Ram Khelawan Saket

This paper introduces a non-isolated, multi-functional on-board charger for elec- tric vehicles (EVs) designed to accommodate various charging needs. The charger integrates grid-based AC charging with power factor correction (PFC), a solar- powered DC charging system using an interleaved buck-boost DC/DC converter, and an emergency charge-sharing model for vehicle-to-vehicle (V2V) energy transfer. The study provides an in-depth analysis of a non-isolated buck-boost PFC AC/DC converter operating in discontinuous conduction mode (DCM) for grid-to-vehicle (G2V) charging. The configurations are optimized for PFC with straightforward and effective control strategies. The interleaved operation of the converter minimizes current stress on semiconductor devices, reduces the need for input filters, and improves overall efficiency. The proposed converter is com- pact and versatile, delivering 1 kW of power at unity power factor (UPF) even under varying AC input conditions, as demonstrated through simulation results. Unlike other literature reviews, this paper highlights the innovation and poten- tial impact of this multi-functional plug-in EV battery charger, advancing the field of sustainable transportation.

Linear induction motors are in vogue these days. High‐speed electromagnetic propulsion powered by three‐phase pulsed power is increasingly sought in emerging industrial projects, such as hyperloop transportation, factory automation for heavy machinery and defence applications that require rapid acceleration of heavy masses, including launchers and electromagnetic aircraft launch systems (EMALS). These energy applications require ensuring reliable and error‐free operation under dynamic conditions. The Double‐Sided Linear Induction Motor (DSLIM), featuring a long primary and a short secondary that incorporates distributed winding, exhibits oscillatory behaviour in its dynamic thrust‐speed characteristics, as well as the occurrence of zero or negative thrust during acceleration, resulting in delayed movement progress of the mover. These effects can be mitigated by optimising the mover material and winding configuration. Case studies of 21‐m and 90‐m long‐primary DSLIMs, housing tooth windings with German silver as a conducting sheet, comprising the secondary mover, were conducted to accelerate a heavy mass to high speeds required for the above‐mentioned applications. A double‐layer DSLIM with a variable‐voltage–variable‐frequency supply is analysed, and prototype experimental results for a 1.5 m configuration are compared to a double‐layer three‐phase tooth winding with distributed winding.

This paper proposes a novel model-free control (MFC) strategy for hybrid electric vehicles (EVs) powered by a proton exchange membrane fuel cell (PEMFC) and a supercapacitor (SC). Unlike conventional model-based approaches that depend on accurate system identification and parameter tuning, the proposed framework employs ultra-local models to adapt dynamically to system variations without explicit modeling. The hybrid architecture is implemented using an interleaved boost converter for the PEMFC and a bidirectional buck–boost converter for the SC, coordinated to supply propulsion power and enable regenerative braking. Comprehensive MATLAB/Simulink simulations demonstrate that the proposed MFC achieves <3% current tracking error for both PEMFC and SC, ~750 ms settling time for PMSM speed variations, and <120 ms response for power transitions, while the DC bus voltage remains tightly regulated under dynamic load disturbances. Hardware-in-the-loop (HIL) validation on an OPAL-RT 5600 platform further confirms the method’s feasibility, showing a 20% reduction in execution time and enhanced robustness against parameter uncertainties compared to classical PI control. Experimental results also verify stable current sharing in interleaved converters, accurate voltage regulation in the SC branch, and smooth torque generation in the PMSM drive. Overall, the proposed control strategy provides a computationally efficient, fault-tolerant, and plug-and-play solution for next-generation EVs by reducing calibration effort and ensuring reliable operation under nonlinear and uncertain conditions, while demonstrating clear potential for real-time automotive applications.

DC Microgrid (DCMG), fed from renewable energy sources (RESs), is one of the most efficient and cost-effective ways that integrate electric vehicles (EVs) for charging. However, the DCMG, without any storage units, is prone to voltage fluctuations under uncertain weather conditions in addition to EV loads. Thus, the batteries of the EVs connected to DCMG can act as storage units to alleviate voltage fluctuations through their charging/discharging operations. This paper presents an energy management strategy of DCMG utilizing RESs, load, AC grid, and EV batteries to maintain its stability using vehicle-to-grid (V2G) and grid-to-vehicle (G2V) operations through a BDDC converter. Besides, in this work, a bidirectional DC-DC converter (BDDC) control technique is proposed, which contains an additional voltage loop in conjunction with a power loop to minimize the DC bus voltage fluctuations. The proposed approach is evaluated under various operating conditions using a MATLAB/Simulink model of a DCMG system. Further, using a WAVECT (WCU300) control interface, the proposed control has been successfully validated on an experimental test bed. It is observed that the proposed BDDC control stabilizes DC bus voltage under different power conditions while maintaining the power balance in the system.

This paper proposes an improved model for the reliability assessment of power systems considering component failures of variable energy resources (VER). The inherent intermittency of VER such as solar photovoltaic (PV) and wind farms, along with their susceptibility to component failures, present significant challenges to reliable system operation. These issues, combined with power grid operation and network constraints, complicate the reliable operation of VER-integrated power systems. To address these concerns, this paper introduces a reliability assessment framework that considers VER input variability, its impact on component availability, and their resulting impact on overall system reliability. Stochastic models based on discrete Markov processes are developed to incorporate variable irradiance, wind speeds, and their effects on PV and wind component failure rates. A next-event and state transition-based approach is then developed to integrate the stochastic models into a mixed-timing sequential Monte Carlo simulation framework for composite reliability assessment. Case studies on the RTS-GMLC system demonstrate the effectiveness of the proposed model in evaluating the reliability of VER-integrated systems.