Innovation

The Team’s key product is based on the ability to predict accurately state of charge (SoC) and state of health (SoH) from measurements of battery current and voltage. The knowledge underpinning this technology and of what is inside a battery from an electronic engineering viewpoint has come from a novel and powerful measurement system.

The novelty lies in leading-edge developments in extra-low frequency characterization (i.e., measurements taken over very long timescales that are representative of the usage cycles of batteries in the real world), identification and computation of equivalent-circuit models containing CPEs, and powerful new data-fitting algorithms. These will revolutionize BMSs and battery quality assessment. CPEs are circuit elements that are now known to represent accurately the energy storage and release characteristics of batteries. They can be viewed simplistically as resembling ‘leaky capacitors’, and their behavior is described mathematically by fractional calculus. This enables us to equip our battery models with the CPE components required for realistic characterization and prediction, to identity hallmarks of aging and degradation, and to provide timely warning of need for replacement to users.