In this paper, software algorithms for condition monitoring of a battery management system (BMS) are developed. The given application is a 400 V high-voltage (HV) battery-pack for automotive use. Generally, the BMS is responsible for a safe and optimized operation of the HV-battery-pack. Therefore, a Matlab/Simulink model for an HV-battery-pack is designed and the common WLTP-load profile computed. For the BMS a state-of-the-art Coulomb-Counter for battery State-of-Charge estimation is implemented. Furthermore, a three-criteria current limitation is realized to perform high quality power prediction. The battery aging-state based on the internal resistance $SO{H}_R$\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$SOH_{R}$$\end{document} is estimated through an internal resistance estimation using several methods. Notably, the internal resistance estimation during a dynamic driving cycle leads to promising results. During a WLTP driving cycle the RT2s-method is able to estimate the internal resistance with a $3\sigma$\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$3\sigma $$\end{document}-accuracy of less than $0,07m\Omega$\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$0{,}07\,m\Omega$$\end{document}. The RT2s-method combined with an adaptive lowpass filter shows a high level of accuracy, stability and robustness. The implemented algorithm detects the $SO{H}_R$\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$SOH_{R}$$\end{document} at different settings with a maximum error of $\Delta SO{H}_R<$\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Delta SOH_{R} <$$\end{document} 8 %.