmugasundaram, S. Saravanan, and Sanjeev Kumar Trivedi
    IGI Global
    The growing popularity of 6G-enabled internet of things (IoT) is addressing persistent challenges in long-term applications. Large-scale knowledge analytics requires real-time, accurate data analysis from AI. When utilizing artificial intelligence for in-depth data analysis, challenges emerge in safety, confidentiality, teaching data, and integrated architecture. This study recommends combining blockchain and artificial intelligence for internet of thinking applications. The suggested architecture is evaluated qualitatively and quantitatively. The authors measure blockchain and AI's problem-solving abilities using the AI-centered B.C. and BC-destined AI framework. After comparing qualitative methodologies, the AI-BC architecture outperforms sophisticated methods.

  • An enhanced taxi demand perception system leveraging fusion and automated sensor integration
    Hemantaraj M. Kelagadi, Ravikiran Kamath Billady, Ravivarman Shanmugasundaram, K. Raj Thilak, L Karthick, and Narhar K. Patil
    IGI Global
    Academia has recently focused on taxi demand prediction, seeing its potential in intellectual transference systems. Older methodologies often overlooked nuanced journey conditions, mainly forecasting from origin locations. This approach lacks efficiency, disregarding demand dynamics between origins and destinations. The research introduces taxi origin-destination demand prediction, leveraging mechanical automation. The authors aim to anticipate future demand across all potential area pairings, acknowledging complex location interplay. A crucial challenge is efficiently collecting diverse contextual data for effective analysis. They employ a sophisticated mechanical automation system integrating deep neural networks (DNNs) to classify journey starting and ending points, outperforming traditional methods in accuracy and performance. Through extensive testing on large-scale datasets, the DNN-based system excels in predicting taxi demand. Leveraging advanced technologies like mechanical automation, the authors pave the way for more efficient transportation systems.

  • Analysis and Simulation of Boost-Flyback Converter for Renewable Energy Integration
    Ravivarman Shanmugasundaram, K. Sai Ramana, K. Akshay, K. Dilip, and Hardik Dahiya
    EDP Sciences
    Analysis and Simulation of Boost-Flyback Converter for Renewable Energy Integration is mainly focusing on boosting and decreasing the voltages coming from the renewable energy sources. The proposed methodology combines the advantages of both Boost and Flyback topologies, providing enhanced efficiency, reduced voltage stress, and improved transient response. The Boost-Flyback Converter employs a two-stage topology, where the Boost stage is responsible for stepping up the input voltage, and the flyback stage facilitates energy transfer and output voltage regulation. The analysis includes a detailed examination of the converter's operating principles, voltage and current waveforms, and control strategies. A comprehensive simulation study is conducted using advanced simulation tools to validate the converter's performance under various operating conditions and load profiles.

  • Preface
    Nnamadi Nwulu, Karuppiah Natarajan, Ravivarman Shanmugasundaram, Praveen Kumar Balachandran, Murugaperumal Krishnamoorthy, and Patil Mounica
    EDP Sciences

  • Simulation of Hybrid Boost Converter with Reduced Switch Stress for PV Systems
    Ravivarman Shanmugasundaram, P. Manojkumar, J. Sreedhar, M. Mallesh, and Jayraj Chanv
    EDP Sciences
    Currently, there is a growing prominence on using switched capacitor and switched inductor techniques in high-power boost converters to achieve higher voltages. This is accomplished by employing reactive elements, where the inductor discharges while the capacitor charges. The switched capacitor and switched inductor can extremely attain dc voltage obtain with require few quantities like inductors, capacitors, diodes, and a switch. Modifications were made to the switched inductor converter, resulting in a reduction in the voltage stress on the active switch. The converter now operates based only on the duty ratio. This study suggests adjustments to the switched capacitor and switched inductor converter to decrease the stress on the switch by altering the duty ratio closer to unity. The paper covers the converter's operation, waveforms, design equations, and simulation results to illustrate this modified converter setup.

