3E, in collaboration with Vrije Universiteit Brussel (VUB) and leading industry partners, has delivered a validated digital twin technology for battery energy storage systems (BESS) as part of the EU-funded FULLEST project.
Now integrated into 3E’s SynaptiQ platform, the solution marks a major advancement in asset performance management for utility-scale energy storage.
The digital twin uses physics-based modelling to track battery degradation with high accuracy, outperforming conventional battery management systems. Built on PyBAMM and incorporating Single Particle Model (SPM) with solid electrolyte interphase (SEI) layer simulation, the system captures key aging mechanisms such as lithium loss and resistance growth. Validation tests using second-life Porsche Taycan cells showed less than 1% error in capacity prediction over one year of operation.
Real-time state estimation is achieved by processing PCS-level voltage, current and temperature data, normalised to cell level. The model delivers 10x speed improvements over full-order simulations, enabling one day of operation to be simulated in just 0.5 seconds.
The FULLEST consortium includes 3E, VUB, Sirris, Revolta and Eneco. Each partner contributed specialised expertise – from electrochemical modelling and machine learning to real-world validation and market integration. The system supports three key use cases: performance optimisation, anomaly detection, and predictive maintenance.
By modelling SEI growth and its impact on state of charge, operators can adjust charging strategies to balance throughput and degradation. Clustering algorithms enable early fault detection, while accurate aging models support proactive maintenance scheduling.
