Lifetime analysis and prediction of lithium-ion batteries
Project completed - Contact: ftm(at)ftm.mw.tum.de
In this project at the Chair of Automotive Engineering at the TU Munich, hardware and software is being researched in order to be able to record and predict the condition of battery-powered products. Based on the algorithms developed, the state of health of a lithium-ion battery system is mapped and analysed in the form of a virtual twin in the cloud to enable service life forecasts and predictive maintenance, for example. Our mission is to help companies, through our hardware and software, to use the data gained through product digitisation in a way that adds value for you.
With our help, companies know the condition of their products at all times and can use their data for new value creation as well as quality-enhancing and cost-saving decisions.