  • Optimizing Electric Vehicle Battery Life: A Machine Learning Approach for Sustainable Transportation
    K. Karthick, S. Ravivarman, and R. Priyanka
    MDPI AG
    Electric vehicles (EVs) are becoming increasingly popular, due to their beneficial environmental effects and low operating costs. However, one of the main challenges with EVs is their short battery life. This study presents a comprehensive approach for predicting the Remaining Useful Life (RUL) of Nickel Manganese Cobalt-Lithium Cobalt Oxide (NMC-LCO) batteries. This research utilizes a dataset derived from the Hawaii Natural Energy Institute, encompassing 14 individual batteries subjected to over 1000 cycles under controlled conditions. A multi-step methodology is adopted, starting with data collection and preprocessing, followed by feature selection and outlier elimination. Machine learning models, including XGBoost, BaggingRegressor, LightGBM, CatBoost, and ExtraTreesRegressor, are employed to develop the RUL prediction model. Feature importance analysis aids in identifying critical parameters influencing battery health and lifespan. Statistical evaluations reveal no missing or duplicate data, and outlier removal enhances model accuracy. Notably, XGBoost emerged as the most effective algorithm, providing near-perfect predictions. This research underscores the significance of RUL prediction for enhancing battery lifecycle management, particularly in applications like electric vehicles, ensuring optimal resource utilization, cost efficiency, and environmental sustainability.

  • Design of Solar Dust Cleaning with Robot and Solar Monitoring System
    P. Harikrishna Goud M., Patil Mounica, Natarajan Karuppiah, S Ravivarman, and Tellapati Anuradha Devi
    IEEE
    Solar energy has emerged as a sustainable and renewable energy source. However, the efficiency of solar panels can be significantly impacted by dust and debris accumulation on their surface. Manual cleaning is time-consuming, labor-intensive, and often impractical for large-scale solar installations. This research presents an automated solar panel cleaning system that utilizes robotic technology to effectively remove dust and debris. The system incorporates a robotic arm equipped with a water spray mechanism and a cleaning brush. The robot is designed to navigate the solar panel surface, accurately spraying water and brushing away contaminants. The effectiveness of the system was evaluated by comparing the power output of cleaned and uncleaned solar panels. The results demonstrate a significant increase in power generation, highlighting the potential of automated cleaning systems to enhance the performance and reliability of solar energy installations.

  • Design of a Low Cost Simplified PWM Inverter
    J. Yaswanth, Vinod Reddy S, Ravivarman S, Karuppiah Natarajan, and Tellapati Anuradha Devi
    IEEE
    Electricity is essential in our day-to-day activities, often becoming an integral part of our lives. In order to supply electricity efficiently, power electronic devices such as converters, inverters, controllers, etc., are needed. This paper presents a simple and low cost sine wave inverter circuit utilizing the PWM IC TL494. It helps to reduce the cost and improve the efficiency in the circuit design. The goal of this paper is to demonstrate the design of a flexible PWM sine wave inverter circuit, utilizing IC TL494 for advanced PWM processing. The output efficiency with calculated parameters is being monitored as the circuit performs on the hardware kit.

  • Sustainable Economic Load Dispatch Using Dungle Beetle Optimization: A New Frontier to Minimize Cost and Emissions
    C Madhusudhan Mudhiraj, Patil Mounica, Natarajan Karuppiah, B. Praveen Kumar, and S Ravivarman
    IEEE
    In this paper the issue of ELD through a new approach by which Dungle Beetle Optimization (DuBO) has been employed. The objectives regarding the research work are optimization of power generation, considering multi-objectives, operational cost minimization, emission reduction, and integration of renewable energy. It is in this context that the present study of a DuBO proposed puts a strong claim for solving these types of problems in consideration through advanced optimization methodologies for attaining better performance than the methods in use currently. In this backdrop, an exclusive comparison of DuBO with some traditional optimization techniques like PSO, GA, and GWO is done here in much detail. Elaborate simulations and analyses have been put in place to establish that, in all circumstances, DuBO will always be better than those techniques during the process of reducing cost and even in the realm of controlling emissions and securing higher levels of penetration for renewable energy. The results showed that DuBO-optimized solutions for such highly nonlinear and complex problems are handled in a very clever way to allow total economic efficiency with a cost to the environment that is tolerable.

