Degradation and Multi-Time-Scale State Estimation of Li-Ion Batteries in Satellites

Abstract

In-orbit satellite REIMEI, developed by the Japan Aerospace Exploration Agency (JAXA), has been relying on off-the-shelf Li-ion batteries since its launch in 2005 [1]. The performance and durability of Li-ion batteries is impacted by various degradation mechanisms, one of which is the growth of the solid-electrolyte interphase (SEI). Long-term SEI growth is the greatest contributor to capacity fade in lithium-ion batteries.In this contribution, we will address several aspects of the modeling and simulation of the batteries of satellite REIMEI. We simulate long-term degradation under the generic LEO satellite cycling conditions in a P2D framework. The simulations are validated with experiments and in-flight data provided by JAXA [1]. Our group has developed models for long-term SEI growth [2,3]. To show the inhomogeneous growth of the SEI in 3D, we perform microstructure-resolved simulations [4].These studies are the foundation for analyzing the states of the batteries, which cannot be measured in operando. To estimate the state of charge and state of health, we make use of filter techniques and the in-flight data of the satellite batteries. Kalman filters are particularly suitable for the noisy data. Since the states change on different timescales, a multi-time-scale algorithm is applied, where two filters are combined. With this approach, we aim to reliably predict the lifetime of satellite batteries in orbit.