Optimizing Cycle Life Prediction of Lithium-ion Batteries via a Physics-Informed Model

arXiv:2404.17174v1 Announce Type: new
Abstract: Accurately measuring the cycle lifetime of commercial lithium-ion batteries is crucial for performance and technology development. We introduce a novel hybrid approach combining a physics-based equation with a self-attention model to predict the cycle lifetimes of commercial lithium iron phosphate graphite cells via early-cycle data. After fitting capacity loss curves to this physics-based equation, we then use a self-attention layer to reconstruct entire battery capacity loss curves. Our model exhibits comparable performances to existing models …

abstract arxiv attention batteries cells commercial cs.lg development equation hybrid hybrid approach life lithium lithium-ion batteries measuring novel performance physics physics-informed prediction self-attention technology type via