  • Modular multilevel converter-based hybrid energy storage system for electric vehicles: Design, simulation, and performance evaluation
    Saravanan Muthampatty Sengottaiyan, Surendiran Subramanian, Ravivarman Shanmugasundaram, and Kamali Samudram Manickam
    Informa UK Limited

  • Simulation and Performance Analysis of a DC-DC Converter with Enhanced Voltage Gain, Wide Input Voltage Variations, and Unified Ground Configuration
    Ravivarman Shanmugasundaram, Ankit Pandya, G. Manasa Priya, B. Anitha, and P. Srinath
    IEEE
    An effective DC-DC converter for fuel cell vehicles should possess the parameters such as efficiency, compactness, and voltage levels. Traditional converters like the two-level, three-level, and cascaded boost ones can't quite meet these needs. So, in this paper, we've developed a new converter topology. This converter uses switched capacitors and inductors and doesn't have any electrical isolation. The converter can achieve high voltage gain, can operate at wide range of input voltages, doesn't have high voltage stress on its components, and uses a common ground setup. PSIM software is used to simulate our converter, to test its performance. The proposed converter delivers 400V and 400W in terms of output voltage and power ratings, respectively. And, based on our simulations, the proposed converter topology works well with fuel cell based electric vehicles.

  • A Level Shifted Pulse Width Modulated Multilevel Inverter Fault Analysis Technique
    Manojkumar Palanisamy, Jeyasudha Segaran, Ravivarman Shanmugasundaram, and Sengolrajan Thanasingh
    Informa UK Limited

  • Enhancing Sustainable Urban Energy Management through Short-Term Wind Power Forecasting Using LSTM Neural Network
    Karthick Kanagarathinam, S. K. Aruna, S. Ravivarman, Mejdl Safran, Sultan Alfarhood, and Waleed Alrajhi
    MDPI AG
    Integrating wind energy forecasting into urban city energy management systems offers significant potential for optimizing energy usage, reducing the carbon footprint, and improving overall energy efficiency. This article focuses on developing a wind power forecasting model using cutting-edge technologies to enhance urban city energy management systems. To effectively manage wind energy availability, a strategy is proposed to curtail energy consumption during periods of low wind energy availability and boost consumption during periods of high wind energy availability. For this purpose, an LSTM-based model is employed to forecast short-term wind power, leveraging a publicly available dataset. The LSTM model is trained with 27,310 instances and 10 wind energy system attributes, which were selected using the Pearson correlation feature selection method to identify crucial features. The evaluation of the LSTM-based forecasting model yields an impressive R2 score of 0.9107. The model’s performance metrics attest to its high accuracy, explaining a substantial proportion of the variance in the test data. This study not only contributes to advancing wind power forecasting, but also holds promise for sustainable urban energy management, enabling cities to make informed decisions in optimizing energy consumption and promoting a greener, more resilient future.


  • Automatic control systems experimentation with LabVIEW using local and remote approaches
    P. Manojkumar, Ravivarman Shanmugasundaram, N. Rajasekaran, R. Rinish, Muhammed U. Hassan, and S. Sreekanth
    AIP Publishing


  • Switched Quasi Z-Source DC-DC Converter for Photovoltaic System
    K. Sanjay, K. Charitha, S. Shiva Kumar, and Ravivarman Shanmugasundaram
    IEEE
    The depletion of fossil fuels worldwide is driving the acceleration of renewable power energy systems, particularly those based on photovoltaics (PV). To enhance the voltage output from PV electricity systems for grid-linked inverters, a dc-dc boost converter can be employed. However, traditional boost converters face various challenges, leading to the proposal of several configurations aimed at improving their boosting capabilities. One such configuration is the Quasi impedance (Z)-source dc-dc converter, derived from the conventional impedance (Z)-source converter by incorporating a switch and diode at the output terminals. Compared to existing Z-source configurations, this converter operates with a small duty cycle (less than 0.25), resulting in a higher boosting factor and avoiding instability caused by inductor saturation. Moreover, it requires fewer passive components, leading to reduced losses, increased power density, and cost reduction. This paper discusses the features of the proposed converter and its functioning in continuous current conduction mode.

