Mass transport conversion to an electrified powertrain requires suitable strategies for processing electric vehicle (EV) batteries after their intended first service life. Due to aging mechanisms, EV batteries lose capacity over their period of use and become unsuitable for their initial application at some point. However, to expand their lifetime and to meet the sustainability demand for EVs, the usage of these batteries in so-called Re-X applications is under intense discussion. Until now, downstream processing has been subject to high uncertainty regarding the expected advances. While many issues on the technical and ecological side have been at least partially resolved, the economics are still under assessment. For this reason, this paper intends to give a well-based outlook on the costs and benefits of three chosen scenarios: reuse, repurpose, and recycle. It is expected that under the given national policies and global market conditions, growing quantities of retired EV batteries will return from the transportation markets. Consequently, the market potential for retired batteries in downstream applications will significantly increase, as well as calls for stable solutions.

Understanding the degradation behavior of lithium-ion batteries under realistic application conditions is critical for the design and operation of Battery Energy Storage Systems (BESS). This research presents a modular, cell-level simulation framework that integrates electrical, thermal, and aging models to evaluate system performance in representative utility and residential scenarios. The framework is implemented using Python and allows time-series simulations to be performed under different state of charge (SOC), depth of discharge (DOD), C-rate, and ambient temperature conditions. Simulation results reveal that high-SOC windows, deep cycling, and elevated temperatures significantly accelerate capacity fade, with distinct aging behavior observed between residential and utility profiles. In particular, frequency modulation and deep-cycle self-consumption use cases impose more severe aging stress compared to microgrid or medium-cycle conditions. The study provides interpretable degradation metrics and visualizations, enabling targeted aging analysis under different load conditions. The results highlight the importance of thermal effects and cell-level stress variability, offering insights for lifetime-aware BESS control strategies. This framework serves as a practical tool to support the aging-resilient design and operation of grid-connected storage systems.

Lithium-ion battery systems are a core component for electric mobility, which has become increasingly important in the last decade. The rising number of new manufacturers and model variants also increases competitive pressure. Competition is shortening development times. At the same time, the range of technology options for batteries is growing steadily. Fast and well-founded concept development is becoming even more essential in this increasingly complex environment. For this purpose, various model-based systems engineering (MBSE) methods are analyzed and evaluated. Based on this, the battery modeling framework is derived and described, tailored to the needs of battery development. The validation of the methodological approach is demonstrated by the simulation workflow from an electrical cell characterization to the thermal evaluation of different cooling methods.

Das thermische Durchgehen („Thermal Runaway“) von Batterien stellt eine zentrale Sicherheitsproblematik dar, da die Zellen durch unkontrolliertes Erhitzen in Brand geraten und explodieren können. Neben konventionellen Lithium-Ionen-Batterien rücken auch Natrium-Ionen-Batterien in den Fokus der Industrie, wobei es bis dato nur wenige Analysen zu deren Sicherheitsverhalten gibt. Ziel dieser Veröffentlichung ist die Charakterisierung der Sicherheit von Natrium-Ionen-Batterien unter externer Wärmezufuhr bei einem Ladezustand von 50 %.