Cell sorting: The earth orbiting spacecrafts use Lithium-ion battery as an energy storage device. Each battery is made up of several series and parallel connected cells. The constraints concerning the cell parameters, obtained by testing, drive the placement of a cell in a particular location in the battery. The cell sorting techniques are used to obtain the required performance in a battery pack. An improved cell sorting method using the genetic algorithm with mixed-integer linear optimization is proposed. It sorts the cell parameters randomly to match them within a set of tight constraints.

Cell performance modeling: Even the closely matched cells in the battery exhibit slightly different performance and experience different temperatures during their use. Due to prohibitive costs, the spacecraft application does not have an option of repair or replacement once it is in space. Hence, there is a need to understand the cell behavior within a battery pack. A nonlinear regression model is developed to estimate cell performance in the battery (CPB) used for spacecraft applications. The CPB model is validated with experimental results and is within an RMSE of 2%.