Battery Storage - Condition Monitoring and Sustainable Operation
The research focus is on the sustainable and resource-efficient use of battery storage systems throughout their entire life cycle. With the help of targeted laboratory aging, automated condition monitoring, and hybrid digital twins, the aging, performance, and remaining service life of battery storage systems can be reliably recorded and predicted. The findings form the basis for condition-based operating and service concepts that extend service life, increase safety, and minimize resource consumption. This allows maintenance measures to be carried out in a targeted, cost-efficient, and proactive manner. The aim is to ensure that battery storage systems can be operated reliably and in a resource-efficient manner over the long term without compromising operational safety.
A central aspect of the research is the artificial aging of battery storage systems under controlled laboratory conditions. Reproducible stress profiles can be used to specifically investigate various degradation mechanisms. At the same time, automated methods for condition monitoring are being developed. These enable the continuous recording of relevant electrical, thermal, and, if necessary, chemical state variables.
The hybrid models of battery storage systems that have been developed combine physics-based modeling approaches with data-driven methods. As digital twins, they map the current and future state of a battery system and are used both to interpret measured data and to predict aging, performance, and remaining service life.
Another focus is on the development of methods and technologies for offline condition assessment, for example in the context of maintenance, testing, or second-life evaluation. In addition, online methods for continuous condition assessment are being researched that can be used during ongoing operation and enable early fault and degradation detection.
The research work is accompanied by extensive tests and laboratory investigations on new and used battery storage systems. In particular, the condition analysis of used battery storage systems forms the basis for well-founded recommendations for service, reuse, or recycling.
- Stationary energy storage (e.g., grid stabilization, PV and wind farms, neighborhood storage)
- Electromobility (batteries in electric vehicles, buses, commercial vehicles)
- Second-life applications for used vehicle batteries (e.g., stationary storage)
- Battery maintenance and service (condition diagnosis, service life prognosis, predictive maintenance)
- Industrial and production facilities with battery-supported energy supply
- Emergency power and safety power systems (data centers, hospitals)
- Research, development, and quality assurance of battery systems
- Many years of experience in the diagnosis and service life prediction of operating equipment
- Development and application of condition monitoring methods
- Aging and degradation analysis of operating equipment
- Model-based and data-driven prediction methods
- Development and use of digital twins for condition and service life assessment
- Laboratory and field tests for reproducible aging and validation of models
- Derivation of condition-based operation and maintenance strategies
Battery Lifecycle Center at the OIC
Research Projects
