Browsing by Author "Bansal, Hari Om"

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Adaptive artificial neural network based control strategy for shunt active power filter
(IEEE, 2016) Ajmera, Pawan K.; Bansal, Hari Om
Shunt active power filter (SAPF) is used to mitigate the current harmonics and to improve the power factor. In this paper, Adaptive linear-neuron (ADALINE) based phase lock loop (PLL) controlling scheme is presented for SAPF. ADALINE networks estimate the fundamental supply frequency. This scheme detects the phase information of the supply voltage and also used for parallel computing as it provides faster convergence. This algorithm is trained by least-mean squares (LMS) rule which offers low computational burden on the system. In this work, ADALINE is tuned using particle swarm optimization (PSO) technique to improve the dynamic performance of the system. The results obtained are compared with conventional PLL control technique and are found to be significantly better. The performance of the proposed ADALINE based control algorithm is validated using MATLAB/Simulink.
Adaptive Artificial Neural Network Based Control Strategy for Shunt Active Power Filter” IEEE International Conference on Electrical Power and Energy Systems (ICEPES), December 14-16, 2016, MANIT Bhopal, India.
(IEEE, 2016) Bansal, Hari Om; Ajmera, Pawan K.
Shunt active power filter (SAPF) is used to mitigate the current harmonics and to improve the power factor. In this paper, Adaptive linear-neuron (ADALINE) based phase lock loop (PLL) controlling scheme is presented for SAPF. ADALINE networks estimate the fundamental supply frequency. This scheme detects the phase information of the supply voltage and also used for parallel computing as it provides faster convergence. This algorithm is trained by least-mean squares (LMS) rule which offers low computational burden on the system. In this work, ADALINE is tuned using particle swarm optimization (PSO) technique to improve the dynamic performance of the system. The results obtained are compared with conventional PLL control technique and are found to be significantly better. The performance of the proposed ADALINE based control algorithm is validated using MATLAB/Simulink.
Blockchain-enabled secure transactions in V2G networks
(IEEE, 2025-06) Dua, Amit; Bansal, Hari Om
The increasing integration of Vehicle-to-Grid (V2G) systems in modern energy networks necessitates secure, transparent, and efficient mechanisms for energy trading. However, existing centralized approaches are susceptible to cyberattacks, lack transparency, and face scalability challenges. This paper proposes a blockchain-enabled decentralized platform to ensure secure and tamper-proof energy transactions between electric vehicles (EVs) and the grid. The system leverages smart con-tracts for automated settlements, cryptographic protocols for enhanced data privacy, and artificial intelligence (AI) models for real-time anomaly detection and fraud prevention. By integrating blockchain's transparency and immutability with AI's adaptability, the proposed solution addresses key challenges in trust, scalability, and cybersecurity. A prototype implementation demonstrates the platform's effectiveness, achieving improved transaction throughput, reduced latency, and enhanced resistance to malicious activities compared to traditional systems. Extensive simulations validate the scalability and resilience of the proposed framework under varying transaction loads and attack scenarios. This work lays the foundation for a transformative approach to energy trading, fostering increased trust, participation, and sustainability in V2G markets.
Commercial Sustainability of Vehicle-to-Grid Concept: An Overview
(IEEE, 2020) Bansal, Hari Om
This paper talks about the vehicle-to-grid (V2G) idea, which is a system wherein electric vehicles (EVs) communicate with the power grid to trade services by either returning electricity to the grid or by regulating the power grid. The paper deals with the theoretical incentives bringing together the four players of V2G: car owners, power firms, aggregators and the society; and the barriers which they face for the commercialization of V2G. The paper then goes on to focus on the Indian market and the specific obstacles faced by the Indian market for the incorporation of V2G.
A comprehensive assessment of the techno-socio-economic research growth in electric vehicles using bibliometric analysis
(Springer, 2021-10) Bansal, Hari Om; Goyal, Praveen
Electric vehicles (EVs) have proved capable of solving many of the environment’s problems such as reducing harmful pollutants’ emission along with having greater motor efficiency than gasoline vehicles. This study presents a bibliometric analysis of 10,426 publications from the year 1989 to 2020, obtained from Web of Science™ (WoS) core collection (CC). An initial citation analysis was done using Histcite to identity the leading nations, institutes, authors, and journals performing research related to EVs. Following this, a co-citation analysis was performed using VOSviewer, which generates clusters that are further analyzed to identify the key domains in EV research. A research overview in EVs over the last three decades is presented that can serve various stakeholders in this field of study. The results of this study will highlight the critical research areas in the field of EVs. Additionally, it will also provide various insights that may help the policymakers, practitioners and associations to accelerate EV adoption by the end-users.
