Professor in Electrical Engineering Department
MS Ramaiah University of Applied Sciences
Renewable Power Generation, Electric Vehicle, Power System
Electric mobility has become an essential part of the future of transportation. Detection, diagnosis and prognosis of fault in electric drives are improving the reliability, of electric vehicles (EV). Permanent magnet synchronous motor (PMSM) drives are used in a large variety of applications due to their dynamic performances, higher power density and higher efficiency. In this study, health monitoring and prognosis of PMSM is developed by creating intelligent digital twin (i-DT) in MATLAB/ Simulink.
Senthil Kumar A, Krishnan Manickavasagam, and Pramod K Bhandiwad Institute of Electrical and Electronics Engineers (IEEE)
Shweta S Hooli, Anusha Vadde, Govind R Kadambi, and Krishnan Manickavasagam IEEE
This work is carried out to understand flux distribution around induction motor and their influence on human health. High-capacity Squirrel Cage Induction Motor (SCIM) draws huge currents; hence, the colossal flux density is emitted around the motor. When the leakage flux interfere with high-frequency electromagnetic waves, the influence on a human being is more dominant than power frequency. Time domain Finite Element Analysis (FEA) is performed to get an accurate instant value of magnetic flux distribution in and around motor a 15kW, SCIM. A 3D human head is modelled using FEA and placed in the vicinity of magnetic leakage flux mixed with high-frequency electromagnetic waves. The simulation reveals that magnetic leakage flux from SCIM is harmful to humans. The main objective of this work is to identify safe regions and create awareness of magnetic leakage flux, which can cause human health problems.
Prajwal Kogodu Thirthappa and Manickavasagam Krishnan Walter de Gruyter GmbH
Abstract Levitation based energy harvester (LBEH) is an energy harvesting technology which is used to convert the existing kinetic energy into electrical energy. The technique utilizes a levitating magnet which in a closed container vibrate or moves for the subjected vibrations. An outer coil which will extract energy into electrical voltage is carefully selected or designed or the rating. In this research work, a conventional LBEH is designed, simulated, and studied for a particular vibration data. The same is carried out in the FEM analysis software. The system is also mathematically derived and analyzed in the numerical tool. The results obtained from the numerical and FEM tool are compared. At the end of the research work, a parametric study is carried out for the variations in the input characteristics such as frequency, nature of vibrations and other parameters. Results obtained indicate that the power developed is maximum with a value of 0.7 V and 10 mW for the designed natural frequency of 10 Hz and decreases on either side as the bandwidth varies from 5 to 15 Hz.
S. Sachin, Krishnan Manickavasagam, and A.T. Sriram Elsevier BV
Senthil Kumar A and Krishnan Manickavasagam Institute of Electrical and Electronics Engineers (IEEE)
K. T. Prajwal, K. Manickavasagam, and R. Suresh Springer Science and Business Media LLC
Senthil Kumar A and Krishnan Manickavasagam Institute of Electrical and Electronics Engineers (IEEE)
Jayashree P Yalawar, R. Suchita, Anusha Vadde, K Manickavasagam, and Prashant Bekwad IEEE
Three phase Squirrel Cage Induction Motors (SCIM) are widely used as industrial drives due to their self-starting, reliable and economical feature. The estimation of the refurbished/rewound SCIM’s working efficiency is given priority in this work. The conventional test set up used by manufacturing industry may not be feasible solution for estimating the efficiency of refurbished/rewound SCIM due to transportation and other issues. Current Vector Method (CVM) and Modified IEEE Standard 112 Equivalent Circuit Method (Modified IEEE Std. ECM) are used based no-load availability of the data. The measured stray load losses are accounted in estimating the efficiency. Hence, the expensive dynamometer test procedure is removed. The proposed methods are simple, more accurate and less expensive which will give minimum possible error. Efficiency estimation using different methods are being calculated, verified and compared for three different rating of three phase SCIM. Mainly focused on the 110kW SCIM carried out in this research work.
