Our ambitious challenge

NEMO aims to advance novel and established modelling techniques based on electrochemical impedance spectroscopy (EIS) to their application.


Raising the bar for batteries

Our objective is to considerably extend battery life and make the battery system safer within long-term operation of stationary and automotive use cases.

Among our technical improvements:

Complete avoidance of foreseeable critical safety issues not linked to severe mechanical impacts.

Extension of the first-life battery lifetime by at least 20% and capture of failure mode with 100% accuracy.

NEMO’s solutions are expected to be validated by industrial partners and to take a considerable share of the market in the future.


Reshaping the
battery sector

Our solutions will position the European BMS industry at the forefront of digital battery management innovations and allow them to take a maximum share of the BMS market estimated to €3.5 bn by 2026. These performance improvements will further increase social acceptance and uptake of the electrification of the European energy system.

NEMO especially contributes to:

Accelerate roll out of electrified mobility through increased attractiveness regarding improvements of e-vehicles operation.

Improved Life Cycle Assessment of the final product segment of the battery value chain and accelerated roll-out of circular designs though innovations that allow for a straight-forward second life usage with economic guarantees.

Increased exploitation and reliability of batteries through demonstration of innovative use cases of battery integration in stationary energy storage and e-vehicles.


A whole new class of
models and algorithms

We aim to leverage in-situ and in-operando EIS sensing, along with active cell switching for balancing at cell-level and sufficient computing power, to execute real-time models and algorithms.

Towards achieving these goals, the consortium tends to provide efficient software and hardware to handle, host, process, and execute these approaches within high-end local processors and cloud computing.

The availability of such diverse physical information on batteries onboard makes room for developing cutting-edge performance, lifetime, and safety battery models and state estimators within NEMO, and validating them on two different BMS configurations.

Physics-based performance model parameters continuously get updated as the battery ages, so that performance and safety state indicators maintain the least possible error. The data-driven approaches exploit mathematical algorithms to be trained upon the large datasets made available from historical or laboratory generated battery information.

Combinations of coupled physics-based and data-driven approaches are also foreseen to be implemented within NEMO as another innovation of the project to propose next-generation BMS.


Meet The Partners

NEMO Consortium is led by VUB and brings together highly experienced and specialized institutions, organizations and companies that conduct cutting-edge research.


Our Advisory Board

The NEMO’s Advisory Board (AB) helps us boost the technical and impact aspects of the project by providing an external expert view.

image about ENERGETIC


ENERGETIC project, funded by the EU Horizon Europe program, aims at developing the next generation BMS for optimising batteries’ systems utilisation in the first (transport) and the second life (stationary) in a path towards more reliable, powerful, and safer operations. It contributes to the field of translational enhanced sensing technologies, exploiting multiple AI models, supported by Edge and Cloud computing. ENERGETIC will monitor and predict the remaining useful life of a Li-ion battery through a digital twin.
image about NETXBMS


NEXTBMS will develop an advanced battery management systems (BMS) built on fundamental knowledge and experience with the physicochemical processes of lithium-ion batteries, which will enable the significant enhancement of current modelling approaches, including the readiness for upcoming lithium (Li) battery material developments. These modelling approaches will be further improved by optimising sensors and measurement techniques to meet modelling needs (and optimising models based on physical sensor data) and the physical cell configurations to form a framework that supports improving the battery state prediction and -control. By solving these challenges, NEXTBMS will ensure that the next generation of BMSs will enable higher performance, safety, and longer lifetime of the battery cells for an overall optimal utilisation of the battery system.
image about BATMAX


BATMAX project aims 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 main objective of the project is to contribute to improving battery system performance, safety, reliability, service life, lifetime cost and therefore to maximise the value created by operation of the battery systems in various kinds of end use applications. BATMAX develops a framework to efficiently parameterise physics-based models as well as the hardware and sensorisation on cell and system level for collection and communication of battery measurement data. The BATMAX BMS framework will enable to exploit advanced battery models with integrated digital twin framework that is capable to cope with high amount of measured data, which will enable to monitor the battery aging in depth and to facilitate the key functions of systems. A central output is an extensive multi purpose and scalable digital twin framework is developed and validated for advanced battery management.
The BMS Alliance

Cluster projects

Our Cluster aims to facilitate exchange among the four projects of HORIZON-CL5-2022-D2-01-09, focusing on physics and data-based battery management for optimized battery utilization. The objective is to share experiences and generate a larger impact.