For accurate estimation of battery lifetime, researchers have developed analytical and empirical models and applied them to representative load profiles. However, accurate battery models are not available for most batteries on the market. Although high-accuracy simulation models exist for certain battery chemistries, they are computationally intensive and still require calibration through trial and error. To address this problem, this paper presents a low-cost load emulation platform for automated, accurate battery estimation. By draining a battery with high-frequency emulation of a system power profile, all of the battery characteristics are accounted for, including the discharge rate and recovery effects. A designer can then accurately observe how the system effects battery life, quantify lifetime performance for multiple batteries, and ultimately optimize the system's power scheduling around a particular battery.