S. Sachin, Krishnan Manickavasagam, and A. T. Sriram Praise Worthy Prize
Jayanth B, V. Sailaja, K. Deepa, and K. Manickavasagam IEEE
The work focuses on how to overcome discriminating environment on buying and selling price of the power in a micro grid. An intermediate system is built to overcome the discriminate environment on real time scenario. Case study with different kinds of loads is carried out to ensure both suppliers and consumers of the micro grid are equally handled over a distributive system. The system works according to the consumer's interaction with the grid. A grading system is introduced to push the respective consumers to the higher level based on the interaction with the grid, thus providing non-discriminating environment. This mechanism will encourage consumers to participate in the grading system and more number of suppliers to join the system. The base of the system is carried using IEEE 44 bus for 2 micro-grids and the simulation is carried out in MATLAB. The system is built on JAVA platform for long run.
Sohail Khazi, Anusha Vadde, Krishnan Manickavasagam, Govind R. Kadambi, Venkat Narayanan, B. M. Lokesh, Swapan Sarkar, and Jagadeesha Springer Singapore
Shweta S Hooli, Anusha Vadde, Krishnan Manickavasagam, and Govind R Kadambi IEEE
Detection of low-level electrical winding faults in Squirrel Cage Induction Motor (SCIM) is prime importance in Electric Vehicle (EVs). This analysis is carried out to predict flux distribution inside and outside of SCIM using Finite Element Analysis (FEA). In FEA, time domain analysis is performed to determine flux at the instant of fault with respect to time whereas steady state analysis will not give such a results. Flux distribution provides significant information about the behavior of SCIM. For analyzing the leakage flux in the surface vicinity of SCIM a 15kW machine is chosen. The analysis indicates magnetic flux distribution and ideal location of flux sensor. From FEM model, leakage flux on the surface of SCIM is captured and exported to MATLAB for health monitoring. Fuzzy rule base is developed for mapping the flux with health monitoring of SCIM used in Electric Vehicle (EV). Continuous health monitoring of the machine is captured by fuzzy controller and displayed in EV or vehicle monitoring centre.
Sudha B, Anusha Vadde, and Krishnan Manickavasagam IEEE
Sudha. B, , Anusha Vadde, Krishnan Manickavasagam, Govind R Kadambi, , , and Journal of Engineering Research
Induction motor usage is increasing drastically due to new entrant of electric vehicle, traction and propulsion systems at present. Temperature of electric motors are significantly affect its parameters. Since, resistances variation of stator and rotor winding are depend on temperature, the torque speed characteristics also affects in the induction motors. In this paper, a innovative approach is proposed to arrive the relation of temperature on torque. Thermal analysis of 160 L-frame induction motors is carried out using Finite Element Method (FEM) under various load to obtain temperature. The mathematical relationship between temperature and torque is arrived using curve fitting technique. The expression arrived in this method is used to predict the torque for a given temperature of SCIM.
Shweta S Hooli, Anusha Vadde, Krishnan Manickavasagam, and Govind R. Kadambi Springer Singapore
This paper proposes a non-invasive method of predicting health monitoring of a three-phase Squirrel Cage Induction Motor (SCIM). A 15 kW SCIM is modelled using Finite Element Analysis (FEA) for performing magnetic analysis to design a restraining coil. Since, torque developed depends on magnitude of flux, an electronic system is designed to display the torque. Health condition of SCIM is predicted based on torque magnitude. A typical implementation of the proposed scheme on 15 kW SCIM revealed a satisfactory correlation between the experimental and simulation results. The proposed approach aids to monitor the SCIM in Electric Vehicles (EVs) without physical intervention.
Krishnan Manickavasagam, Ilango Karuppasamy, and Vineetha Puttaraj Springer International Publishing
Power systems are steadily growing to meet the power demand. Due to the challenges arising from fossil fuel exploitation and associated pollution, researchers are focusing on distributed generations (DG). The hosting capacity of the power system can be increased by increasing the DG and energy storage device (ESD). However, usage of DG creates challenges in operation due to its stochastic nature. The electricity generated from DG causes mismatch of generation and load demand. This causes voltage and frequency deviations and eventually affects system stability. Penetration of DG with conventional power system requires strategic approach for smooth operation and control. Steady-state operation of DG connected to microgrid operates in two types of analysis: (i) large signal analysis and (ii) small signal analysis. The control strategies for island mode are classified as communication based and droop based. Presently, Internet of Things (IoT) is replacing high bandwidth lines for the purpose of effective communication. Different countries are following their own control strategies for effective control of microgrids. This chapter discusses the communication-based control strategy implemented in Gasa Island, South Korea. Taiwanese microgrid under normal and disturbance conditions implemented with multi-agent system (MAS) platform in Taiwan using agent-oriented programming is also discussed.
