Effect of Sample Interval on the Parameter Identification Results of RC Equivalent Circuit Models of Li-ion Battery: An Investigation Based on HPPC Test Data

Abstract

The validity of the equivalent circuit model (ECM), which is crucial for the development of lithium-ion batteries (LIBs) and state evaluation, is primarily dependent on the precision of the findings of parameter identification. In this study, the commonly used first-order RC (1-RC) circuit and second-order RC (2-RC) circuit models were selected for parameter identification. A time series of voltage with different sample intervals were used for function fitting based on the least square method, which were extracted from the hybrid pulse power characteristic (HPPC) test data of a commercial square punch LIB, and the sample intervals were set to be 0.1 s, 0.2 s, 0.5 s, and 1.0 s to evaluate the effect of sample interval on the parameter identification results. When the sample interval is more than 0.5 s, the results reveal that the 2-RC circuit model’s goodness of fit marginally declines, and for some data scenarios, the bias between the fitted terminal voltage curve and test curve increases obviously. With all of the sample intervals under consideration, the 1-RC circuit model’s imitative effect is satisfactory. This work demonstrates that the sample interval of data samples, in addition to the method itself, affects the accuracy and robustness of parameter identification, with the 1-RC circuit model showing larger advantages under low sample frequency compared to the 2-RC circuit model.

Keywords

• Lithium-ion battery
• equivalent circuit model
• parameter identification
• sample interval
• hybrid pulse power characteristic test
• least square method