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BATMAX project overview

Battery management by multi-domain digital twin

Physics and data-based battery management by multi-domain digital twins (BATMAX) sets out to pave the way for advanced next-generation data-based and adaptable battery management systems capable of fulfilling the needs and requirements of various mobile and stationary applications and use cases.

The transportation sector is responsible for roughly one-quarter of the total greenhouse emissions in the EU, with road vehicles contributing to over 60% of the emissions. The European Green Deal sets forth ambitious climate change mitigation goals, with all 27 EU Member States dedicated to transforming the EU into the world's first carbon-neutral continent by 2050. They have committed to reducing emissions by a minimum of 55% by 2030 compared to 1990 levels, with the aim of achieving a fossil-free society by 2050. The development of more efficient and reliable battery systems is crucial in achieving these objectives.

BATMAX project main objective is to optimize the performance of the battery system by improving its safety, reliability, service life and lifetime cost. For the fulfillment of the main objective BATMAX partners are building a framework (hardware and software) for next generation of battery management by adopting emerging technologies for a holistic data management. Advanced Battery Management System (BMS) algorithms coupled to real-time multiscale digital twins will combine data from simulation, laboratory and operational sources to provide next-generation battery management.

RISE will conduct safety critical and light abuse testing of large pouch cells, identify safety limitis and State-of-safety (SoS) of the cells based on the light abuse tests and perform safety critical modelling and simulations on pressure effects. 

Objectives

  • Develop a system for effectively parameterizing physics-based models.
  • Develop hardware that utilizes advanced sensors to enhance connectivity and data sharing to support the battery BMS.
  • Develop hybrid (data and physics-based models) and AI-driven models to optimize battery lifetime and improve battery management BMS.
  • Integrate the BMS with a multi-scale battery digital twin framework to enable a dynamic operation.
Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Climate, Infrastructure and Environment Executive Agency. Neither the European Union nor the granting authority can be held responsible for them. Grant Agreement: 101104013
Ellen Scott
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