锂动力电池动态一致性评价方法的研究

发布时间：2018-03-27 17:36

本文选题：锂动力电池　切入点：SOC预测　出处：《哈尔滨理工大学》2015年硕士论文

【摘要】：锂动力电池，以其比容量高和长循环寿命，在动力电池领域作为技术革新的重要支持。尽管制造工艺以及使用管理技术不断提高，在实际的使用中，，都需要将各单体电池，通过串联或并联的方式成组使用，而在长期的使用后，电池组都会出现性能大幅衰减的现象。经研究表明，这是由于构成电池组的单体电池在一致性上出现了明显的差异。因此，为了让动力电池组在长期使用过程中，都能一直保持有较高的性能，延长整个电池组的使用寿命，就需要对组内单体电池的一致性有较好的判断，以便于电池管理系统(BMS)以及用户对其进行及时维护。对动力电池的一致性概念进行了研究，经过大量的实验，并对实验数据进行分析发现在多个性能参数中，电池的荷电状态(SOC)和动力电池的工作电压(CCV)能够全面的显示电池当前的状态，同时也是电池动态特性的集中体现，可以作为评价电池一致性评价的技术指标。本文建立并改进了动力电池的等效模型，在模型建立过程中，引入了权值向量A(m)，来更好地反映这一差异的存在。文中采用平方根容积卡尔曼滤波法，结合强跟踪滤波理论(SCKF-STF)对SOC进行预测，给出了预测结果和误差分析，在算法的前端设计并加入了多重滤波算法，对混入的噪声进行处理，并结合针对一致性差异的等效模型，进一步提高算法的预测精度，同时加入了仿真分析对方案的可行性进行了验证。文中采用数理统计的F分布概率密度函数实现用SOC和工作电压对一致性评价的综合分析。根据动力电池的实际参数，给出相应对概率密度函数的描述，进而得到概率密度曲线，通过设定一致性预警阈值，得出符合预期的结果区域，将实验数据代入函数表达式后得出的计算结果，如果计算结果在该区域中，则可以得出该组实验电池的一致性较好的结论。
[Abstract]:Lithium power battery, with its high specific capacity and long cycle life, is an important support for technological innovation in the field of power battery. In series or in parallel, the battery pack is used in groups, and after a long period of time, the performance of the battery pack attenuates significantly. This is because there is a clear difference in consistency between the single cells that make up the battery pack. So, in order to keep the power battery in the long run, it can maintain high performance and prolong the service life of the whole battery pack. It is necessary to judge the consistency of the single cell in the group so as to facilitate the battery management system (BMS) and the user to maintain it in time. The concept of consistency of power battery is studied. After a large number of experiments and analysis of the experimental data, it is found that there are many performance parameters. The current state of the battery and the operating voltage of the power battery can be displayed comprehensively, and the dynamic characteristics of the battery are also reflected. It can be used as the technical index to evaluate the battery consistency. In this paper, the equivalent model of power battery is established and improved. In the process of establishing the model, the weight vector Agnemer is introduced to better reflect the existence of this difference. The square root volume Kalman filter method is used in this paper. Combining the strong tracking filter theory with SCKF-STF to predict the SOC, the prediction results and error analysis are given. The multiple filtering algorithm is designed and added in the front end of the algorithm to deal with the mixed noise, and the equivalent model aiming at the consistency difference is combined. The prediction accuracy of the algorithm is further improved, and the feasibility of the scheme is verified by adding simulation analysis. In this paper, the F distribution probability density function of mathematical statistics is used to realize the comprehensive analysis of consistency evaluation using SOC and working voltage. According to the actual parameters of power battery, the corresponding description of probability density function is given. Then the probability density curve is obtained. By setting a consistent warning threshold, the expected result region is obtained, and the calculated results after the experimental data are substituted into the functional expression are obtained, if the calculated results are in this region, It can be concluded that the consistency of the experimental battery is good.
【学位授予单位】：哈尔滨理工大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TM912

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