储能工况下磷酸铁锂电池动态辨识方案研究

发布时间：2018-08-26 14:20

【摘要】：锂离子电池的动态性能受温度、电流及老化等多种因素制约,限制了电池储能系统的大规模推广和应用,同时由于传统的参数辨识方法只能准确辨识电池开路电压,而复杂的储能电池工况却对储能电池组的性能参数辨识提出了更高要求。以储能用大容量磷酸铁锂电池为研究对象,分析了传统电池参数辨识对不同温度、不同电流倍率下电池动态性能的估计误差,综合利用一阶和二阶等效电路模型研究了参数辨识在不同使用区间的精度,结合典型储能工况提出了复合脉冲序列条件下的粒子群参数辨识方法。实验结果表明该方法对于准确评估单体和串联电池组的动态电压及性能表征参数具有较高的精度,为大规模储能系统电池参数的在线辨识和电池评估提供依据。
[Abstract]:The dynamic performance of lithium-ion battery is restricted by many factors, such as temperature, current, aging and so on, which limits the large-scale popularization and application of battery energy storage system. At the same time, the traditional parameter identification method can only accurately identify the open circuit voltage of the battery. However, the complex operating conditions of energy storage cells require higher performance parameters identification of energy storage batteries. The estimation error of traditional battery parameter identification for battery dynamic performance at different temperature and different current ratio is analyzed by taking the high-capacity lithium iron phosphate battery for energy storage as the research object. The accuracy of parameter identification in different application regions is studied by using the first and second order equivalent circuit models. A particle swarm optimization method for parameter identification under the condition of composite pulse sequence is proposed in combination with typical energy storage conditions. The experimental results show that the proposed method has a high accuracy for accurately evaluating the dynamic voltage and performance parameters of single and tandem batteries, and provides a basis for on-line identification and evaluation of battery parameters in large-scale energy storage systems.
【作者单位】：北京交通大学国家能源主动配电网技术研发中心;
【基金】：国家“863”高技术基金项目(2011AA05A108)
【分类号】：TM912

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