Search Results (4)

In this paper, we consider a subclass of normalized analytic functions associated with the hyperbolic secant function. We compute the sharp bounds on third- and fourth-order Hermitian–Toeplitz determinants for functions in this class. Moreover, we determine the bounds on second- and third-order Hankel determinants, as well as on the generalized Zalcman conjecture. We examine a Briot–Bouquet-type differential subordination involving the Bernardi integral operator. Finally, we obtain a univalent solution to the Briot–Bouquet differential equation, and discuss the majorization property for such function classes. Full article

With the increasingly widespread application of large-scale energy storage battery systems, the demand for battery safety is rising. Research on how to detect battery anomalies early and reduce the occurrence of thermal runaway (TR) accidents has become particularly important. Existing research on battery TR warning algorithms can be mainly divided into two categories: model-driven and data-driven methods. However, the common model-driven methods are often of high complexity, with poor versatility and low early warning capability; and the common data-driven methods are mostly based on neural networks, requiring substantial training costs, with better early warning capabilities but higher false alarm probabilities. To address the limitations of existing works, this paper proposes a combined data-driven and model-based algorithm for accurate battery TR warnings. Specifically, the K-Means algorithm serves as the data-driven module, capturing outliers in battery data, and the Bernardi equation serves as the model-driven module used to evaluate battery temperature. Ultimately, the outputs of the weighted model-driven module and data-driven module are combined to comprehensively assess whether the battery is abnormal. The proposed algorithm combines the advantages of model-driven and data-driven approaches, achieving a 25 min advance warning for thermal runaway, with a significantly reduced probability of false alarms. Full article

This study investigates the influence of the considered Electric Equivalent Circuit Model (ECM) parameter dependencies and architectures on the predicted heat generation rate by using the Bernardi equation. For this purpose, the whole workflow, from the cell characterization tests to the cell parameter identification and finally validation studies, is examined on a cylindrical 5 Ah LG217000 Lithium-Ion-Battery (LIB) with a nickel manganese cobalt chemistry. Additionally, different test procedures are compared with respect to their result quality. For the parameter identification, a Matlab tool is developed enabling the user to generate all necessary ECMs in one run. The accuracy of the developed ECMs is evaluated by comparing voltage prediction of the experimental and simulation results for the highly dynamic World harmonized Light vehicle Test Cycle (WLTC) at different states of charges (SOCs) and ambient temperatures. The results show that parameter dependencies such as hysteresis and current are neglectable, if only the voltage results are compared. Considering the heat generation prediction, however, the neglection can result in mispredictions of up to 9% (current) or 22% (hysteresis) and hence should not be neglected. Concluding the voltage and heat generation results, this study recommends using a Dual Polarization (DP) or Thevenin ECM considering all parameter dependencies except for the charge/discharge current dependency for thermal modeling of LIBs. Full article

The Marchaud fractional derivative can be obtained as a Dirichlet-to–Neumann map via an extension problem to the upper half space. In this paper we prove interior Schauder regularity estimates for a degenerate elliptic equation with mixed Dirichlet–Neumann boundary conditions. The degenerate elliptic equation arises from the Bernardis–Reyes–Stinga–Torrea extension of the Dirichlet problem for the Marchaud fractional derivative. Full article