Mac Geoffrey is a PhD student in Systems Engineering and Cohort 3 member of EPSRC AAPS CDT at the University of Bath.
His project focuses on ultrasound testing for battery management systems bringing this advanced technique to automotive batteries authorising continuous in-service charge and health monitoring.
Mac Geoffrey has interest in providing advanced expertise in the area of digital signal processing with concentration towards end-to-end research, development, integration, and prototyping. Also, he is the founder of Imperium Potentia (IP) – a platform aiming to innovate power systems while introducing new insights, articles, and artefacts through scientific investigation to shape an efficient and fair global economy.
His alma mater includes a master’s degree with Distinction in Engineering with Management from King’s College London (class of 2021), and a bachelor’s degree with First Class Honours in Mechanical Engineering from London South Bank University (class of 2020).
Batteries change in density as they are charged and discharged, and recent research has shown that ultrasound can be used to detect these changes, allowing the charge level of the battery to be detected. This project aims to take this new technique and apply it to automotive batteries to allow continuous in-service charge and health monitoring.
Batteries are key to the sustainability of future transportation solutions, and ultrasonic charge monitoring has several advantages which make it interesting. Presently, battery state of charge (SOC) is 'tracked' by charging the battery to its maximum voltage and setting SOC to 100% (full), and then integrating the charge (or energy) taken from it. The ultrasound method allows the battery SOC to be directly measured at any time, even while being used, and without needing to know the usage history since the last charge. This will allow for better estimation of SOC and maximum power limits, improved battery range estimation (in Electric Vehicles) and accelerated battery testing.
Ultrasonic charge monitoring has been demonstrated in laboratory tests at an individual cell level. The changes in the mechanical properties of the battery change the sound speed of an ultrasound pulse travelling through the battery cell. The sound speed is determined by measuring the time taken for a pulse to traverse the cell and is used to infer the SOC. Automotive batteries consist of many cells, and we need your help to explore how this method can be applied to multiple cells stacked in a module, and how this might constrain module design. You will design and build a test system, collect data from it, use analysis and numerical modelling to interpret the data, and test the effects of different sensor and module designs.