A comprehensive review on hybrid electric vehicles: architectures and components
(Springer, 2019-03) Bansal, Hari Om; Singh, Dheerendra
The rapid consumption of fossil fuel and increased environmental damage caused by it have given a strong impetus to the growth and development of fuel-efficient vehicles. Hybrid electric vehicles (HEVs) have evolved from their inchoate state and are proving to be a promising solution to the serious existential problem posed to the planet earth. Not only do HEVs provide better fuel economy and lower emissions satisfying environmental legislations, but also they dampen the effect of rising fuel prices on consumers. HEVs combine the drive powers of an internal combustion engine and an electrical machine. The main components of HEVs are energy storage system, motor, bidirectional converter and maximum power point trackers (MPPT, in case of solar-powered HEVs). The performance of HEVs greatly depends on these components and its architecture. This paper presents an extensive review on essential components used in HEVs such as their architectures with advantages and disadvantages, choice of bidirectional converter to obtain high efficiency, combining ultracapacitor with battery to extend the battery life, traction motors’ role and their suitability for a particular application. Inclusion of photovoltaic cell in HEVs is a fairly new concept and has been discussed in detail. Various MPPT techniques used for solar-driven HEVs are also discussed in this paper with their suitability.
Design and Control of a Bi-directional CLLC Resonant Converter For Low voltage Energy Storage Systems
(IEEE, 2020) Bansal, Hari Om
This paper presents the design of a bi-directional CLLC converter with an Integrated transformer for energy storage systems (ESS) applications (48 V batteries). As the distributed energy generation and storage are gaining momentum it Is required to have ESS that can regulate the power bi-directionally, presently the ESS are bulky in size, to enhance the power density and converter efficiency, an integrated transformer is introduced and simulated using 3D Finite Element Analysis (FEA). Essentially, a simple PI-based voltage/current control loop Is implemented on a 32-bit microcontroller (TMS320F28379D). Also, synchronous rectification (SR) Is implemented by controlling the turn-on and turn-off delays on rectifier sides, respectively. The design and control of the CLLC converter are verified through the experimental results. A 300 kHz, 700 W prototype Is built with the peak conversion efficiency of 96.6% while charging and 96.4% while discharging.
Design and Control of Wind integrated Shunt Active Power Filter to Improve Power Quality
(IEEE, 2018) Bansal, Hari Om
In this paper wind energy conservation system (WECS) with shunt active power filter (SAPF) is proposed for harmonics elimination, power factor correction, reactive power compensation and grid current balancing. Adaptive neuro fuzzy inference system (ANFIS) based controller is implemented at WECS side to control the boost converter to achieve MPP and at SAPF sides to minimize voltage variations and enhance power quality. Here, synchronous reference frame (SRF) theory based reference current generation technique is employed in SAPF. The proposed scheme is implemented in MATLAB/Simulink. The results confirm that this method has better performance and can maintain total harmonic distortion (THD) level of the system within the IEEE standard 519.
Design and real-time validation of PI and Fuzzy Logic tuned photovoltaic integrated DSTATCOM to improve power quality
(Springer, 2022-07) Bansal, Hari Om
Power loss and malfunctioning of equipment due to current and voltage harmonics produced by nonlinear loads are major concerns for both power suppliers and consumers. This paper employs DSTATCOM to mitigate these harmonic distortions in distribution systems. DSTATCOM is a current controlled voltage source PWM converter with passive components. It supplies compensating current that eliminates current harmonics and provides reactive power compensation thereby providing a smooth source current. The performance of DSTATCOM is controlled using proportional integral and fuzzy logic–based control (FLC) schemes to improve power quality at dynamic loading. As the penetration of photovoltaic (PV) systems in energy production is significant, the power quality issues for PV-integrated systems have also been investigated. The maximum power point for a PV array is tracked using perturb and observe and FLC methods. The complete system is simulated in MATLAB and extensively investigated for a large range of balanced and unbalanced nonlinear load conditions. The simulation results are validated in real time through the hardware in loop (HIL) test bench using Opal-RT controller. The proposed PV-integrated DSTATCOM with FLC yields better performance in terms of DC link voltage settling time, total harmonics distortion, and smooth source current as compared to other schemes.
Design of an Improved Q-ZSI with Fault Tolerance for EV Applications
(IEEE, 2019) Bansal, Hari Om; Singh, Dheerendra
In this paper, a Fault Tolerant Quasi Z-source Inverter (Q-ZSI) topology has been proposed for three phase induction motor drive systems. The proposed topology incorporates the ability to detect an open circuit or a short circuit fault in any of the switching arms. Once a fault is detected the firing signal is transferred to another switching arm to ensure uninterrupted flow of power. The main goal of this paper is to design a rugged inverter topology that can give better performance than the standard Z-Source Inverters (ZSI) in harsh environments where the switches are more prone to faults.
