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Accurate estimation of the state of charge (SoC) of lithium-ion batteries is crucial for battery management systems, particularly in electric vehicle (EV) applications where real-time monitoring ensures safe and robust operation. This study introduces three advanced algorithms to estimate the SoC: deep neural network (DNN), gated recurrent unit (GRU), and long short-term memory (LSTM). The DNN, GRU, and LSTM models are trained and validated using laboratory data from a lithium-ion 18650 battery and simulation data from Matlab/Simulink for a LiCoO2 battery cell. These models are designed to account for varying temperatures during charge/discharge cycles and the effects of battery aging due to cycling. This paper is the first to estimate the SoC by a deep neural network using a variable current profile that provides the SoC curve during both the charge and discharge phases. The DNN model is implemented in Matlab/Simulink, featuring customizable activation functions, multiple hidden layers, and a variable number of neurons per layer, thus providing flexibility and robustness in the SoC estimation. This approach uniquely integrates temperature and aging effects into the input features, setting it apart from existing methodologies that typically focus only on voltage, current, and temperature. The performance of the DNN model is benchmarked against the GRU and LSTM models, demonstrating superior accuracy with a maximum error of less than 2.5%. This study highlights the effectiveness of the DNN algorithm in providing a reliable SoC estimation under diverse operating conditions, showcasing its potential for enhancing battery management in EV applications. [ABSTRACT FROM AUTHOR]

Structural, magnetic, electronic, elastic, thermodynamic, optical, and thermoelectric properties of full-Heusler alloys Co2YSn (Y = Ti; Zr; Hf) were determined using density functional theory-based WIEN2k code within GGA and GGA + U approximations for exchange correlation functions. The calculated formation energies and elastic parameters demonstrate the stability of these alloys. It was also observed that the studied compounds have a ductile structure and exhibit anisotropic behavior. The magnetic moment of these systems is equal to 2 μB, which conforms to the Slater–Pauling rule. In addition, the half-metallic ferrimagnetic behavior and good bandgap in the minority spin are showed for all compounds. The optical properties are systematically studied by computing the optical parameters. The existence of bandgaps with minimal energy loss in IR and visible regions makes these materials suitable candidates for optoelectronic devices. The thermoelectric properties of these systems were also examined in terms of temperature and chemical potential. [ABSTRACT FROM AUTHOR]

The main objective of this study is to explore the nonlinear dynamics and chaos detecting in the three-dimensional (3D) generalized Hamiltonian Yang–Mills system as coupled quartic oscillators. We investigate its Liouvillian integrability. The integrable system is obtained and its associated first integral of motion is explicitly given. Also, a variety of nonlinear phenomena could be expressed using various numerical analysis, such as the construction of the system's Poincaré Surface of Section (PSS), the maximum Lyapunov exponent (mLE), and the modern numerical methods like the Smaller (SALI) and the Generalized (GALI) Alignment Indexes. In this context, a series of numerical simulations are appropriate in order to explore ordered and chaotic motions of the system both in two (2D) and three dimensions, and one can observe chaos–order–chaos transition of the system when any parameters on which the system depends vary. Finally, several numerical schemes are shown to demonstrate the effectiveness and rapidity of these proposed methods for distinguishing chaos and order states of the system. [ABSTRACT FROM AUTHOR]

• We study the integrability of three-dimensional Armbruster Guckenheimer Kim potential. • We determine three integrable cases by using the Painlevé analysis. • We build the integrals of motion for all cases obtained. • Numerical investigations are performed to observe the chaos-order-chaos phenomenon of each case. The three-dimensional (3D) Armbruster Guckenheimer Kim galactic potential in the general form is considered. The integrability of this problem is performed by using the Painlevé analysis. We report three cases of integrability, and the exact integrals of motion are obtained explicitly for each case. Several numerical simulations were performed in order to investigate the classical phase space and explore chaos-order-chaos transition. Also, the maximum Lyapunov exponent (mLE) and the smaller alignment index (SALI) methods are used to distinguish rapidly and with certainty between ordered and chaotic motion. [ABSTRACT FROM AUTHOR]