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The DC-DC converter is an essential subsystem in electric vehicle (EV) chargers, and most converters depend on a single-input single-output structure, which can be costly when multiple charging units are needed. Additionally, these converters offer limited voltage gain, restricting charging configurations. This paper proposed a dual-stage high-gain converter that operates in a boost mode with reduced components, using an inductor, capacitor, and 2-diodes (LC2D) to provide high-gain output. The proposed Dual Inputs and Dual Outputs (DIDO) converter tied with Photovoltaic (PV) and constant DC acting as inputs and two different voltage levels EV chargers are serving as the output. The proposed converter operates at continuous conduction mode (CCM), achieving high efficiency and reliability with fewer losses. The proposed work was designed for 418V and 85V systems in MATLAB/Simulink, and the results were validated with hardware implementation. The proposed converter delivers high-gain output to the electric vehicle application with 92.2 % efficiency.
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http://dx.doi.org/10.1016/j.heliyon.2024.e38048 | DOI Listing |
J Safety Res
September 2025
Department of Civil Engineering, College of Engineering, Qassim University, 51452, Saudi Arabia. Electronic address:
Introduction: The recent rise in e-scooter usage has reshaped urban mobility but has also led to a significant increase in e-scooter-related injuries, raising critical safety concerns. While existing research has primarily focused on post-crash medical outcomes and general risk comparisons, substantial gaps remain in identifying specific risk factors associated with e-scooter crashes and utilizing interpretable analytical approaches.
Method: This study addresses these gaps by analyzing 2,400 e-scooter crash records from the UK STATS19 database using advanced machine learning models to predict injury severity.
Epigenomics
September 2025
Institute of Clinical Medicine, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
Aims: Psychological resilience refers to an individual's capacity to adapt to adverse events. MicroRNAs (miRNAs) play a crucial role in regulating post-transcriptional processes, while small extracellular vesicles (sEVs) act as transport vehicles. This study aimed to employ genome-wide profiling to identify and validate differences in the expression of resilience-associated sEV-miRNAs between low resilience (LR) and high resilience (HR) in young adults.
View Article and Find Full Text PDFSci Rep
September 2025
Fukushima Renewable Energy Institute, Koriyama, Japan.
Ultra-fast charging stations (UFCS) present a significant challenge due to their high power demand and reliance on grid electricity. This paper proposes an optimization framework that integrates deep learning-based solar forecasting with a Genetic Algorithm (GA) for optimal sizing of photovoltaic (PV) and battery energy storage systems (BESS). A Gated Recurrent Unit (GRU) model is employed to forecast PV output, while the GA maximizes the Net Present Value (NPV) by selecting optimal PV and BESS sizes tailored to weekday and weekend demand profiles.
View Article and Find Full Text PDFISA Trans
August 2025
Department of Vehicle Engineering and Jiangsu Engineering Research Center of Vehicle Distributed Drive and Intelligent Wire Control Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China; Department of Vehicle Engineering and Jiangsu Engineering Research Center of Vehi
The steer-by-wire (SbW) system, as the core component of vehicle steering, needs to track the front wheel angle accurately. To mitigate the angle tracking accuracy degradation caused by D-Q axes coupling, time-varying motor electrical parameters, and load disturbance, a fractional-order adaptive fuzzy decentralized tracking control (FAFDTC) strategy is proposed in this paper. First, considering time-varying motor parameters, D-Q axes coupling, and fractional-order characteristics of components, a fractional-order SbW interconnected system is constructed to enhance its ability to characterize nonlinearities, time-varying dynamics, and system coupling.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
September 2025
Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh 15213, Pennsylvania.
We model the effect of plug-in electric vehicle (EV) adoption on U.S. power system generator capacity investment, operations, and emissions through 2050 by estimating power systems outcomes under a range of EV adoption trajectory scenarios.
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