We design systems and develop diagnostics and control algorithms for electrochemical energy devices such as batteries and supercapacitors, in applications from electric cars to grid power systems.
The group is led by Professor David Howey at the Department of Engineering Science in the University of Oxford.
Our aim is to improve performance and cost by predicting dynamics and lifetime, estimating temperatures and faults, and measuring how and why devices perform in the real world. This requires us to address fundamental issues in modelling, instrumentation and data processing.
A warm welcome to new group members Blanka Gaál and Tihana Štefanić who arrived in October and are working on LMFP modelling/testing and electrochemical-thermal-mechanical coupling in large format cells, respectively, both with industry partners.
Several of us had a great time attending the Faraday Institution’s annual conference, this year held at Newcastle University, where we presented work on battery electro-thermal modelling, parallel packs, and lifetime prediction.
A warm welcome to new group members Emmanuelle Hagopian and Joe Ross who arrived in October and are working on voltage hysteresis and power prediction, respectively. We were sad to say goodbye to Antti Aitio recently who has moved to take up a position in industry. You can read about his awesome PhD work on battery life diagnostics and machine learning here.
It’s been a busy few months as the world opens up to travelling again. Professor Howey gave keynote presentations at ModVal in Germany, the ISE Topical Meeting in Sweden, and the Benelux Meeting on Systems and Control; Nicola Courtier and Ross Drummond spent time working with Luis Cuoto at ULB in Belgium on battery fast charging, and Gosia Wojtala gave a talk at the 241st ECS Meeting on how battery ageing impacts entropy measurements.
Huge congratulations to Sam Greenbank who today successfully defended his doctoral work on battery aging using machine learning to predict lifetime. Read more about this topic in Sam’s excellent IEEE paper.