EE Distinguished Lecturer Seminar: Squeezing more out of Lithium-ion battery grid energy storage systems by accurately modelling battery degradation


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Date and time 27.09.2019 13:3014:30  
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Speaker David Howey is an Associate Professor in the Department of Engineering Science at the University of Oxford, where he leads a research group focused on modelling, diagnostics and control of electrochemical energy devices and systems, with a particular focus on batteries. He has active current research on degradation, thermal and electrochemical modelling, data driven health prediction, parameter estimation, and control of grid energy storage, sponsored by EPSRC, the Faraday Institution, InnovateUK and companies including Siemens and Continental AG. He is an IEEE Senior Member, ECS Member, and editor of IEEE Transactions on Sustainable Energy. He is also a co-founder of battery management system company and technical advisor to grid storage optimisation company His group website
Category Conferences - Seminars
Abstract: The lifetime of lithium-ion batteries is a key element in the business case for grid-connected energy storage. Battery degradation is the result of many different processes. This presentation will discuss a range of different models that existing for simulating degradation, and how these can be incorporated into optimisation of usage for energy arbitrage applications. Various battery degradation models exist, of differing complexity, accuracy and data-requirements. The simplest model is a linear degradation model assuming a maximum energy throughput over the battery’s lifetime. A second class are the empirical degradation models, interpolating test data sets. Different empirical models include different operating conditions, depending on the dominant degradation mechanisms appearing in the data set. Thirdly, electrochemical degradation models try to capture the physics of the degradation processes. A comprehensive overview of different modelling approaches will be given, using the single particle model (SPM) as a framework for investigating behaviour. The different degradation models are implemented as add-ons to the SPM leading to a flexible framework, which allows to assess the effects of individual assumptions, as well as how different mechanisms interact. The SPM with a side reaction at the negative electrode is then used within an optimisation algorithm to perform ‘degradation aware’ energy arbitrage over one year. Results show that the profit in this application can be increased substantially and degradation can be reduced by using more realistic models. This illustrates that using a simplistic battery model in a techno-economic assessment of grid-connected batteries might substantially underestimate the business case and lead to erroneous conclusions. These results have also been recently validated with experimental cycling tests of battery cells using different profiles, and measured data will be shown from these tests. References: (1) Reniers, J. M., Mulder, G., Ober-Blöbaum, S., & Howey, D. A. (2018). “Improving optimal control of grid-connected lithium-ion batteries through more accurate battery and degradation modelling”. Journal of Power Sources, 379, 91-102. (2) Reniers, J., Howey, D., & Mulder, G. (2019), ECSArXiv pre-print “Review and performance comparison of mechanical-chemical degradation models for lithium-ion batteries”, DOI 10.1149/ (3) Software

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  • General public
  • Free


  • Prof. Elison Matioli


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