  • Impact of Stator Slot Shape on Cogging Torque of BLDC Motor
    Karthick Kanagarathinam, R. Manikandan, and Ravivarman S
    FOREX Publication
    Brushless DC (BLDC) motors have a wide range of applications in these modern days, such as electric vehicles, industrial robots, washing machines, pumps, and blowers. The brushless DC motors have many advantages when compared to induction motors and conventional DC motors, such as better speed control, noiseless operation, high efficiency, less maintenance, and a long life. Along with these benefits, there is one major disadvantage known as cogging, which causes undesirable effects in the motor such as noises and vibrations. BLDC motors have been widely used in automation and industrial applications due to their attractive features. There are certain parameters to be considered while designing a BLDC motor, such as its dimensions, number of windings turns, type of magnetic materials used, required torque, output current, slot-to-depth ratio, efficiency, temperature rise, etc.

  • A Comparative Analysis of Maximum Power Point Techniques for Solar Photovoltaic Systems
    Ashwin Kumar Devarakonda, Natarajan Karuppiah, Tamilselvi Selvaraj, Praveen Kumar Balachandran, Ravivarman Shanmugasundaram, and Tomonobu Senjyu
    MDPI AG
    The characteristics of a PV (photovoltaic) module is non-linear and vary with nature. The tracking of maximum power point (MPP) at various atmospheric conditions is essential for the reliable operation of solar-integrated power generation units. This paper compares the most widely used maximum power point tracking (MPPT) techniques such as the perturb and observe method (P&O), incremental conductance method (INC), fuzzy logic controller method (FLC), neural network (NN) model, and adaptive neuro-fuzzy inference system method (ANFIS) with the modern approach of the hybrid method (neural network + P&O) for PV systems. The hybrid method combines the strength of the neural network and P&O in a single framework. The PV system is composed of a PV panel, converter, MPPT unit, and load modelled using MATLAB/Simulink. These methods differ in their characteristics such as convergence speed, ease of implementation, sensors used, cost, and range of efficiencies. Based on all these, performances are evaluated. In this analysis, the drawbacks of the methods are studied, and wastage of the panel’s available output energy is observed. The hybrid technique concedes a spontaneous recovery during dynamic changes in environmental conditions. The simulation results illustrate the improvements obtained by the hybrid method in comparison to other techniques.

  • Intelligent Shopping Cart using IoT Technology
    Patil Mounica, Karuppiah Natarajan, and Ravivarman Shanmugasundaram
    IEEE
    In today's cities, shopping and browsing for things in shopping malls have become a regular activity. At shopping malls, during vacations and weekend breaks., a diverse range of people is observed. When there are exceptional bargains and reduced rates, there is a rush. People used to purchase different items and place them in their shopping carts. Following the overall purchase., the invoicing response should be used for invoicing and production resettlement. The cashier creates the bill using a bar code reader in the invoicing response. This is a time-consuming method and leads to long queues at the invoicing counters. The goal of this project is to reduce lines at invoicing counters in shopping malls. The smart shopping cart accomplishes the same goal by displaying the total cost of the items in the cart. By doing so, the customer simply pays the price in-app or via the invoicing response, and then walks away with the goods he or she has purchased. The Arduino Uno, RFID Component, RFID Card, and Buzzer are all required components. It eliminates the conventional scanning of things at the point of response, which speeds up the entire purchasing process. The consumer is aware of the total amount due using this technique. As a result, the client plans his purchases simply by acquiring the most important commodities in accordance with his budgetary resources. Since the entire billing process is based on RFID, the risk of human error is considerably reduced. The system also has a feature that allows users to clear their checked goods, which improves the shopping experience even further.