Design of an Intelligent PD Controller for Artificial Pacemaker
(IEEE, 2012) Bansal, Hari Om; Kumar, Rajneesh
This paper presents the design and analysis of an intelligent control system for regulating the heart rate using a pacemaker. The considered model of the heart is composed of the cardio vascular system duly energised by one pacemaker and operates in closed loop manner. The proposed design emphasises on the optimality in control process. In this work genetic algorithm is used to achieve the optimality. The proposed system is found to be stable with appropriate gain and phase margins. A comparative study of controller tuning using classical approach and the proposed method is made and the best is finally presented. The controllability and observability of the complete system is tested and found to be better for the proposed system
Determination of Critical Clearing Time in a Power System Using Support Vector Machine
(SSRN, 2009-10) Bansal, Hari Om
A Support Vector Machine (SVM) is a new supervised machine learning method based on the statistical learning theory. It is a very useful method for classification and regression in small-sample cases such as critical clearing time (TCC) calculations, fault diagnosis, etc. In this paper, an effort has been made to determine the TCC using SVM for a system having exposed to a fault and the results obtained are compared with the results of ‘Step-by-Step’ method - a classical method for determining TCC - to prove its superiority over classical methods
Development of a fuzzy-pi tuned bidirectional charger for electric three-wheeler applications
(IEEE, 2025-05) Bansal, Hari Om; Singh, Dheerendra
The growing worldwide market for electric vehicles (EVs) has put pressure on automotive system developers to improve charging efficiency and enhance the charging infrastructure. Bidirectional chargers support the grid by flowing the power in the two directions, i.e. functioning in both V2G and G2V modes. In this paper, a bidirectional converter interfaces a fixed DC bus that supports EV battery charging and discharging operation, is presented and simulated in a MATLAB environment. A Fuzzy Logic tuned Proportional Integral (FLPI) is designed using MATLAB Simulink to enhance the charger's performance. This paper also presents a performance comparative analysis of the FLPI and conventionally used PI Controller, highlighting the FLPI controller's advantages. FLPI is better than the conventional PI because of low errors, faster response time, better transient performance and improved robustness. The charger is developed and simulated for a 600V DC supply with a peak output power of 10kW. The simulation results demonstrate the charging and discharging of a 72V 150 Ah Lithium-ion (Li-ion) battery for electric-3-wheeler applications.
Development of an adaptive neuro-fuzzy inference system–based equivalent consumption minimisation strategy to improve fuel economy in hybrid electric vehicles
(IET, 2020) Bansal, Hari Om; Singh, Dheerendra
The most viable option to achieve the goals of saving energy and protecting the environment is to replace conventional vehicles with hybrid electric vehicles (HEVs). In HEVs, the operational characteristics of an internal combustion engine (ICE) and an electric motor (EM) are different from each other and thus require an adaptive control strategy to achieve higher fuel economy along with smooth operation and better performance of the vehicle. An energy management control strategy is proposed for an HEV based on an adaptive network-based fuzzy inference system (ANFIS). The proposed adaptive equivalent consumption minimisation strategy decides the power to be drawn from ICE and EM based on input parameters such as the speed of the vehicle, the state of charge of the battery, the EM torque and the ICE torque. The whole system is simulated in an advanced vehicle simulator tool. The proposed non-linear controller has also been tested for real-time behaviour using a field-programmable gate array–based MicroLabBox hardware controller to compare its performance against existing controllers. The authors compared the fuel economy obtained using the proposed method with several other methods available in the literature. The comparison clearly reveals that the proposed ANFIS-based method results in better optimization of energy and hence offers better fuel economy. The urban dynamometer driving schedule has been employed for this analysis.
Development of an ANFIS based equivalent consumption minimization strategy to improve fuel economy in Hybrid Electric Vehicles
(IET, 2021-03) Singh, Dheerendra; Bansal, Hari Om
The most viable option to achieve the goals of saving energy and protecting the environment is to replace conventional vehicles with hybrid electric vehicles (HEVs). In HEVs, the operational characteristics of an internal combustion engine (ICE) and an electric motor (EM) are different from each other and thus require an adaptive control strategy to achieve higher fuel economy along with smooth operation and better performance of the vehicle. An energy management control strategy is proposed for an HEV based on an adaptive network-based fuzzy inference system (ANFIS). The proposed adaptive equivalent consumption minimisation strategy decides the power to be drawn from ICE and EM based on input parameters such as the speed of the vehicle, the state of charge of the battery, the EM torque and the ICE torque. The whole system is simulated in an advanced vehicle simulator tool. The proposed non-linear controller has also been tested for real-time behaviour using a field-programmable gate array–based MicroLabBox hardware controller to compare its performance against existing controllers. The authors compared the fuel economy obtained using the proposed method with several other methods available in the literature. The comparison clearly reveals that the proposed ANFIS-based method results in better optimization of energy and hence offers better fuel economy. The urban dynamometer driving schedule has been employed for this analysis.
