Research & Innovation

Through the use of a BMS – in our case, an active BMS – cells are balanced by transferring energy from those with a higher charge level to those with a lower state of charge (SoC). This means that energy is redistributed within the battery rather than wasted. Based on data collected during previous research activities, a software prototype was developed to collect and analyse data and estimate key battery parameters, including state of charge (SoC) and state of health (SoH).

The project involves the use of Artificial Intelligence and Machine Learning (ML). One of its key elements is integrating the BMS with software capable of using Machine Learning to interpret real-world data and develop a control system that can identify potential issues. Advanced networks connected via the cloud to a database have also been designed to collect the information needed to continue training the software. The use of batteries as propulsion systems in the automotive industry is still a relatively young field, characterised by a variety of solutions and continuous development. Collecting data such as SoC, temperatures and the number of charge and discharge cycles can provide the software with the information required to continue learning and ensure that the BMS is kept updated over time.

The contribution of CIM

As part of the BMS project, STAR7 partnered with Competence Industry Manufacturing 4.0 (CIM) to identify the most suitable Machine Learning algorithms and receive support in designing a remote data repository.

The need to develop a project on the circular economy for electric vehicle batteries arose naturally from STAR7’s experience in providing services to support manufacturing in the sector.

The circular economy project aims to maximise resource efficiency, reduce waste and minimise the environmental impact of batteries used across different sectors, including automotive, electronics and energy.

The proposed innovation addresses the traceability of components that can be repaired, reconditioned, reused or recycled. The solution includes a manual for the complete disassembly of the battery, with a particular focus on safety, as well as a procedure for analysing and characterising battery modules that cannot be repaired. The modules will undergo a series of laboratory tests to assess their suitability for new applications in both the automotive and civil sectors.

The Circular Economy project aims to extend the life cycle of modules certified for long-term use by repurposing the modules or individual cells for less demanding applications. Rare elements are recovered only after the components have undergone repair, reuse and recycling processes. Looking ahead, advances in recovery technologies –currently still expensive – could become more efficient and contribute to the development of a fully circular system, reducing the natural-resource waste.

The contribution of CIM

As part of the Circular Economy project, STAR7 partnered with Competence Industry Manufacturing 4.0 (CIM) to develop a cloud-connected traceability system and define guidelines for analysing an effective business model for the research project.

STAR7 and CIM also organised a workshop to encourage discussion with industry leaders interested in the project’s area of application.