  • Design of Modified Counter based PWM generator for closed-loop DC-DC Voltage Regulation
    Joseph Anthony Prathap, Ravivarman Shanmugasundaram, M. Kranthi Kiran Reddy, and K. Harika
    IOP Publishing
    Abstract This paper proposes the design of a novel Modified Counter based Digital Pulse Width Modulation generator to analyze the performance of the closed-loop DC-DC buck converter. The closed-loop DC-DC buck Converter uses the Proportional Integral controller to regularize the output voltage and the bio-inspired algorithms namely Particle Swarm Optimization and Ant Colony Optimization are considered for the generation of the optimal values for the PI gains namely KP and KI. Conventionally, the switching of the buck converter is controlled by the PWM signals that exhibit complexity in design. The updated Digital Pulse Width Modulation techniques were suitable for voltage regulation at the cost of high clock frequency requirement, increase in the design area for real implementation, and the trade-off between the switching frequency and the component size of the buck converter. To overcome these, the modified Counter based Digital Pulse width modulation that generates the high switching frequency DPWM is developed in HDL. Then the proposed technique is validated in the closed-loop PI-based DC-DC buck converter using the System Generator MATLAB SIMULINK. To regularize the voltage output, the PI controller is included along with the optimization algorithms such as Particle Swarm Optimization and Ant Colony Optimization to optimize the PI gains. The time transient analysis of the proposed method exhibits improvement in the ACO based design compared to the PSO based method. The power and area are manipulated by using the Cadence and Xilinx tools

  • Analysis of the Impact of Magnetic Materials on Cogging Torque in Brushless DC Motor
    K. Karthick, S. Ravivarman, Ravi Samikannu, K. Vinoth, and Bashyam Sasikumar
    Hindawi Limited
    The cogging torque is the most significant issue in permanent magnet applications, since it has a negative impact on machine performance. In this article, the impact of magnetic materials on cogging torque is analyzed on brushless DC motors (BLDC). The effect of neodymium magnets (NdFeB), compression molded magnet, and samarium cobalt (SmCo) magnet on the cogging torque is analyzed to the BLDC motor designed for hybrid electric vehicle traction that has the peak power rating of 50 kW motor with 48 stator slots and 8 rotor poles. With the presence of these three magnetic materials, the cogging torque is estimated independently using multiposition simulation. The multiposition is simulated using a transient application that runs at constant speed. The results of cogging torque, rotational speed, angular position of BLDC motor, and magnetic flux density distribution have been presented. Also, the maximal, mean, minimal, rectified mean, and rms values of cogging torque were provided.

  • A case study on the assessment of program quality through co-po mapping and its attainment
    B. Rajagopal Reddy, Natarajan Karuppiah, Md. Asif, and S. Ravivarman
    Rajarambapu Institute of Technology
    : In recent years, accreditation of National Board of Accreditation has become mandatory for all the Autonomous colleges and Universities. NBA stresses on Outcome Based Education to improve the quality of education. It has formulated twelve graduate attributes to measure the quality of the program that a graduate has to acquire from any college/university during his four years of under graduation. The success of any program depends on the attainment of course outcomes and program outcomes. But there is a lack of understanding among the Engineering faculties in CO-PO attainment calculations. This study explores the significance of proper CO-PO mapping and its attainment calculation. CO-PO mapping and its attainment calculations are an integral part of OBE and it helps in continuous quality improvement, which serves as a feedback for OBE loop. CQI is instrumental in identifying any setbacks in Teaching Learning Process and additional solutions are figured out to improve the delivery of the course. In this study, different approaches are suggested to calculate the attainment of COs of the course and POs, PSOs of the program. Results and discussions are done on the attainment of COs of different courses and suggestions for the courses which fail to attain the target has been discussed. A sample of CO-PO attainment calculation for the course Basic Electrical Engineering offered for BTech I Year students has been discussed. Microsoft Office Excel spreadsheet has been used for computation purpose.

