Electric vehicles (EVs) powered by lithium-ion batteries are crucial for sustainable transportation. Accurate State of Charge (SOC) estimation, a core function of Battery Management Systems (BMS), enhances battery performance, lifespan, and safety. This paper proposes a hybrid CNN-LSTM-AKF model integrating Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) Neural Networks with an Adaptive Kalman Filter. CNN extracts spatial features from current, voltage, and temperature data, while LSTM processes temporal dependencies. AKF reduces output fluctuations. Trained on datasets under three operating conditions, the model was tested across various temperatures and initial SOC states. Results demonstrate that the proposed model significantly outperforms standalone LSTM and LSTM-AKF model, particularly at low temperatures. Within 0 °C to 50 °C, it achieves Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) below 1.51% and 1.18%, respectively. With an initial SOC of 80%, the model achieves an RMSE of 1.09% and MAE of 0.88%, showing rapid convergence. The model exhibits high accuracy, strong adaptability, and robust performance.

This study presents a numerical investigation into the hydrodynamic and biomechanical performance of bone-repair scaffolds based on Triply Periodic Minimal Surfaces (TPMSs). Focusing on Gyroid and Diamond architectures, scaffolds with uniform (40–70%) and functionally graded porosities were developed. Computational Fluid Dynamics (CFD) simulations were employed to evaluate permeability, pressure drop, and Wall Shear Stress (WSS) distributions. Results indicate distinct topological advantages: the Gyroid structure demonstrates superior permeability and uniform WSS distribution due to its isotropic fluid channels, whereas the Diamond structure maintains better flow velocity stability. Crucially, the introduction of a porosity gradient (40–60%) successfully mitigates localized pressure surges and optimizes the bioactive WSS window for cell differentiation. Notably, increasing porosity to 70% in Gyroid scaffolds yielded a 277% enhancement in permeability. These findings establish a theoretical basis for designing functionally graded TPMS scaffolds that balance fluid transport efficiency with a favorable cellular microenvironment.