Online Capacity Estimation for Lithium-Ion Batteries in Partial Intervals Considering Charging Conditions

Abstract

Employed extensively for lithium-ion battery health assessment and capacity estimation, incremental capacity analysis (ICA) traditionally requires substantial time investment under standard charge and discharge conditions. However, in practical usage, Li-ion batteries rarely undergo full cycles. This study introduces aging temperature cycles within different partial intervals of the battery, integrating local ICA curves, peak range analysis, and incremental slope (IS) as an auxiliary feature. The extracted partial incremental capacity curves serve as features for state of health (SOH) estimation. The proposed temperature-rate-based SOH estimation method relies on a mechanistic function, analyzing relationships between temperature, different partial intervals, aging rate, and aging. Experimental tests on FCB21700 batteries demonstrate accurate SOH estimation using only partial charge curves, with an average error below 2.82%. By manipulating charging and discharging ranges, the method significantly extends battery lifespan, offering promising widespread applications.