  • Design and application of a fuzzy adaptive controlled permanent magnet synchronous motor drive employed in electric vehicle
    Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP
    In this work, design, development and analysis of a closed loop-based control strategy of a fuzzy adaptive controlled PWM operated Permanent Magnet Synchronous Motor drive has been established. The entire structure of the proposed closed loop model is made up of two loop control formation, outer loop speed and inner loop current. Therefore, to enhance the dynamic operation of the drive system classical PI controller is taken as current controller and fuzzy adaptive controller with simplified fuzzy rules have been utilized as speed controller. With the implementation of sinusoidal PWM control strategy, it is evident that the nature of armature current would be nearly sinusoidal and generated torque ripples will be lesser. The detailed dynamic performance of a permanent magnet synchronous motor drive is carried out in MATLAB/SIMULINK environment. An economic as well as efficient inverter configuration is also proposed in this article. The simulations results confirm the effectiveness of the proposed approach. The outcome of the proposed concept can be utilized for dynamic performance prediction of a light electric vehicle in a modern energy efficient environment

  • Non-isolated modified quadratic boost converter with midpoint output for solar photovoltaic applications
    Shanmugasundaram Ravivarman, Karuppiah Natarajan, and Reddy B Raja Gopal
    EDP Sciences
    This paper presents a boost DC-DC converter topology with non - isolated high gain and output midpoint, to boost the voltage obtained from solar photovoltaic panels. The three-level boost converter is coupled to the output port of the single-switch quadratic boost converter to derive the proposed converter topology. The voltage gain of the proposed converter is greater than that of the classical boost converter. The voltage stress on the switches of the proposed converter is equal to half of the converter output voltage. Static analysis, operating modes, experimental waveforms in continuous current conduction and discontinuous current conduction modes are shown. A 520 W prototype converter was implemented in the laboratory and its results are presented.

RECENT SCHOLAR PUBLICATIONS

  • Modular multilevel converter-based hybrid energy storage system for electric vehicles: Design, simulation, and performance evaluation
    S Muthampatty Sengottaiyan, S Subramanian, R Shanmugasundaram, ...
    Energy Sources, Part A: Recovery, Utilization, and Environmental Effects 46 2024

  • Design of a Low Cost Simplified PWM Inverter
    J Yaswanth, V Reddy, S Ravivarman, K Natarajan, TA Devi
    2024 International Conference on IoT Based Control Networks and Intelligent 2024

  • Design of Solar Dust Cleaning with Robot and Solar Monitoring System
    P Mounica, N Karuppiah, S Ravivarman, TA Devi
    2024 3rd International Conference on Automation, Computing and Renewable 2024

  • Sustainable Economic Load Dispatch Using Dungle Beetle Optimization: A New Frontier to Minimize Cost and Emissions
    CM Mudhiraj, P Mounica, N Karuppiah, BP Kumar, S Ravivarman
    2024 3rd International Conference for Advancement in Technology (ICONAT), 1-7 2024

  • A Level Shifted Pulse Width Modulated Multilevel Inverter Fault Analysis Technique
    M Palanisamy, J Segaran, R Shanmugasundaram, S Thanasingh
    Electric Power Components and Systems 52 (10), 1737-1748 2024

  • Optimizing Electric Vehicle Battery Life: A Machine Learning Approach for Sustainable Transportation
    K Karthick, S Ravivarman, R Priyanka
    World Electric Vehicle Journal 15 (2), 60 2024

  • Simulation and Performance Analysis of a DC-DC Converter with Enhanced Voltage Gain, Wide Input Voltage Variations, and Unified Ground Configuration
    R Shanmugasundaram, A Pandya, GM Priya, B Anitha, P Srinath
    2024 Fourth International Conference on Advances in Electrical, Computing 2024

  • An Enhanced Taxi Demand Perception System Leveraging Fusion and Automated Sensor Integration
    HM Kelagadi, RK Billady, R Shanmugasundaram, KR Thilak, L Karthick, ...
    Trends and Applications in Mechanical Engineering, Composite Materials and 2024

