School of Mathematics

Goncalo dos Reis receives several awards

Accurately predicting the lifetime of complex, non-linear systems such as lithium-ion batteries is critical for technological development. Understanding the ageing mechanisms and device variability within dynamic operating conditions remains challenging. Addressing this challenge of battery modelling constitutes an essential step to support a growing industrial activity in Scotland. The cost of a battery represents a considerable portion of an EV's total price, hence, how can one evaluate the price of a second-hand EV? How long will the battery last? How to determine if the battery is still fit for purpose? Once a battery is deemed no longer serviceable for EV use, what to do with it? The world is going through a momentous shift towards electric vehicles and renewable energy. A major part of this energy transition will be the widespread use of battery technology for transport, backup and grid storage. Once batteries are removed from vehicles they need to begin the 2nd life. The market for 2nd life batteries is at its onset, in energy storage (residential, grid support, storage units) and later recycling, however, there is no low cost, fast way to determine the most suitable use for a 2nd life battery There is no easy way to predict the lifespan and the expected performance of the battery in its 2nd life. No matter the application, EVs, consumer electronics, grid storage, the demand for easily accessible insightful health metrics for batteries is paramount for their lifespan prediction in particular.

These are the themes of several awards to Goncalo dos Reis:

  • Over £60,000 from the EPSRC Impact Acceleration Account for his commercialisation project entitled "Battery intelligence: Cell Evaluation and (early) Prognostics (BICEP) - a frameword for Li-ion Cell prognostics".
  • A Scottish Enterprise High-Growth Spin-Out Grant worth over £40,000 for his programme on "Predictive Energy". The High-Growth Spin-Out programme helps researchers to take their ideas and inventions from the lab to the global marketplace by awarding funding and support.
  • Funding for his project "Data-driven tools for battery lifecycle prediction" as part of the Data-Driven Innovation initiative "Building Back Better" call. This is part of the SFC Covid-19 recovery funding made to the University which allowed the DDI initiative to allocate funding for small grants to support staff to apply data-drive innovation ideas to promote job security, creation and retention within universities and economic and social recovery from the pandemic across the wider Edinburgh and South East Scotland region.