Dr. M. Arun Noyal Doss received his B.E. degree in electrical engineering from Madras University, in 2004, the M.E. degree in power electronics and drives from Anna University, in 2006, and the Ph.D. degree in electrical engineering from SRM Institute of Science and Technology University, in 2014. He is currently working as an Associate Professor at SRM University. His research interests include power electronics, modeling of electrical machines, and special machines. Dr. Doss's research interests encompass power electronics, modeling of electrical machines, and special electrical machines. He has contributed to the academic community with numerous publications, focusing on areas such as BLDC motors, cogging torque, harmonics, and multilevel inverters. Dr. Doss has guided research scholars, including work on multilevel inverters for electric vehicle applications and BLDC motors. His scholarly work has been recognized with citations, reflecting his impact on the field.
RESEARCH, TEACHING, or OTHER INTERESTS
Electrical and Electronic Engineering, Energy Engineering and Power Technology
48
Scopus Publications
Scopus Publications
High-Performance Speed Control of BLDC Motor Drives Using a PI Sailfish Optimization Algorithm Othman Abdalkader Othman, Mohan Arun Noyal Doss, Jamal Aldahmashi, Moustafa Ahmed Ibrahim, Narayanamoorthi Rajamanickam Energies, 2026 BLDC motors are utilized in electric cars, robotics, drones, home appliances and medical equipment due to their effectiveness, dependability, and accurate control. PI controllers have been put forward to enhance the dynamic performance of brushless direct current (BLDC) motors, and they have been tested in many papers with various algorithms (such as PSO, GA, GWO, ACO and ABC) and strategies (such as PI/PID control, FOC, FLC, SMC and MPC). Meanwhile, in this research, and for the first time, the PI controller was tuned by the proposed Sailfish Optimization algorithm (SFO) with a direct torque control (DTC) strategy to enhance the dynamic performance of BLDC motors. Although DTC provides a very fast torque response, it still suffers from high torque ripple and noticeable instability at low speeds. These issues persist even when using conventional PI tuning or common optimization algorithms. Hence, in this research, we proposed an improved control strategy that combines DTC with PI tuning optimized by the Sailfish Optimization algorithm (SFO), which delivers smoother torque, more stable low-speed operation, and stronger robustness during sudden changes in load. In this regard, the PI controller was tested under different levels of torque and compared with the traditional Gray Wolf Optimization (GWO-PI) algorithm controller, as well as PI and PID controllers, and the performance of each of them was evaluated for different torque levels at speeds of 600 rpm and 2000 rpm during physical experiments. The simulation results showed that the Sailfish-PI controller, compared to the others, recorded the fastest response with a rise time of 2.1 ms and settling time of 2.9 ms under 2.39 Nm nominal torque at 2000 rpm speed; in addition, it continuously showed the lowest values of overshoot and undershoot as torque increased. It also maintained the most accurate and consistent performance, keeping the peak rpm almost flat and extremely near to the target of 2001 rpm. Therefore, in systems that require variable speed and torque while operating, such as electric automobiles, the proposed method is suitable for application.
Microgrid system for electric vehicle charging stations integrated with renewable energy sources using a hybrid DOA–SBNN approach Kommoju Naga Durga Veera Sai Eswar, M. Arun Noyal Doss, Mohammad Shorfuzzaman, Ali Elrashidi Frontiers in Energy Research, 2025 Microgrid-equipped electric vehicle charging stations offer economical and sustainable power sources. In addition to supporting eco-friendly mobility, the technology lowers grid dependency and improves energy reliability. The manuscript introduces a hybrid technique for efficient electric vehicle (EV) charging integrating the Dollmaker Optimization algorithm (DOA) and spatial Bayesian neural network (SBNN). This method optimizes the joint operation of photovoltaic (PV), wind turbines (WTs), supercapacitors (SCs), and battery energy storage systems (BESSs) in microgrids to enhance EV charging station efficiency, reliability, and power quality while reducing grid outages. The SBNN predicts EV load demand for improved efficiency and reliability, while DOA manages microgrid (MG) fluctuations to ensure seamless EV charging. The MG system features a four-phase inductor coupled interleaved boost converter (FP-ICIBC) and a fractional-order proportional-integral-derivative (FOPID) controller for optimal power management. An evaluation in MATLAB compares DOA–SBNN with existing approaches, demonstrating its effectiveness in enhancing EV charging performance. The proposed method outperforms all current techniques, including the Multi swarm Optimization (MSO), the Multi-Objective Gray Wolf Optimizer (MOGWO), and the Modified Multi-objective Salp Swarm Optimization algorithm (MMOSSA). The results show that the energy efficiency of the recommended approach is 19.19%, 26.15%, and 32.57% higher than the three current techniques, respectively, and that of total harmonic distortion (THD) is 19.09%, 25.85%, and 31.17% lower than those three techniques, respectively.
