The battery industry is growing at an exceptional rate driven by the growing electric vehicle industry. Range and power demands from consumers are forcing the industry to develop more capable batteries. Therefore, along with new chemistries being developed, existing chemistries are continually tweaked to meet a need. These, often small changes in chemistry, can result in large changes in the behaviour of the battery over a single cycle or its lifetime. Understanding battery behaviour can be achieved either through a detailed set of experiments, which is time and cost intensive and therefore not often feasible, or through the development of battery models. The accuracy of these models is heavily dependent on the experimental data used for the model parameterisation. In addition, the speed at which models can be developed is dependent on the experimental technique used for collection of data required for model parameterisation.
GITT (galvanostatic intermittent titration technique) tests are typically used to parameterise ECMs (equivalent circuit models) for batteries. If done well, a GITT test can take up to 80 hours to complete and if this is repeated at multiple temperatures, a full parameter set can take few weeks to compile. The ESE group at Imperial College London has developed an innovative experimental technique which takes less than 8 hours to complete for each test temperature. Models parameterised using AMPP (accelerated model parametrisation procedure) are as good as those models parametrised using GITT, however, AMPP is 90% faster.