A discharging internal resistance dynamic model of lithium-ion batteries based on multiple influencing factors

Abstract

Direct current internal resistance (DCR) is a key indicator for assessing the health status of batteries, and it is of significant importance in practical applications for power estimation and battery thermal management. The DCR of lithium-ion batteries is influenced by factors such as environmental temperature, state of charge (SOC), and current rate (C-rate). In order to investigate the influence of these factors on battery DCR, this paper proposes a DCR dynamic model of lithium-ion battery based on multiple influencing factors (multi-factor). The model utilizes a binary quadratic polynomial to perform least squares fitting of the DCR with respect to environmental temperature and battery SOC. The obtained coefficients of the binary quadratic polynomial are then fitted with a cubic polynomial with respect to the C-rate, thus establishing the relationship between DCR and C-rate, environmental temperature, and SOC. Multi-rate hybrid pulse power characterization (HPPC) experiment is conducted to perform charging-discharging tests on lithiumion batteries. The experimental results demonstrate that the RMSE between the estimated DCR obtained from the established model and the experimental values is 0.9758 mΩ, confirming the effectiveness of the proposed DCR model.

摘要

直流内阻(DCR)是衡量电池健康状况的关键指标,在实际应用中对功率状态的估算以及热管理 都具有重要意义。锂离子电池放电DCR与环境温度、电池荷电状态(SOC)以及放电倍率(C-rate)等因素 有关,为了研究这些因素对电池内阻的影响,本文提出一种基于多影响因素的锂离子电池放电内阻动 态模型,利用二元四次多项式对DCR与环境温度和电池SOC进行最小二乘拟合,再将所得二元四次 多项式系数与放电倍率进行三次多项式拟合,最终建立DCR与放电倍率、环境温度和SOC之间关系 的内阻模型。运用多倍率混合脉冲功率特性(HPPC)实验对锂离子电池进行充放电测试,并根据测试数 据对所提出的模型进行验证,实验结果表明,所建立的动态内阻模型获得的DCR估算值与实验值的最 大均方根误差为0.9758 mΩ,证明所提出的电池放电内阻模型是有效的。