Implementation of a Microgrid System with a Four-Phase Inductor Coupled Interleaved Boost Converter for EV Charging Stations Kommoju Naga Durga Veera Sai Eswar, Mohan Arun Noyal Doss, Mohammed Alruwaili, Waleed Mohammed Abdelfattah Energies, 2024 Electric vehicle charging stations are essential to enable broad reception due to the rise in electric vehicles in the transportation industry because they will lessen range anxiety concerns about distance. The primary objective of this work is to design a microgrid that is effective and affordable for an electric vehicle charging station that combines a photovoltaic, wind, and utility grid energy system (optional) as a principal source of energy. The proposed study employs a four-phase inductor coupled interleaved boost converter which is compact and effective with high power output which results in charging a vehicle within 33 min. A perturb and observe MPPT approach based on DC converters is used along with the digital 2PI controller to increase the effectiveness and performance of distributed energy systems. To make the converter a hassle-free operation, an interleaving technique is applied to the developed converter which results in ripple reduction, which results in an increase in the output current and voltage gain, with high power density and efficiency. For better understanding, real-time data for 2W/3W/4W are acquired and tested for various conditions and the maximum state of charge for the battery is gained within one-third of the usual time. At present, the interleaved converter’s operation is theoretically examined, and the behavior of the converter and the charging conditions of several electric vehicle systems are compared and shown in the simulation analysis.
Design and analysis of dynamic wireless power transfer for electric vehicle charging application M. Parthasarathi, S. George Fernandez, M. Arun Noyal Doss Aip Conference Proceedings, 2024 The depletion of oil and the emission of greenhouse gases are getting attention worldwide. The transport sector is one of the major causes in producing greenhouse gases next to the industry sector. Electric Vehicles are a promising solution to minimize the negative impacts caused by conventional vehicles on the environment. However, problems associated with introducing EVs arise, such as inadequate charging facilities. The wireless charging system can make EVs more accessible. This mode of charging allows the battery to get charged from the power source without the electric cables and wires. This paper proposes the design and simulation of parallel-parallel configuration for the dynamic charging. ANSYS Maxwell software is used for design and simulation of the coil. The power transfer between the transmitter coils and receiver coil is tested by taking the parallel compensation. The system is simulated and demonstrated for 5cm air gap between the coils. The output waveforms has 18.9 kHz frequency. A DSO is used instead of multimeter as the work deals with high frequency. The DSO is used to measure output voltage across load and thus power transmitted was calculated. In this work, the misalignment between transmitter and receiver coils also improved.
Analysis of Vienna rectifier N. Kalaiarasi, S. George Fernandez, M. Arun Noyal Doss, U. Vaishali, M. Jayakumar, V. Aridoss, S. Nithyanandham Aip Conference Proceedings, 2024
Gesture recognition vehicle using PIC microcontroller K. Selvakumar, Palanisamy R, M.Arun Noyal Doss, P. Gopi, A. Esakkipandi, L. Mathivadhanam, T. Abul Kalam Asath Indonesian Journal of Electrical Engineering and Computer Science, 2020
Performance comparison of seven level inverter and nine level inverter with minimum devices International Journal of Control Theory and Applications, 2016
A new single-phase multilevel inverter with reduced number of switches for solar applications International Journal of Control Theory and Applications, 2016
A cost effective speed control method for BLDC motor drive International Journal of Control Theory and Applications, 2016
Cogging torque reduction in brushless DC motor by applying various slot modification techniques in stator tooth International Journal of Control Theory and Applications, 2016
Bidirectional AC/DC converter pwm strategy with feed forward control for grid tied micro grid systems International Journal of Applied Engineering Research, 2015
Cogging torque reduction in brushless dc motor by reshaping of rotor magnetic poles with grooving techniques International Journal of Applied Engineering Research, 2015
Minimization of harmonics and torque ripple in BLDC motor using PI & fuzzy controller International Journal of Applied Engineering Research, 2015
Modeling and simulation of BLDC motor for minimizing the cogging torque, harmonics and torque ripples International Review on Modelling and Simulations, 2013