soc-estimation

Battery state of charge estimation using kalman filter in Matlab

Neural ODE-based State of Charge (SOC) estimation for Li-ion batteries using the NASA Battery Dataset. Built as a weekend project to explore learned dynamics for battery modeling, with visualizations designed for engineering audiences.

Sandbox to develop, test and compare neural network-enabled estimation techniques for state of charge of a sample lithium-ion battery using deep learning methodologies, utilizing transient signals to predict state across points in time.

MATLAB/Simulink simulation of a 4S Li-ion BMS with SOC estimation, protection logic and cell balancing

Battery SOC estimation using equivalent circuit models, EKF, embedded-oriented implementation, and C firmware-style code

MATLAB implementation of VBMCCKF for Li-ion battery SOC estimation.

Machine learning-based battery State of Charge estimation using charge–discharge data, Coulomb counting, and Random Forest regression in Python.

Prior-based patch-level representation learning for electric vehicle battery state-of-charge estimation across a wide temperature scope

MATLAB/Simulink battery SOC estimation project comparing Coulomb Counting, EKF, and UKF using a 1-RC lithium-ion battery model.

Battery Management System (BMS) State of Charge (SoC) estimator for Lithium-Ion batteries using an Extended Kalman Filter (EKF). Features a realistic simulation environment with sensor fusion, noise compensation, and voltage relaxation dynamics modeling.

Simulation and Data Science Project: Model-based State-of-Charge estimation with a Kalman filter (MATLAB/Simulink) and data-driven Remaining-Useful-Life prediction using a Long Short-Term Memory Recurrent Neural Network (PyTorch).

State of Charge (SoC) estimation algorithms and battery modeling tools for Lithium-ion Battery Management Systems (BMS)

MATLAB/Simulink model of a Series Hybrid Electric Vehicle (SHEV) with rule-based energy management, battery SOC estimation, fuel consumption and emission analysis.

Interactive Battery State of Charge (SoC) Estimator built with Python, Streamlit, Plotly, Pandas, and NumPy.

Deep learning State-of-Charge estimation for EV lithium-ion batteries on the LG 18650HG2 benchmark (-20 to +40 C): six architectures compared under identical conditions, each trained across seeds.

Adaptive 2RC Thevenin EKF for LG INR18650 MJ1 with autonomous excitation gating and causal online Bayesian R0 adaptation in MATLAB/Simulink.

EV Battery Management System (BMS) with Discrete Extended Kalman Filter (EKF) SOC estimation in MATLAB/Simulink.

Self-calibrating Dual Extended Kalman Filter (DEKF) state-of-charge estimator for LFP home batteries — AppDaemon apps for Home Assistant