Anna G. Stefanopoulou, PhD, William Clay Ford Professor of Technology, Professor Mechanical Engineering, Professor of Electrical and Computer Engineering, University of Michigan
Accurate predictions of degradation and lifetime of lithium-ion batteries are essential for reliability, safety, and key to repurposing. Cycle life is a key performance metric for a battery management system since it can dynamically adjust operation limits based on their impact on lifetime 10-20 years ahead. A health-conscious power derating or a temporary stretch of power capability will be continuously adjusted depending on the short-term economics and long-term durability predictions. We show an adaptive inter-cycle extrapolation algorithm that allows us to simulate the entire lifetime of the battery in seconds for a real-time decision. The accelerated simulation allows us also to iteratively tune (learn) degradation parameters to match experimental observations of capacity fade, loss of lithium inventory, and individual electrode capacities (features) from both cycling and calendar aging.