From the University of Oxford’s Battery Intelligence Lab
The University of Oxford’s Department of Engineering Science is world-leading and covers the entire spectrum of engineering disciplines, from traditional engineering like turbines or heat flow to cutting-edge topics like machine learning. Our research group at the Department is the Battery Intelligence Lab, and as you can infer from the name, we research batteries and specifically lithium-ion batteries. We understand how they work, their efficiencies in terms of thermal behaviour, degradation and all these other things. That’s important because these details are really hidden and the investors and developers building and operating these batteries don’t necessarily have that level of insight into how high-level decisions will impact individual cells.
Creating a digital twin: How and why
My role within Energy Superhub Oxford is to create a digital twin of the grid battery. This is basically a model of the physical asset which can simulate every individual component inside the battery and how they work together. A lot of physical assets are black boxes. When you buy an asset the manufacturer provides a data sheet on how you should use it and what you should expect from it.
For instance, a battery will tell you how often it can be charged or discharged at certain power levels, and what efficiencies and behaviour you can expect. It’s a very high-level overview when what you actually have is a field full of containers of tens of thousands of cells.
The digital twin allows you to understand how everything works together, and more importantly to test different scenarios. If you have an asset which is worth tens of millions of pounds, you don’t want to do something in the real world unless you’re certain it will work, because it’s quite expensive if you make a mistake!
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