€11m for Munich battery digital twin startup

March 26, 2020 //By Nick Flaherty
€11m for battery digital twin startup
Twaice, a spinout of the Technical University of Munich building technology for a digital twin of a battery system, has raised €11m in its Series A round

Munich-based battery analytics software company Twaice has raised €11m in its Series A round of funding to boost the development of digital twin technology.

Twaice develops software to create a detailed model, or digital twin, of a battery system. Combining the model with field data allows precise analysis and prediction of the state of health of each energy storage device. The software also opens up applications such as predictive maintenance and warranty extension. Operational failures can be detected — and prevented — in real time.

The round was led by venture capital firm Creandum. Cherry Ventures, UVC Partners and Speedinvest already invested €3.2m as part of an earlier seed round.

“We are very happy to have Creandum, an internationally recognized investor, onboard now,” said Michael Baumann, Managing Director and Co-Founder of Twaice. “They share our vision of an analytics platform for e-mobility and renewable energies.”

The company was founded in 2018 after four years of research at the Technical University of Munich into combining in-depth battery knowledge, a scalable cloud platform and machine learning. It has a focus on both electric vehicle battery packs and stationary energy storage systems that are used alongside solar panels and wind turbines.

These stationary storage units are used to avoid increased grid fees or to stabilize the grid. However, due to their cost and complexity, the battery systems are especially challenging regarding significant test scopes during development, a lack of transparency about their condition, and remaining lifetime during operation.

For vehicle battery packs, the software provides more precise information about the processes taking place in the batteries during use. This allows operators of electric vehicle fleets, for example, to reduce their operating costs through predictive maintenance and achieve an increase in battery life of up to 25 percent.


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