Hysteresis Modeling and SOC Estimation for LiFePO4 Batteries under Charging and Discharging Conditions
梁莹 1孙涛 1郑岳久1
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作者信息
1. 上海理工大学机械工程学院,上海 200093
折叠
摘要
针对磷酸铁锂电池(LiFePO4)平坦的开路电压OCV(open circuit voltage)与荷电状态SOC(state of charge)滞回特性在充、放电切换工况下传统等效电路模型估计OCV存在精度较低的问题,提出电池迟滞建模.为了突出LiFePO4电池考虑滞回特性的必要性,对3种电池模型的复杂性、准确性和适用性进行综合评价和对比分析.结果表明,一阶RC模型不考虑滞回的影响,仅适用纯充电或纯放电的工况;一阶RC滞回模型在一阶RC模型的基础上增加1个滞回量,虽考虑了滞回特性的影响,但滞回量受参数辨识影响较大,OCV估计存在波动;Preisach模型对存在充、放电切换工况的估算精度较好,但训练数据时间成本较高.NEDC(new European driving cycle)充、放电工况下对不同模型结合算法估计SOC,估计误差均在5％以内,其中Preisach误差在3％以内.
Abstract
In view of the flat hysteresis characteristics of open circuit voltage(OCV)and state of charge(SOC)of LiFePO4 batteries,the OCV estimated by using the traditional equivalent circuit model has the problem of low accuracy under the charge-discharge switching conditions,so the hysteresis modeling of battery is proposed.To highlight the necessity of considering the hysteretic characteristics of LiFePO4 batteries,three battery models are compared to comprehensively evaluate their complexity,accuracy and applicability.Results show that the first-order RC model is only suitable for pure charge or pure discharge conditions without considering the influence of hysteresis.The first-order RC hysteresis model adds a hysteresis on the basis of the first-order RC model.Although the influence of hysteresis characteristics is considered,the hysteresis is greatly affected by parameter identification and the OCV estimation fluctuates.The Preisach model has a good accuracy under the charge-discharge switching conditions,but the corresponding training data and time cost are high.Under the new European driving cycle(NEDC)charging and discharging conditions,SOC estimation is carried out for different models combined with algorithms,and the estimation errors are all within 5％,among which the Preisach error is within 3％.
关键词
LiFePO4电池/OCV-SOC迟滞特性/等效电路模型/Preisach模型/SOC估计
Key words
LiFePO4 battery/hysteresis characteristics of open circuit voltage-state of charge(OCV-SOC)/equivalent circuit model/Preisach model/SOC estimation
万方数据