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AI Project: PEM Aims to Increase Battery Production Efficiency

Battery Production efficiency ai

AI Project: PEM Aims to Increase Battery Production Efficiency

With several partners from research and industry, the Chair of Production Engineering of E-Mobility Components (PEM) of RWTH Aachen University has begun the three-year TRAICELL project. Funded by the German Federal Ministry of Education and Research, the project focuses on the traceability of crucial data as well as on artificial intelligence to optimize battery cell production.

Three predefined core areas

PEM Director Professor Achim Kampker, says:

Innovative solutions – including those from digitalized battery cell production – must be transferred from research to industry more quickly,

“In future, it will be important to be able to make reliable quality predictions during the forming process in order to reduce production times and detect rejects at an early stage.” In terms of significantly more sustainable battery production, the project focuses on three core areas a panel of experts from research and industry had previously assessed as promising approaches. In this way, three near-series prototypes are to be created along three scaling stages of battery production.

Earliest possible quality predictions

On the one hand, a system is to be developed that enables production and quality data to be tracked down to individual electrode layers. In addition, the aim is to increase efficiency and quality by simultaneously optimizing the mixing and coating processes. At the end of the project, machine learning models will make it possible to predict cell quality in early production phases in order to minimize waste and improve material yield.

The transfer of data-based solutions to industry will strengthen domestic mechanical and plant engineering and help to make European battery cell production more efficient and sustainable as quickly as possible.

TRAICELL also involves the Fraunhofer Research Institution for Battery Cell Production FFB, German electrode and cell manufacturer UniverCell, BST as a full-service provider of quality assurance systems, and AI developer Merantix Momentum. Together, the consortium will develop and test the intended innovations on various scales – from pilot to near-series production.

PEM Management Member Professor Heiner Heimes, says:

The transfer of these data-based solutions to industry will strengthen domestic mechanical and plant engineering and help to make European battery cell production more efficient and sustainable as quickly as possible,

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