Validating the state-of-function (SOF) algorithm is critical for battery management as it is responsible for battery power utilization as well as safety protection and life. The SOF accomplishes this optimization task by communicating battery level operational limits related to power, current, voltage and temperature. Ultimately these operational limits are predicted via parameters derived from component models. Correspondingly, any errors within the component models will propagate into the reported SOF limits. Developing an efficient SOF validation methodology will facilitate the understanding of SOF performance gaps. In this work, we developed a methodology that consists of simulating the cell model response and SOF output for a set of current pulse events that span operational boundaries defined by temperature, initial state-of-charge, pulse time and current magnitude. Each pulse event is then tested at the pack level for comparison with the simulated cell response as well as SOF output. A validation algorithm analyzes the array of events from the simulation and test environments and then generates a validation report that graphically highlights areas of concern. Consequently, SOF performance can be more easily tuned to meet battery power, safety and life requirements.