Active Battery Diagnostics

This result has been achieved by partners TNO, EDF and VUB. The result has been achieved on 31st October 2024 in month 47 of the project.

Introduction

On the 1st and 31st of October the active battery diagnostic system, also called the CheckUp Tool, was demonstrated at the iSTORMY demonstration site (EDF concept grid). On both dates a diagnostic cycle was performed to measure battery capacity and internal resistance of the stationary energy storage system. The diagnostic system shows potential for improved asset management and optimized battery lifetime.

Objective

The goal of the performed tests is to demonstrate that the active battery diagnostic system can consistently and accurately measure the battery health of the energy storage system.

Research

Battery health is measured by applying a diagnostic protocol, i.e. a series of current setpoints, to the battery through the charger. By controlling the charger with software and collecting measurements from the battery, the capacity and internal resistance of the battery can be calculated. By doing this periodically, the degradation of battery health can be monitored.

Results

The tests on the 1st and 31st of October were successful and the battery capacity and internal resistance of the energy storage system were measured. The demonstration proved the concept of consistent and accurate battery health measurement through the charger. By applying an identical diagnostic protocol twice, the results of both test could be directly compared.

  • What will it be used for: Given this integration, the system will be tested on 3 different use cases, corresponding respectively to the provision of:
    The results of the tests will feed into a scientific publication discussing the advantages and challenges of actively diagnosing battery health for real world applications. In the long term, repeated diagnostic cycles over time will provide high quality battery degradation data. This data can be used to train machine learning algorithms and to optimize the operation of the energy storage system.
  • Impact: The data generated by the system can be used to optimize system operation and inform owners about the status of their asset. Through optimization, battery lifetime can be extended and costs can be saved.