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- ItemAdvanced machine learning techniques for State-of-Health estimation in lithium-ion batteries: A comparative study(Elsevier, 2025-06-01) Sedlařík, Marek; Vyroubal, Petr; Capková, Dominika; Omerdic, Edin; Rae, Mitchell; Mačák, Martin; Šedina, Martin; Kazda, TomášThe accurate modeling and prediction of the State-of-Health (SOH) of lithium-ion (Li-ion) batteries are crucial for extending their lifespan, ensuring reliability, and minimizing the costs associated with extensive laboratory testing. This paper investigates the SOH estimation of Li-ion batteries utilizing advanced machine learning (ML) techniques. Specifically, 600 cycles were performed on Samsung INR18650–35E cells using the Constant Current Constant Voltage (CCCV) protocol. The input data for the ML methods were extracted from both charging and discharging cycles to achieve the best possible results. Data-driven models with different methodological foundations were used to predict SOH: Gaussian Process Regression (GPR), Support Vector Regression (SVR), and from the field of Artificial Neural Networks (ANN), Feed-Forward Neural Network (FFNN) and Adaptive Neuro-Fuzzy Inference System (ANFIS), which utilizes fuzzy logic. The input features for the ML methods were analyzed using Pearson Correlation Analysis (PCA), and additional inputs for the ANFIS method were selected using Exhaustive Search (ES) to identify the optimal combination of inputs with the lowest Root Mean Square Error (RMSE). The individual ML methods were evaluated on datasets of various sizes using the features with the highest correlation to SOH and the full set of features to detect overfitting. Further experiments explored the dependency of RMSE on the amount of training data, and SOH estimation of one battery was performed using training data from another. Overall, experiments show that nearly all methods achieved RMSE below 0.5% for SOH estimation, with SVR proving the most stable technique and ANFIS excelling with meticulously optimized configurations.
- ItemAn Experimental and Numerical Analysis of the Influence of Surface Roughness on Supersonic Flow in a Nozzle Under Atmospheric and Low-Pressure Conditions(MDPI, 2025-04-16) Šabacká, Pavla; Maxa, Jiří; Bayer, Robert; Binar, Tomáš; Bača, Petr; Švecová, Jana; Talár, Jaroslav; Vlkovský, MartinThe ongoing research in Environmental Scanning Electron Microscopy (ESEM) is contrib-uted to in this paper. Specifically, this study investigates supersonic flow in a nozzle ap-erture under low-pressure conditions at the continuum mechanics boundary. This phe-nomenon is prevalent in the differentially pumped chamber of an ESEM, which separates two regions with a significant pressure gradient using an aperture with a pressure ratio of approximately 10:1 in the range of 10,000 to 100 Pa. The influence of nozzle wall rough-ness on the boundary layer characteristics and its subsequent impact on the oblique shock wave behavior, and consequently, on the static pressure distribution along the flow axis, is solved in this paper. It demonstrates the significant effect of varying inertial-to-viscous force ratios at low pressures on the resulting impact of roughness on the oblique shock wave characteristics. The resulting oblique shock wave distribution significantly affects the static pressure profile along the axis, which can substantially influence the scattering and loss of the primary electron beam traversing the differential pumping stage. This, in turn, affects the sharpness of the resulting image. The boundary layer within the nozzle plays a crucial role in determining the overall flow characteristics and indirectly affects beam scattering. This study examines the influence of surface roughness and quality of the manufactured nozzle on the resulting flow behavior. The initial results obtained from ex-perimental measurements using pressure sensors, when compared to CFD simulation re-sults, demonstrate the necessity of accurately setting roughness values in CFD calcula-tions to ensure accurate results. The CFD simulation has been validated against experi-mental data, enabling further simulations. The research combines physical theory, CFD simulations, advanced experimental sensing techniques, and precision manufacturing technologies for the critical components of the experimental setup.
- ItemThe Tuning of a CFD Model for External Ballistics, Followed by Analyses of the Principal Influences on the Drag Coefficient of the .223 Rem Caliber(MDPI, 2025-05-08) Maxa, Jiří; Šabacká, Pavla; Bayer, Robert; Binar, Tomáš; Bača, Petr; Švecová, Jana; Talár, Jaroslav; Vlkovský, Martin; Dobšáková, LenkaThis paper presents the subject of external ballistics. The presented research employs a contemporary methodological approach, integrating theoretical analysis, CFD simulations, and experimental measurements. External ballistics is characterized by a wide spectrum of physical phenomena that influence projectile trajectory. This contribution focuses on the analysis of drag force acting on a .223 rem caliber projectile in both subsonic and supersonic regimes. Based on experimental findings, a CFD model was refined and subsequently used to evaluate the drag force and drag coefficient, with a comparative analysis performed against G1 and G7 ballistic coefficient functions. Furthermore, the effect of the barrel length on the resultant outcome was assessed. The validated CFD model was employed to analyze the characteristics of shock waves generated at the projectile’s nose and their impact on the drag force, along with the influence of ambient temperature, particularly within the supersonic domain.
- ItemComprehensive Study of Rapid Capacity Fade in Prismatic Li-ion Cells with flexible packaging(Nature Research, 2024-11-18) Stravová, Zuzana; Klvač, Ondřej; Báňa, Jiří; Anothumakkool, Bihag; Zikmund, Tomáš; Blažek, Pavel; Kaiser, Jozef; Kazda, TomášPrismatic lithium-ion batteries (LIBs) are considered promising electric energy sources in electromobility applications due to their efficient space utilization. However, their sensitivity to external and internal influences and reduced durability lead to inflation risk and potential explosions throughout their lifecycle. These critical processes are strongly influenced by the inner construction of the cell, especially concerning the coating and mechanical fixation. This study subjects a commercially available prismatic LIB cell to comprehensive, correlative analysis employing various imaging techniques. The inner structure of the entire cell is visualized non-destructively by X-ray computed tomography (CT), enabling the identification of critical design flaws prior to electrochemical cycling. Electrochemical cycling simulates the battery lifecycle, and the cell is subsequently disassembled in the fully charged state. The usage of the inert-gas transfer system allowed the preparation of Broad Ion Beam (BIB) electrodes cross-sections in a fully native state and for the first time to observe the tearing of graphite particles due to over-lithiation. Established region labeling system allowed to use CT and scanning electron microscopy (SEM) correlatively to identify critical regions. After 100 cycles, a 40% capacity loss was observed and event diagram describing deagradation mechanisms, related both to the cell design and to the processes occurring at high load, was created.
- ItemCFD Analyses of Density Gradients under Conditions of Supersonic Flow at Low Pressures(MDPI, 2024-09-14) Bayer, Robert; Bača, Petr; Maxa, Jiří; Šabacká, Pavla; Binar, Tomáš; Vyroubal, PetrThis paper deals with CFD analyses of the difference in the nature of the shock waves in supersonic flow under atmospheric pressure and pressure conditions at the boundary of continuum mechanics for electron microscopy. The first part describes the verification of the CFD analyses in combination with the experimental chamber results and the initial analyses using optical methods at low pressures on the boundary of continuum mechanics that were performed. The second part describes the analyses on an underexpanded nozzle performed to analyze the characteristics of normal shock waves in a pressure range from atmospheric pressure to pressures at the boundary of continuum mechanics. The results obtained by CFD modeling are prepared as a basis for the design of the planned experimental sensing of density gradients using optical methods, and for validation, the expected pressure and temperature courses from selected locations suitable for the placement of temperature and pressure sensors are prepared from the CFD analyses.