Battery Capacity Estimation of Low-Earth Orbit Satellite Application

Simultaneous estimation of the battery capacity and state- of-charge is a difficult problem because they are dependent on each other and neither is directly measurable. This paper proposes a particle filtering approach for the estimation of the battery state-of-charge and a statistical method to estimate the battery capacity. Two different methods and time scales have been used for this estimation in order to reduce the dependency on each other. The algorithms are validated using experimental data from A123 graphite/LiFePO4 lithium ion commercial-off-the-shelf cells, aged under partial depth-of- discharge cycling as encountered in low-earth-orbit satellite applications. The model-based method is extensible to bat- tery applications with arbitrary duty-cycles.