Battery Aging represents a major challenge for the design and operation of battery energy storage systems. Models to describe the degradation depending on factors like state of charge, temperature and charge-discharge cycles do exist. To parameterize these models, time-consuming and cost-intensive experiments are necessary so far. In the BaPoBs (Battery aging and Pareto-optimal operating strategy) project, methods for an efficient and effective characterization of the aging of battery-electric storage devices are developed. Therefore, several aging studies are conducted using a commercially available Li-ion battery cell in order to find and calibrate a model. The first iteration of experiments is planned on as little pre-knowledge as possible, assuming the tested battery is an unknown, complex system. The aging is assumed to consist of independent calendar and cyclical inﬂuences. Check-ups (CU) are carried out at regular intervals, during which the change of the capacity (Qloss) and the inner resistance (Rinc) are monitored. Every combination of inﬂuence factors is repeated three times.
For calendar aging, the factors temperature (T), state of charge (SoC) and time (t) are examined. In addition to the three cells with which regular check-ups are performed, only the initial and ﬁnal CU is performed for three additional cells per TP. This is to determine the inﬂuence of the CUs itself on the aging of the cells. The design space for the cycle aging study includes temperature (T), state of charge (SoCmax), depth of discharge (DoD), charge and discharge current (Cch , Cdisch) and full equivalent cycles (FEC).
The design of experiments as well as the test procedures for the first calendar aging and cycle aging study are shown in this poster. Later on, another set of experiments will be based on optimized, model-based experimental design.