锂动力电池动态一致性评价方法的研究摘要锂动力电池,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值向量()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。
关键词锂动力电池;SOC预测;一致性评价;统计学原理- I -Evaluation on the Dynamic Consistency of Li-IonPower BatteryAbstractLi-ion power battery has been the solid foundation for technology innovation within power battery field with its unique discharge specific capacity and long cycle life. Cell batteries should be connected in series to be applied for large appliance, though the rapid development in crafts and management. However, the general performance of the formed battery pack may suffer a apparent decay after a long term application, due to the deterioration in the consistency of the battery based on large quantities of research. A better evaluation on the consistency of battery is the very basis to keep better performance of the battery, to extend the cycle life, as well as to give advantage to battery management system (BMS) with maintenance.Various experiments are conducted to get to essence of consistency of battery, as to analyze the performance index of power battery for the typical ones for the current state of battery in this paper. State of charge, as well as SOC and closed circuit voltage (CCV) are selected with the research results for the performance index of consistency.The equivalent circuit model is established and improved with weightA m is involved to embrace the discrepancy in the very battery of the victor ()formed battery pack in the paper. Square-Cubature-Kalman-Filter, combined with Strong-Tracking Filter (SCKF-STF) algorithm is involved for SOC prediction with corresponding simulation and error analysis. To obtain SOC prediction result with higher precision, multiple filter algorithm is designed ahead of the SCKF-STF algorithm to tackle with the involved noise with input data. The comparison simulation of SOC prediction is conducted with optimized SCKF-STF algorithm and improved model. The corresponding simulation result and error analysis is conducted with the single SCKF-STF for the adtantage of the optimized algorithm.- II -The probability density function of F-distribution with principle of statics is involved to obtain the evaluation on consistency of battery with SOC and CCV as performance index. The corresponding description for probability density function is deducted with actual index of experimented battery, as well as the probability density curve. A pre-designed trust zone can be settled on the curve with designed warning value. The zone of which is applied to make comparison with the result from deducted function with experiment data to evaluate the general consistency of the experimented battery.Keywords Li-ion power battery, Prediction for SOC, Evaluation of the consistency of battery, Principle of statistics- III -目录摘要 (I)Abstract (II)第1章绪论 (1)1.1 课题研究的目的及意义 (1)1.2 SOC预测方法的现状研究 (2)1.2.1 SOC预测方法的发展趋势 (3)1.2.2 常用SOC预测的算法综述 (3)1.3 锂动力电池一致性评价的现状研究 (5)1.3.1 一致性评价的研究方向 (5)1.3.2 基于参数的评价方法综述 (5)1.4 本文主要研究内容 (6)第2章锂动力电池不一致性的研究 (8)2.1 电池一致性的概念阐述 (8)2.2 不一致性的产生机理 (8)2.2.1 分析生产和储存环节 (8)2.2.2 分析成组使用环节 (10)2.3 判定电池不一致的条件 (11)2.3.1 性能参数分析 (11)2.3.2 状态参数分析 (12)2.4 电池不一致的危害 (12)2.5 改善电池不一致的方法 (13)2.5.1 改善分选环节 (13)2.5.2 改善电池均衡环节 (14)2.5.3 其它方法 (15)2.6 本章小结 (15)第3章锂动力电池SOC预测算法的研究与改进 (16)3.1 SOC预测的影响因素分析 (16)3.2 电池等效模型的建立 (17)3.2.1 等效模型的数学推导 (18)3.2.2 针对一致性评价的模型修正 (21)3.3 SCKF-STF算法的研究与仿真 (22)3.3.1 强跟踪滤波算法研究 (23)3.3.2 动力电池SOC的预测 (24)3.3.3 结果仿真与误差分析 (27)3.4 基于参数和模型修正的电池SOC预测及仿真 (29)3.4.1 性能参数修正 (29)3.4.2 对SCKF-STF预测算法的优化 (30)3.4.3 算法的仿真分析 (34)3.5 本章小结 (35)第4章基于F分布的动力电池动态一致性评价 (36)4.1 常用动态一致性评价方法的分析 (36)4.1.1 工作电压标准差评价法 (36)4.1.2 SOC离散度评价法 (37)4.2 基于F分布的动态一致性评价方法 (39)4.2.1 工作电压离散度的统计学分析 (39)4.2.2 电池不一致性的数学描述 (40)4.2.3 基于F分布的方法描述与数学推导 (41)4.3 电池一致性评价方法的验证 (44)4.4 本章小结 (46)结论 (47)参考文献 (48)攻读学位期间发表的学术论文 (53)致谢 (54)第1章绪论近年来尽管行业发展的速度逐年攀升,但快速发展所带来的环境破坏与严重污染不得不让人们关注的重点转向资源的可持续利用和能源的清洁可再生方面[1]。