If a lithium metal polymer battery is operated at 50% DOD, the cycle life of the battery is 2.7 times longer than that operated at 80% DOD [26]. This is similar for other types of batteries, even
life-cycle inventory studies o lead-acid, nickelf -cadmium, nickel-metal hydride, sodium-sulfur, and lithium-ion battery technologies. Data were sought that represent the production of battery constituent materials and battery manufacture and assembly. Life-cycle production data for many battery materials are available
Ren, L. et al. Remaining useful life prediction for lithium-ion battery: a deep learning approach. IEEE Access 6 , 50587–50598 (2018). Article Google Scholar
Bl = Bc Iata ta+ts + Ists ta+ts B l = B c I a t a t a + t s + I s t s t a + t s. Where: B l = Battery lifetime in hours. B c = Battery capacity in mAh. I a = Device current consumption when awake in mA. I s = Device current consumption when in Sleep Mode in mA. t a = Time spent awake in seconds (per cycle)
BLAST: Battery Lifetime Analysis and Simulation Tool Suite. This suite of tools pairs NREL's high-fidelity battery degradation model with electrical and thermal performance models for modeling battery cells, packs, and systems. Open-source models for battery lifetime are provided for users to explore battery life research questions.
Many prior publications have attempted to early predict the lithium-ion battery cycle life. Summarizing these studies, it is not difficult to find that methods for early prediction of lithium-ion battery's cycle life can be categorized into two main types: model-based method and data-driven method [5]. Model-based methods rely on models that
. 163 372 191 318 24 192 148 98 134
li ion battery life cycle
