<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-06-22T07:57:45Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/FAB29F48-FE88-45A3-AF9A-E4D317216A94" ns1:id="FAB29F48-FE88-45A3-AF9A-E4D317216A94"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/FB3E0F48-F53B-4583-8DE4-149AEEBBA5C6" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/B3D759FF-F1BF-4184-A582-944EA26ADDB7" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/FB3E0F48-F53B-4583-8DE4-149AEEBBA5C6" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2017-02-28T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/3BFF9D31-903F-4FA5-B8AD-9F888E821739" ns1:rel="FUND" ns1:start="2016-03-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">132224</ns2:identifier></ns2:identifiers><ns2:title>Diagnostics and Prognostics for Lithium-ion Battery Systems</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Feasibility Studies</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>The growth in electric vehicles and renewables is placing greater demands on energy storage and energy

management. Much of these applications are dependent on large Lithium-ion battery packs. The

Electrochemical Science and Engineering group at Imperial College London are world leaders in modelling

lithium-ion cells to estimate the pack state of charge, and the advanced techniques that can be used to

diagnose and predict degradation and failure. Dukosi Ltd has developed an innovate and disruptive Battery

Management System technology that can implement these advanced techniques. The project will implement

and demonstrate the best available techniques within a battery pack. This Feasibility Study will potentially lead

to the development of the worlds most intelligent BMS system with unique diagnostics and prognostics

capabilities.</ns2:abstractText></ns2:project>