NEMO - NExt-generation MOdels for advanced battery electronics

NEMO - NExt-generation MOdels for advanced battery electronics  

NEMO advances next-generation Battery Management Systems (BMS) for electric vehicles and stationary storage. The project aims to make lithium-ion batteries longer-lasting, safer and more efficient by improving sensing, modelling, data handling and battery-state estimation.
The project develops and validates new battery electronics and advanced models that combine physics-based and data-driven approaches. A key technology direction is the use of in-situ and in-operando electrochemical impedance spectroscopy (EIS) together with real-time and historical battery data to better identify electrochemical processes inside battery cells and track them over time.
NEMO targets advanced State of X (SoX) information such as State of Charge, State of Health and State of Safety. The resulting knowledge supports battery lifetime extension, early detection of safety-relevant behaviour, improved charging and discharging strategies and more reliable second-life usage of battery systems.

Key objectives

• Advance the state of the art in Battery Management Systems using improved sensing, modelling and computing resources.
• Improve the estimation of battery states and degradation by combining physics-based and data-driven models.
• Support safer operation through better monitoring of State of Safety and battery failure indicators.
• Extend first-life battery lifetime and improve the utilisation of batteries in e-vehicles and stationary energy storage.
• Provide FAIR/open research data and cloud-based data access for the battery modelling community while maintaining a robust data pipeline.

Use cases / business relevance

• Electric vehicles: NEMO supports more attractive electrified mobility by improving battery operation, state estimation and safety-relevant battery functions.
• Stationary energy storage: The project is relevant for battery integration in stationary storage by improving reliability, utilisation and monitoring.
• Second-life and circular designs: Improved battery diagnostics and lifetime modelling support more reliable decisions on second-life use and circular battery concepts.