Influence of Sampling Delay on the Estimation of Lithium-Ion Battery Parameters and an Optimized Estimation Method

Bing Jiang, Zeqi Chen and Feifan Chen
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Bing Jiang: State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University, Beijing 100084, China
Zeqi Chen: State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University, Beijing 100084, China
Feifan Chen: State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University, Beijing 100084, China

Energies, 2019, vol. 12, issue 10, 1-16

Abstract: The equivalent-circuit model (ECM) is widely used in online estimating the parameters and states of lithium-ion batteries. However, the sampling delay between the voltage and current of a battery is generally overlooked, which is unavoidable in a modular battery management system (BMS) and would lead to wrong results in the estimation of battery parameters and states. In this paper, with the first-order resistor–capacitor (RC) model as our battery model, we analyze the influence mechanism of sampling delay and then propose an optimized method for online estimating battery parameters. The mathematical model derived from the first-order RC model and the approximation method of first-order derivative are optimized. The recursive least squares (RLS) algorithm is used for identifying the parameters of the model. In order to verify the proposed method, a modular battery test system with high sampling frequency and high synchronization accuracy is developed. The experiment results indicate that the sampling delay would cause the estimation process to fluctuate, and the optimized method effectively improves the tolerance range of sampling delay.

Keywords: open-circuit voltage; internal resistance; equivalent-circuit model; sampling delay (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
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