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Professor David Howey and researchers at a University of Oxford public engagement event

Extending battery lifetime

Energy Storage

Dr David Howey runs a battery management lab where he and his team build battery systems and work out how to control them correctly, so that they last as long as possible.

Their main applications are electric transport and energy storage for the power grid. Their work involves running lots of tests on different battery cells and looking at how they behave in the real world, building models of their performance, and joining the dots from the technical constraints to the economic factors. They have developed a system which stops a battery pack from being limited by the worst-performing cell in the pack, allowing one to have a pack that lasts for a longer time, or is cheaper, or smaller. Dr Howey’s group have a spin-out company, Brill Power, which is working to commercialise some of this technology.

The experimental work of one of the DPhil Engineering students in Dr Howey’s team, Trishna Raj, who is also a member of St Hilda’s, has focused on characterising battery ageing. Part-funded by Jaguar Land Rover, Trishna is investigating path dependency of aging. She combines experimental testing and computer simulations to further the team’s understanding of how degradation mechanisms, and the sequence in which they occur, will impact on battery lifetime. This enables them to make accurate predictions, which allows for improved designs, asset valuation, and preventative maintenance.

One undergraduate student, Han Zhou (Engineering, 2015), was funded by St Hilda’s for a Summer Internship with Dr Howey. Dr Howey and Han worked with BBOXX, a company developing solutions to provide affordable, clean energy to off-grid communities in the developing world. The scale of this business has grown rapidly over the past ten years, and the company spends a significant amount of money on batteries. Han helped to develop algorithms to analyse date from off-grid energy systems in sub-Saharan Africa, to enable accurate failure detection and lifetime prediction.

Republished with kind permission of St Hilda's College. 

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