Development of an Intelligent POD Controller to Mitigate Power Oscillations
(IEEE, 2020) Bansal, Hari Om
Mitigation of power oscillations is a key challenge while dealing with power system performance. The stability of the power system is more affected and observable when it is subjected to different faults. In this paper power oscillation damping (POD) controller is used as a supplementary controller to damp-out the oscillation in the power system. Which is designed using a Static Synchronous Series Compensator (SSSC) as a FACTS (Flexible AC transmission system) controller. MATLAB/Simulink software is used to investigate the time domain behavior of SSSC under various conditions. The investigations have validated that the proposed controller effectively improved the performance of power system.
Development of fuzzy logic controller for photovoltaic integrated shunt active power filter
(IOS, 2019-06) Bansal, Hari Om
This paper presents the design, modeling, and implementation of a photovoltaic (PV) integrated shunt active power filter (SAPF) for clean power generation along with power quality improvement. The system uses fuzzy logic control (FLC) for maximum power point tracking (MPPT) and SAPF control. The proposed system implements synchronous reference frame theory based direct power control strategy using hysteresis control. The system performance is evaluated in real-time under-balanced/unbalanced and nonlinear load conditions using field-programmable gate array (FPGA) based computational engine with different controllers. The performance is observed to be better with FLC as compared to traditional controllers.
Disturbance observer-based sliding mode control of boost-flyback converter
(IEEE, 2025-04) Bansal, Hari Om; Gautam, Aditya R.
This paper presents a disturbance observer based sliding mode control of single-input double-output Boost-flyback dc-dc converter. The converter supplies two outputs i.e. flyback side output and boost side output through common magnetic path of flyback transformer. The power flow through common magnetic path poses the challenges of cross-coupling and crossregulation at line and load transient operations of converter. In this paper, these challenges are alleviated using sliding mode control approach. Moreover, a disturbance observer is also designed to alleviate the effect of cross-regulation at the load transients. The performance of proposed control technique is validated using simulation results.
The efficient operating parameter estimation for a simulated plug-in hybrid electric vehicle
(Springer, 2021-10) Singh, Dheerendra; Bansal, Hari Om
Hybrid electric vehicles (HEVs) and plug-in HEVs (PHEVs) are indispensable tools in reducing greenhouse gas emissions to fight the twin evils of pollution and climate change. In these vehicles, battery replacement and fuel costs are the major recurring costs over a lifetime. Hence, there is a growing attempt to develop strategies that reduce the long-run expenditure in these vehicles without compromising on performance levels. Further, an increase in the fuel economy is also required for the effective penetration of these vehicles in society. Here, the authors attempt to identify the optimal operating values for battery state of charge (SoC), power ratings of motor, and fuel converter to increase the battery life and fuel economy without degrading the vehicle performance. The simulations have been carried out on Ford C-Max Energi (2016) as a representative for PHEVs based on the Urban Dynamometer Driving Schedule (UDDS) and Highway (HWY) driving cycles. The software used for these simulations is the future automotive systems technology simulator (FASTSim), developed by the National Renewable Energy Laboratory (NREL). In this paper, firstly, the effect of important parameters like battery SoC, fuel converter power, and motor power on HEVs’ driving range, battery life, fuel economy, cost, and charge-depleting range has been analyzed. Based on this analysis, the optimal values of the parameters have been estimated. These parameters have resulted in improvements of driving range by 4.3% and battery life by 18% at a minute cost of a 1% decrease in the charge-sustaining battery life and a 0.4-s increase in the time the car takes to hit 60 mph from the rest. This paper presents a simple, effective, and new approach that explores the effect of altering the existing design parameters on vehicle performance, without manipulating, adding, or deleting any component or controller. This can further be extended to study the impact of various other parameters in the proposed work and opens a way to explore other parameters that exist in various other components of XEVs (where X can be H/PH//F). This study will help in achieving optimal cost reduction in these vehicles.
Electronic aid for elder and sick people IR-remote controlled switch board for changing state of electrical appliances
(IEEE, 2014) Bansal, Hari Om
This paper propose a wireless switch board for easy-accessibility in an hospital-like environment for controlling various electrical appliances like light, fan, etc. without interference with similar wireless switches in adjoining room. The data signal is communicated to receiver wirelessly by IR Remote Controller. The receiver consists of IR Receiver, TSOP1838, to read data signal operating at 38 kHz and a microcontroller to process data and communicate trigger signal to change the state of switch.