Suchitra Venkatesan, Krishnan Manickavasagam, Nikita Tengenkai, and Nagendran Vijayalakshmi Institution of Engineering and Technology (IET)
Electric mobility has become an essential part of the future of transportation. Detection, diagnosis and prognosis of fault in electric drives are improving the reliability, of electric vehicles (EV). Permanent magnet synchronous motor (PMSM) drives are used in a large variety of applications due to their dynamic performances, higher power density and higher efficiency. In this study, health monitoring and prognosis of PMSM is developed by creating intelligent digital twin (i-DT) in MATLAB/Simulink. An artificial neural network (ANN) and fuzzy logic are used for mapping inputs distance, time of travel of EV and outputs casing temperature, winding temperature, time to refill the bearing lubricant, percentage deterioration of magnetic flux to compute remaining useful life (RUL) of permanent magnet (PM). Health monitoring and prognosis of EV motor using i-DT is developed with two approaches. Firstly, in-house health monitoring and prognosis is developed to monitor the performance of the motor in-house. Secondly, Remote Health Monitoring and Prognosis Centre (RHMPC) is developed to monitor the performance of the motor remotely using cloud communication by the service provider of the EV. The simulation results prove that the RUL of PM and time to refill the bearing lubricant obtained by i-DT twins theoretical results.
Krishnan Manickavasagam, Belur Krishna Swathi Prasad, and Hariharan Ramasangu Institution of Engineering and Technology (IET)
Power system security assessment is important for the analysis of a power system network. The security analysis is based on equality constraint of generation-demand balance and inequality constraints of maximum voltage and current limits. The lack of a single measure to identify the state of the power system network limits the analysis of security and leads to uncertainty in identifying the states of the power system. In this study, a single measure Security Information Index (SII) is proposed for identifying the state of power system using steady-state power flow analysis. SII is computed using participation factors which are derived from both equality and inequality constraints, and moments of their statistics. SII is used to identify the present state of the power system and enhance the system security. This is successfully tested on IEEE 14 and IEEE 30-bus system.
Krishnan Manickavasagam, Naveen Kumar Thotakanama, and Vineetha Puttaraj Institution of Engineering and Technology (IET)
Utilisation of renewable energy sources (RES) is increasing day by day to reduce greenhouse emissions. The toxic emission from ship is the main concern in marine sector. Here, utilisation of renewable energy for propulsion and electrification of accessories in a ship are proposed. Microgrid with AC and DC bus is developed using solar panels, wind mills, fuel cell, diesel generator, and energy storage devices. Energy management system with two fuzzy logic controllers (FLCs) is used to select and manage energy in the microgrid. Selection of source is decided by FLC1 based on the availability of RES. Generation of control pulses for inter-linking converters is decided by FLC2 based on variation in solar irradiance and wind velocity. The microgrid with RES is simulated using MATLAB/SIMULINK. The results show that uncertainty in RES can be handled by FLCs to provide a continuous power supply for transportation of ship and its accessories.
T Nikita, K. Manickavasagam, and S Sachin IEEE
In present scenario, the Doubly Fed Induction Generator (DFIG) is contributing more than 50% in wind power generation. The computation of core losses and copper losses are essential to analyse the electric machine performance. In this paper, DFIG is modelled and analysed using ANSOFT MAXWELL which results in distribution of magnetic flux and magnetic flux density for all the parts of the machine. To validate the result under the disturbance, the Low Voltage Ride Through (LVRT) is considered which is the biggest challenges faced by DFIG. The analysis is made using MATLAB SIMULINK to predict the fault current and voltage magnitudes during LVRT. The same fault current and voltage magnitudes are used in DFIG model created using ANSOFT MAXWELL. The core losses of the machine is computed from maximum flux density under normal, during LVRT and after supressing LVRT.
