Understanding Li-ion Battery Degradation Under Realistic Loads

Electrochemical systems, including batteries, play a pivotal role in the transition towards a low-carbon economy. The global rise in renewable energy adoption has stimulated a high demand for energy storage technologies. As more energy is derived from fluctuating renewable sources, energy storage systems capable of retaining this energy become increasingly valuable. Batteries serve to balance the demand for electricity with the supply from green energy sources. However, various degradation mechanisms impact electrochemical systems' performance and longevity by affecting their different components. Therefore, understanding and mitigating these degradation phenomena is vital to improve the durability, efficiency, and reliability of these systems. The stability of electrochemical systems over time, particularly when powered by naturally intermittent renewable sources like solar or wind with fluctuating input power profiles, remains a complex issue. The escalating demand for Lithium-Ion Batteries (LIBs) across various sectors, ranging from portable devices to electric vehicles and grid-scale energy storage systems, underscores the importance of investigating battery degradation over time under realistic loading scenarios. To investigate these degradation mechanisms, novel in-situ or ex-situ characterization techniques are needed to capture the aging phenomena in batteries. Typically test methods used in existing literature are not realistic. Therefore, in this study, a Power-Hardware-in-the-Loop (PHIL) system is introduced to perform aging studies on various Li-ion chemistries under realistic load profiles. We developed a test station that can emulate real loading profiles and monitor system health in response. The aim of this research is to provide a tool to characterize the effect of differences in operating conditions such that we can develop control methods to minimize degradation rates. Here we present preliminary requirement on Li-ion battery real time testing to achieve an understanding of battery degradation phenomena in real-world applications.