A cell sorting Algorithm for series-parallel configured Lithium ion battery packs in spacecrafts

The Series-parallel (s-p) configured Lithium ion batteries find use in many spacecrafts. Cell selection to make a battery pack involves sorting tested cells to meet screening and matching criteria. Cell capacity, cell resistance, and self-discharge could be used for cell selection. Conventionally, data is linearly sorted into ascending or descending order based on one parameter. Matching criteria are applied to choose cells to be put into strings. Cell sorting using the Genetic Algorithm (GA), involving mixed-integer linear optimization, is proposed in this paper. Cells are arranged randomly to match all of the parameters within a set of tight constraints. A better match for the cells is achieved by multiple iterations. GA Improved Cell Sorting Algorithm (GICSA) is verified with experimental data and has given close to 100% cell yield.