Upcoming Presentations

Master Thesis

 

Abstract

Accurate modeling of lithium-ion battery systems is a key prerequisite for developing high-performance battery management systems (BMS) in electric vehicles and stationary energy storage. This master’s thesis develops, parametrizes, and validates a real-time capable 3RC Thevenin model for a 12s2p lithium-ion battery module. The model is based on an electrical equivalent circuit with three RC branches representing electrochemical polarization processes on different time scales.

Parameter identification is performed using the least squares method based on stepwise discharge tests at four temperatures (0°C, 10°C, 25°C, 40°C) and a discharge rate of ⅓ C. The open-circuit voltage (OCV) and RC parameters are extracted from relaxation phases and stored in temperature- and SOC-dependent lookup tables. Validation demonstrates high model accuracy (RMSE = 30.7 mV, MRE = 0.04%) and confirms generalization capability through additional tests with ½ C discharge and a WLTP load profile (MRE = 0.11%, max. error = 0.49%).

By scaling the model to cell level, a 12-cell configuration is derived that accurately reproduces individual cell voltages (RMSE = 26.8 mV, MRE = 0.03%) and enables detection of faulty cells. The developed model thus provides an excellent balance between accuracy and computational efficiency and is well suited for model-based SOC estimation and the analysis of inhomogeneous battery systems.