These are algorithms used in battery management systems (BMS) to estimate important battery parameters that cannot be measured by the BMS, like state of charge and state of health. Kalman filters, for example, use a series of measurements observed over time, containing statistical noise and other inaccuracies, and produce estimates of unknown variables that tend to be more precise than those based on a single measurement alone.