Generalized Recursive Algorithm for Adaptive Multiparameter Regression

We derive and implement an algorithm that can accommodate an arbitrary number of model parameters, thereby allowing for more complicated battery models to be employed in formulating model reference adaptive systems as part of an energy management scheme for systems employing batteries. We employ the (controls) methodology of weighted recursive least squares with exponential forgetting. The output from the adaptive algorithm is the battery state of charge (remaining energy), state of health (relative to the battery's nominal rating), and power capability. The adaptive characterization of lead acid, nickel metal hydride, and lithium-ion batteries is investigated with the algorithm. The algorithm works well for lithium-ion and lead-acid batteries; more work is needed on nickel metal hydride batteries.