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公开(公告)号:US20230003802A1
公开(公告)日:2023-01-05
申请号:US17854980
申请日:2022-06-30
Applicant: UNIVERSITY OF SOUTH CAROLINA
IPC: G01R31/367 , G01R31/3835 , G01R31/392
Abstract: Method provides accurate state-of-health (SOH) diagnostics and prognostics during the whole-life-service of a lithium-ion battery by considering the effects of state- of-charge (SOC) and SOH on certain parameters (such as consideration of nonlinearity of the terminal voltage) during the process of SOC diagnostics and prognostics. The method integrates Lebesgue sampling and equivalent circuit model (ECM) analysis, which greatly decreases computation cost and uncertainty accumulation to provide efficient acquisition of open circuit voltage (OCV) determinations for the ECM process. The OCV curve of the battery was obtained during Hybrid Pulse Power Characterization testing by fitting a series of selected OCV points after enough rest of the subject battery. Identified parameters of ECM are updated according to terminal voltage measurement to enable accurate SOC estimation and prediction during the period from full charge to full discharge of the battery. Parameter identification is re-conducted and an initial condition for SOC estimation is updated according to SOH to enable accurate SOC estimation during the whole-life-service of battery.