Connected BMS: Virtual Fleet Data for Battery Life Management

Digital services and offerings that can extract insights from the large datasets that are generated by connected vehicle fleets. The Ricardo vision is for advanced monitoring and prognostics services to reduce electric vehicle battery failures in the field and extended battery life.

The key objective of this project is to develop a test platform for monitoring and prognostics of battery health. Such monitoring management is part of a connected Battery Management System (BMS). A secondary objective is to investigate novel hybrid physics-based/data-driven prognostics algorithms for battery health management. A tertiary objective is to derive BMS calibration updates from the physics based/data-drive prognostics algorithm, that can then be applied via Software-over-the-Air (SOTA).

There will be four focus areas in this project. Firstly, we will develop tools to virtually represent vehicle fleets. These virtual fleets will provide data to be ingested by the Connected BMS test platform. Secondly, we will address information flow from a CBMS to the test platform (Data-over-the-Air) Thirdly, we will focus on battery monitoring and prognostics algorithm development. Lastly, we will address information flow from the test platform back to the CBMS (Software-over-the-Air).

There are three main innovations in this project. We will propose novel data storage methods on a Connected BMS, exploring techniques for data compression without degrading fidelity. We will develop innovative algorithms, combining physics-based modelling and data driven techniques, to generate insight into the battery health through statistical inference. We will derive from these algorithms techniques to automatically update the BMS calibrations (in the form of de-ratings) that will be provided, over the air, to the CBMS.