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 pa- per 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 de- pendency 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.