Life verification of large capacity Yardney Li-ion cells and batteries in support of NASA missions

Abstract

SUMMARYLithium-ion batteries have been used on a number of NASA missions and have been base-lined for use on a number of up-coming aerospace applications. The Li-ion cells and batteries that have been developed together with Yardney Technical Products are especially attractive due to their high specific energy and energy density, good performance over a wide operating temperature range, as well as their good calendar and cycle life performance. However, given that the Li-ion technology is relatively new to the aerospace community and that mature, large capacity prototype cells have continued to evolve over the last 10 years, real-time performance test data is especially valuable in demonstrating the capabilities over a number of environmental and application specific conditions. For this reason, we have focused on performing a number of generic and mission specific performance life tests to establish the viability of the technology to meet current and future applications. In this work, we will describe the results of a number of generic cycle life tests, including 100% depth-of-discharge (DOD) cycling at various temperatures, partial DOD cycling simulating planetary orbiters and low earth orbit (LEO) satellite conditions, as well as partial DOD mission specific testing. We will also describe the results obtained from a number of calendar life tests where the cells were stored under different conditions, such as at different temperatures and different storage modes (i.e. open circuit voltage (OCV) conditions and storage under trickle charge conditions). Methods to quantify the capacity degradation and impedance growth of the batteries when subjected to different electrical and environmental conditions will be discussed, as well as, possible degradation mechanisms that can lead to reduced lifetime.

Behavior and state-of-health monitoring of Li-ion batteries using impedance spectroscopy and recurrent neural networks

“…Nevertheless, artificial neural networks (ANNs) present a useful alternative for forecasting nonlinear dynamics and complex behaviors [19][20][21][22][23][24][25][26]. ANN techniques are capable of solving complex problems where traditional methods have failed.…”

“…In this study, cell temperature (T), the amplitude of SOC variations (DSOC = SOCmax À SOCmin), current pulse (I) magnitude, and the charge throughput of a micro-cycle (CT in As) are considered the main factors of aging in power cycling tests [21][22][23][24].…”

Strategy for lithium-ion battery performance improvement during power cycling

“…From literature and previous studies on lithium-ion battery aging, it was demonstrated that, for power cycling aging, temperature (T), the State-of-Charge variation (∆SoC) and the magnitude of the current pulse (I) were considered as the main factors of aging [9]. However, for calendar aging, SOC and temperature are the main influencing parameters on battery performances [10].…”

Reactive execution for solving plan failures in planning control applications

“…The rover could perform reconnaissance activities [12] to identify interesting targets and maps for future missions. After a long time, the rover may lose capabilities [28,42] (e.g. reduced mobility due to wear and tear on motors or mechanical systems, reduced power generation due to battery degradation, accumulated dust on solar arrays), as happened with the Spirit and Opportunity rovers.…”