VITO/EnergyVille offers tools such as BattSense and SmartCells that link up with energy management systems and ensure that the right control strategy is chosen at any time according to the final objective and the exact state of the storage unit.

VITO/EnergyVille is working on interfaces between storage units and the system they are part of. These interfaces are the hardware and software components of battery management systems that ensure efficient, flexible, safe and cost-effective integration of the storage units. These battery management systems are developed technology-independently in different topologies to provide the necessary flexibility according to the application.

Read more about battery storage

Get to know some of our tools

BattSense: The battery management system that makes sense

BattSense by VITO is the cost-efficient, modular, high performant BMS for all your mobile and stationary energy storage packs. The BattSense battery management system with dynamic cell balancing is designed to provide maximal safety, efficiency and an increased lifespan for cell-based electrical energy storage solutions.

Learn more about BattSense

SmartCells: The intelligent solution for our rechargeable future

Decentralisation is in, also in the way batteries are monitored and adjusted. At VITO/EnergyVille, we are working on an innovative battery management system based on 'distributed intelligence'. The smart battery cells could soon form the basis of a disruptive new value chain for European-made batteries.

Learn more about SmartCells
Contact:
Sofie Ignoul
Business Developer Storage
+32 14 33 51 25

News

Project News

Cooperation with the World Bank on sustainable development

Fri 27/09/2019
Project News

The neglected energy transition

Fri 27/09/2019

Publications

On Electrochemical Model-Based State Estimation for Lithium-Sulfur Batteries
Download Open Access Publication
Year: 
2023
Journal: 
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
Huang, ZJ; Couto, LD; Dangwal, C; Xiao, SJ; Lv, W; Zhang, D; Moura, SJ
An Efficient Methodology Combining K-Means Machine Learning and Electrochemical Modelling for the Determination of Ionic Diffusivity and Kinetic Properties in Battery Electrodes
Year: 
2023
Journal: 
MATERIALS
Capron, O; Couto, LD
Robust multivariable control design for HVDC systems considering AC grid impedance uncertainties
Year: 
2022
Journal: 
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
Tavakoli, SD; Prieto-Araujo, E; Fekriasl, S; Beerten, J; Mehrjerdi, H; Gomis-Bellmunt, O
Physics-based modeling of sodium-ion batteries part I: Experimental parameter determination
Year: 
2022
Journal: 
ELECTROCHIMICA ACTA
Chayambuka, K; Jiang, M; Mulder, G; Danilov, DL; Notten, PHL
Physics-based modeling of sodium-ion batteries part II. Model and validation
Year: 
2022
Journal: 
ELECTROCHIMICA ACTA
Chayambuka, K; Mulder, G; Danilov, DL; Notten, PHL

Pages

View all