Estimating the Power Capability of Li-ion Batteries Using Informationally Partitioned Estimators

Enforcing constraints on the maximum deliverable power is essential to protect lithium-ion batteries and to maximize resource utilization. This paper describes an algorithm to address the estimation of power capability of battery systems accounting for thermal and electrical constraints. The algorithm is based on model inversion to compute the limiting currents and, hence, power capability. The adequacy of model inversion significantly depends on the accuracy of model states and parameters. Herein, these are estimated by designing cascading estimators whose structure is determined by quantifying the relative estimability of states and parameters. The parameterized battery model and the estimation algorithms are integrated with a power management system in a model of a series hybrid electric vehicle to demonstrate their effectiveness.