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hILDe: AI-Empowered Monitoring System for Vanadium Redox Flow Batteries

Gian-Luca Kiefer; Alassane Ndiaye; Matthieu Deru; Boris Brandherm; Laura Gerart; Stephan Schulte; Bodo Groß; Dan Durneata; Rolf Hempelmann
In: Constantine Stephanidis; Margherita Antona; Stavroula Ntoa; Gavriel Salvendy (Hrsg.). HCI International 2023 Posters. Communications in Computer and Information Science (MODELSWARD-2023), February 19-21, Lisbon, Portugal, Pages 490-496, Vol. 1835, ISBN 978-3-031-36001-5, Springer Nature Switzerland, Cham, 7/2023.


The dynamic production of green energy requires capable mediate storage solutions, often in the form of large batteries. Here, a Vanadium Redox Flow Battery is used to collect solar panels’ energy and, later, power electric vehicles. Since the balance of the chemical liquids inside the battery can change over multiple loading cycles, a system for predictive monitoring is needed. This paper presents the project “hILDe - Novel, cost-effective and highly accurate indication of imbalance and state of charge of vanadium redox flow batteries using AI-assisted detection of specific colors”, which features an absorbance sensor for chemical liquids and an AI-empowered monitoring system to interpret and predict sensory data. The current progress in our lab scenario suggests that the deployment of our sensor and monitoring system enables an accurate and cost-efficient imbalance and state of charge sensor for Vanadium Redox Flow Batteries. In the future, the system will be tested in full-sized batteries to verify its scalability and commercial potential.

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