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TWAICE predictive analytics and digital twin ecosystem to optimise and automate batteries second life and re-use

Project description

Improved insights for development, operation and second life of batteries

To achieve the EU’s ambitious emission- and carbon-reduction goals, the adoption of efficient and sustainable solutions is necessary, and innovation is required. The battery industry is considered a key enabler of a low-carbon economy. In this context, the EIC-funded Predictive Battery Analytics project aims to align the battery industry with these green goals. To do so, it will offer currently lacking but crucial transparency throughout the development, production and reuse phases of lithium-ion batteries with the use of a novel software based on digital twin technology, AI and battery knowledge. Project results will lead to significantly reduced CO2 emissions.

Objective

Our solution solves the major cost and safety problems posed by batteries. TWAICE’s predictive battery analytics platform can be implemented at all stages of the battery value chain, optimizing processes such as development, operation and re-use (second life). There is a substantial lack of transparency in Li-ion batteries, a problem which can lead to overly high development and operation costs and pose safety risks. Our software addresses this problem by empowering customers to better understand their batteries. They can obtain precise diagnoses and prognoses on battery health and remaining lifetimes, using this information to inform their strategic operational decisions. Underpinned by digital twin technology, we combine battery knowledge with artificial intelligence and machine learning to solve the specific customer needs mainly in the energy and mobility sector. Wherever it is applied, our solution will make significant contributions to reducing CO2 and ensuring a greener future.

Coordinator

TWAICE TECHNOLOGIES GMBH
Net EU contribution
€ 2 163 875,00
Address
JOSEPH-DOLLINGER-BOGEN 26
80807 MUNCHEN
Germany

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SME

The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.

Yes
Region
Bayern Oberbayern München, Kreisfreie Stadt
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Links
Total cost
€ 3 091 250,00