  • AI-Empowered Smart Electricity System With Predictive Maintenance Integration
    L Karthick, L Mishra, R Shanmugasundaram, S Saravanan, SK Trivedi
    Trends and Applications in Mechanical Engineering, Composite Materials and 2024

  • Simulation of Hybrid Boost Converter with Reduced Switch Stress for PV Systems
    R Shanmugasundaram, P Manojkumar, J Sreedhar, M Mallesh, J Chanv
    E3S Web of Conferences 547, 02014 2024

  • Analysis and Simulation of Boost-Flyback Converter for Renewable Energy Integration
    R Shanmugasundaram, KS Ramana, K Akshay, K Dilip, H Dahiya
    E3S Web of Conferences 547, 01017 2024

  • Enhancing sustainable urban energy management through short-term wind power forecasting using lstm neural network
    K Kanagarathinam, SK Aruna, S Ravivarman, M Safran, S Alfarhood, ...
    Sustainability 15 (18), 13424 2023

  • Switched Quasi Z-Source DC-DC Converter For Photovoltaic System
    K Sanjay, K Charitha, SS Kumar, R Shanmugasundaram
    2023 3rd International Conference on Intelligent Technologies (CONIT), 1-6 2023

  • Automatic control systems experimentation with LabVIEW using local and remote approaches
    P Manojkumar, R Shanmugasundaram, N Rajasekaran, R Rinish, ...
    AIP Conference Proceedings 2492 (1) 2023

  • SENSOR FAILURE IDENTIFICATION AND SEGREGATION USING WAVELET PERFORMANCE ANALYSIS FOR WSN BASED STATUS SURVEILLANCE SYSTEM OF A WIND TURBINE.
    SM Sengottaiyan, J Rajaiah, R Shanmugasundaram, J Ponnusamy
    International Journal of Industrial Engineering 30 (3) 2023

  • Impact of Stator Slot Shape on Cogging Torque of BLDC Motor
    K Kanagarathinam, R Manikandan, R S
    International Journal of Electrical and Electronics Research 11 (1), 54-60 2023

  • Machine Learning Based Prediction of Social Media Performance Metrics Using Facebook Data
    K Karthick, SK Aruna, S Ravivarman
    Security and Risk Analysis for Intelligent Cloud Computing, 216-233 2023

  • Intelligent Shopping Cart using IoT Technology
    P Mounica, K Natarajan, R Shanmugasundaram
    2022 3rd International Conference on Communication, Computing and Industry 4 2022

  • A comparative analysis of maximum power point techniques for solar photovoltaic systems
    AK Devarakonda, N Karuppiah, T Selvaraj, PK Balachandran, ...
    Energies 15 (22), 8776 2022

  • A review on demand side management: Definition, scope, challenges and benefits
    R Premkumar, R Shanmugasundaram, KR Thilak, ANVSS Balaji
    2022 8th International Conference on Smart Structures and Systems (ICSSS), 1-4 2022

MOST CITED SCHOLAR PUBLICATIONS

  • A comparative analysis of maximum power point techniques for solar photovoltaic systems
    AK Devarakonda, N Karuppiah, T Selvaraj, PK Balachandran, ...
    Energies 15 (22), 8776 2022
    Citations: 59

  • A review on demand side management: Definition, scope, challenges and benefits
    R Premkumar, R Shanmugasundaram, KR Thilak, ANVSS Balaji
    2022 8th International Conference on Smart Structures and Systems (ICSSS), 1-4 2022
    Citations: 15

  • Non-isolated modified quadratic boost converter with midpoint output for solar photovoltaic applications
    S Ravivarman, K Natarajan, RBR Gopal
    E3S web of conferences 87, 01025 2019
    Citations: 13

  • Z Source Inverter for Photovoltaic System with Fuzzy Logic Controller
    R Vijayabalan, S Ravivarman
    International Journal of Power Electronics and Drive Systems 2 (4), 371 2012
    Citations: 11

  • Optimizing Electric Vehicle Battery Life: A Machine Learning Approach for Sustainable Transportation
    K Karthick, S Ravivarman, R Priyanka
    World Electric Vehicle Journal 15 (2), 60 2024
    Citations: 9