T Nikita, K. Manickavasagam, and S Sachin IEEE
Rotating electrical machines are designed at many levels and from a number of different points of view. The development of powerful computation engines in previous decades allowed for the use of numerical methods in electromagnetics. In electrical machines, the magnetic field effect the dimensions of iron parts due to magnetostriction. In this paper, Doubly Fed Induction Generator (DFIG) is modelled and analyzed using ANSOFT MAXWELL which results in distribution of magnetic flux for all the parts of the machine. The Low Voltage Ride Through (LVRT) is the cause of magnetostriction in DFIG. To capture this effect, the LVRT is created in DFIG model using MATLAB SIMULINK to predict the fault current and voltage magnitudes. The same fault current and voltage magnitudes are used for analyzing the ANSOFT MAXWELL DFIG model.
A Senthil Kumar and K. Manickavasagam IEEE
It is critical to design an earthing system for transient conditions such as lightning strikes, over voltages, surges etc., for which the estimation of soil resistivity under transient conditions is essential. The soil resistivity varies dynamically under transient conditions and hence the estimation of dynamic soil resistivity is difficult process. In this work, under lightning impulse conditions, the dynamic soil resistivity profile is created by simulations considering soil ionization for different soil resistivity, ionization and deionization time constants. Based on the simulation results, dynamics soil resistivity modeled mathematically to compute ionization and deionization resistivity. The results infer that the dynamic soil resistivity depends on permeability, permittivity and lightning impulse rise time and does not depend upon earth electrode dimension.
Shriti Das, Naveen Kumar Thotakanama, and Krishnan Manickavasagam IEEE
This paper presents the designing of a SIMULINK model based on solar power generation scheme. The bidirectional converter charges the battery, whenever PV module generates excess power. Battery discharges power to the load during low solar irradiation. SOC (State of Charge) control of battery is provided to avoid complete discharge. In practice, the battery charging circuit is connected before load. In this work to extract maximum power from PV module, the battery charging unit and battery is connected near to the source to reduce the number of power conversion stages. The control of power is achieved through DC-DC Converter by controlling the gate pulses using fuzzy based PWM technique. A DC-AC converter is associated to feed power to AC load. The simulation results of designed system are validated and compared with the conventional PID controlled system during constant and varying irradiance and load.
Krishnan Manickavasagam Institute of Electrical and Electronics Engineers (IEEE)
This paper presents the modeling of intelligent energy control center (ECC) controlling distributed generators (DGs) using multi-agent system. Multi-agent system has been proposed to provide intelligent energy control and management in grids because of their benefits of extensibility, autonomy, reduced maintenance, etc. The multi-agent system constituting the smart grid and agents such as user agent, control agent, database agent, distributed energy resources (DER) agent work in collaboration to perform assigned tasks. The wind power generator connected with local load, the solar power connected with local load and the ECC controlled by fuzzy logic controller (FLC) are simulated in MATLAB/SIMULINK. The DER model is created in client and ECC is created in server. Communication between the server and the client is established using transmission control protocol/internet protocol (TCP/IP). The results indicate that the controlling of DER agent can be achieved both from server and client.
R. Karthikeyan, K. Manickavasagam, Shikha Tripathi, and K.V.V. Murthy Walter de Gruyter GmbH
Abstract This paper discusses the application of adaptive neuro-fuzzy inference system (ANFIS) control for a parallel cascade control system. Parallel cascade controllers have two controllers, primary and secondary controllers in cascade. In this paper the primary controller is designed based on neuro-fuzzy approach. The main idea of fuzzy controller is to imitate human reasoning process to control ill-defined and hard to model plants. But there is a lack of systematic methodology in designing fuzzy controllers. The neural network has powerful abilities for learning, optimization and adaptation. A combination of neural networks and fuzzy logic offers the possibility of solving tuning problems and design difficulties of fuzzy logic. Due to their complementary advantages, these two models are integrated together to form more robust learning systems, referred to as adaptive neuro-fuzzy inference system (ANFIS). The secondary controller is designed using the internal model control approach. The performance of the proposed ANFIS-based control is evaluated using different case studies and the simulated results reveal that the ANFIS control approach gives improved servo and regulatory control performances compared to the conventional proportional integral derivative controller.