BITS Faculty Publications
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Item Development of a fuzzy-pi tuned bidirectional charger for electric three-wheeler applications(IEEE, 2025-05) Bansal, Hari Om; Singh, DheerendraThe 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.Item Hardware-in-loop implementation of an adaptive MPPT controlled PV-assisted EV charging system with vehicle-to-grid integration(Springer Nature, 2025-08) Bansal, Hari OmThe penetration of electric vehicles (EVs) into society needs extensive charging infrastructure. The existing charging system solely depends on the grid supply, which is essentially fossil fuel-dependent and leads to carbon emissions and environmental pollution. This can be minimized by incorporating renewable energy into the charging grid. This article presents a charging scheme combining photovoltaic (PV) and grid, offering a clean and dependable charging plan to sustain green transport. The proposed work presents the modelling and controlling a 10 kW EV charging/discharging framework integrating PV and grid. This work has multi-fold objectives: i) the development of an intelligent hybrid maximum power point tracking (MPPT) strategy, ii) the design of a fuzzy logic controlled bidirectional charger, iii) the setup of a PV-grid integrated charging system, and iv) the implementation of vehicle-to-grid (V2G) operation. The proposed charging system utilizes PV power and seamlessly switches to grid power whenever required. Since the performance of the PV source is affected by varying temperatures and irradiance, MPPT methods are needed to extract maximum power from the PV source. This paper developed and compared perturb and observe (P&O), Particle swarm optimization (PSO), and hybrid PSO + Adaptive neuro-fuzzy inference system (ANFIS) based algorithm for MPPT. The findings indicate that the PSO + ANFIS-driven method offers the highest tracking efficiency of 99.5%. This algorithm is also tested under dynamic partial shading conditions (PSC) to ensure robustness, and it led to achieving fast convergence and high efficiency despite multiple power peaks. In addition, the designed bidirectional charging system maximizes solar energy collection, minimizes the charging cost, and improves grid stability through demand balancing. The overall system is validated in a hardware-in-loop real-time environment through FPGA-based OPAL-RT.Item A Study on DC Fast Charging of Electric Vehicles(Springer, 2023-07) Bansal, Hari OmAs the penetration of electric vehicles (EVs) is increasing, their efficient charging becomes very important. This paper presents the simulation of various charging algorithms for the Li-Ion Batteries of EVs and their comparison with each other. Various charging algorithms like Constant Current (CC), Constant Voltage (CV), and Constant Current-Constant Voltage (CC/CV) algorithms have been discussed along with various DC-DC charging topologies like the Buck converters and the LLC Resonant Converter have been discussed. Finally, voltage matching algorithm has been proposed, simulated, and incorporated into the CC/CV algorithm and compared to previous results.Item An extensive review on hybrid electric vehicles powered by fuel cell-enabled hybrid energy storage system(Springer, 2023) Bansal, Hari OmTo overcome the air pollution and ill effects of IC engine-based transportation (ICEVs), demand of electric vehicles (EVs) has risen which reduce *gasoline consumption, environment degradation and energy wastage, but barriers—short driving range, higher battery cost and longer charging time—slow down its wide adoptions and commercialization. Although to overcome such issues, EV variants —HEVs and PHEVs—were also brought into the market but not that successful either. The use of ICE in HEVs and PHEVs increases fossil fuel dependency. Thus, the research focus shifted towards fuel cell-powered electric vehicles (FCEVs) which offer negligible emission and higher efficiency than EV variants. Though a moderate research work has been done on FCEVs, still its wide expansion is limited, facing severe challenges commonly related to fuel cost, selection of energy units, power electronic interfacing, component sizing and energy management. This paper presents an extensive exploration on EV variants, their issues, an in-depth comparison of latest topologies for FCEVs and optimum arrangement of HESS, designed by energy unit’s integration, i.e. FC, battery and UCs, to encounter the dynamic power demand and develop a performant model for transportation. In last, progress and possible future research areas are discussed. In short, this paper reveals all contemporary information of FCHEV technology to the scientists and scholars who are working in this particular arena.