  • Analysis of the impact of magnetic materials on cogging torque in brushless dc motor
    K Karthick, S Ravivarman, R Samikannu, K Vinoth, B Sasikumar
    Advances in Materials Science and Engineering 2021 (1), 5954967 2021
    Citations: 8

  • Wastage Pay Smart Bin
    N Karuppiah, SS Kumar, S Ravivarman, PJ Joshuva, A Prabhu, ...
    International Journal of Engineering & Technology 7 (4.6), 193-197 2018
    Citations: 8

  • A Review on Voltage Balancing Solutions in Multilevel Inverters
    M Ranjitha, S Ravivarman
    Indonesian Journal of Electrical Engineering and Computer Science 1 (1), 53-59 2016
    Citations: 8

  • Enhancing sustainable urban energy management through short-term wind power forecasting using lstm neural network
    K Kanagarathinam, SK Aruna, S Ravivarman, M Safran, S Alfarhood, ...
    Sustainability 15 (18), 13424 2023
    Citations: 7

  • Enhancing the performance of Transmission Lines by FACTS Devices using GSA and BFOA Algorithms
    N Karuppiah, S Muthubalaji, S Ravivarman, M Asif, A Mandal
    International Journal of Engineering & Technology 7 (4.6), 203-208 2018
    Citations: 6

  • Switched Quasi Z-Source DC-DC Converter For Photovoltaic System
    K Sanjay, K Charitha, SS Kumar, R Shanmugasundaram
    2023 3rd International Conference on Intelligent Technologies (CONIT), 1-6 2023
    Citations: 5

  • Optimized Grid Power Injection with Maximum Power Point Tracking Using Cascaded SEPIC Converter and Three Phase Inverter
    S Ravivarman, T Samydurai
    International Journal of Advanced Research in Electrical, Electronics and 2015
    Citations: 5

  • A Level Shifted Pulse Width Modulated Multilevel Inverter Fault Analysis Technique
    M Palanisamy, J Segaran, R Shanmugasundaram, S Thanasingh
    Electric Power Components and Systems 52 (10), 1737-1748 2024
    Citations: 4

  • Simulation and Performance Analysis of a DC-DC Converter with Enhanced Voltage Gain, Wide Input Voltage Variations, and Unified Ground Configuration
    R Shanmugasundaram, A Pandya, GM Priya, B Anitha, P Srinath
    2024 Fourth International Conference on Advances in Electrical, Computing 2024
    Citations: 4

  • A case study on the assessment of program quality through CO-PO mapping and its attainment
    BR Reddy, N Karuppiah, M Asif, S Ravivarman
    Journal of Engineering Education Transformations 34, 104-111 2021
    Citations: 4

  • SENSOR FAILURE IDENTIFICATION AND SEGREGATION USING WAVELET PERFORMANCE ANALYSIS FOR WSN BASED STATUS SURVEILLANCE SYSTEM OF A WIND TURBINE.
    SM Sengottaiyan, J Rajaiah, R Shanmugasundaram, J Ponnusamy
    International Journal of Industrial Engineering 30 (3) 2023
    Citations: 3

  • Impact of Stator Slot Shape on Cogging Torque of BLDC Motor
    K Kanagarathinam, R Manikandan, R S
    International Journal of Electrical and Electronics Research 11 (1), 54-60 2023
    Citations: 3

  • Design of Modified Counter based PWM generator for closed-loop DC-DC Voltage Regulation
    JA Prathap, R Shanmugasundaram, MKK Reddy, K Harika
    Journal of Physics: Conference Series 1818 (1), 012227 2021
    Citations: 3

  • Performance study of MATLAB modelled PV panel and conventional PV panel interfaced with LabVIEW
    K Jaiganesh, N Karuppiah, S Ravivarman, M Asif
    International Journal of Engineering & Technology 7 (2.17), 70-73 2018
    Citations: 3

  • Intelligent Shopping Cart using IoT Technology
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