本文選題：鋰動力電池　切入點：SOC預測　出處：《哈爾濱理工大學》2015年碩士論文

【摘要】：鋰動力電池，以其比容量高和長循環(huán)壽命，在動力電池領域作為技術革新的重要支持。盡管制造工藝以及使用管理技術不斷提高，在實際的使用中，，都需要將各單體電池，通過串聯(lián)或并聯(lián)的方式成組使用，而在長期的使用后，電池組都會出現(xiàn)性能大幅衰減的現(xiàn)象。經(jīng)研究表明，這是由于構(gòu)成電池組的單體電池在一致性上出現(xiàn)了明顯的差異。因此，為了讓動力電池組在長期使用過程中，都能一直保持有較高的性能，延長整個電池組的使用壽命，就需要對組內(nèi)單體電池的一致性有較好的判斷，以便于電池管理系統(tǒng)(BMS)以及用戶對其進行及時維護。 對動力電池的一致性概念進行了研究，經(jīng)過大量的實驗，并對實驗數(shù)據(jù)進行分析發(fā)現(xiàn)在多個性能參數(shù)中，電池的荷電狀態(tài)(SOC)和動力電池的工作電壓(CCV)能夠全面的顯示電池當前的狀態(tài)，同時也是電池動態(tài)特性的集中體現(xiàn)，可以作為評價電池一致性評價的技術指標。 本文建立并改進了動力電池的等效模型，在模型建立過程中，引入了權值向量A(m)，來更好地反映這一差異的存在。文中采用平方根容積卡爾曼濾波法，結(jié)合強跟蹤濾波理論(SCKF-STF)對SOC進行預測，給出了預測結(jié)果和誤差分析，在算法的前端設計并加入了多重濾波算法，對混入的噪聲進行處理，并結(jié)合針對一致性差異的等效模型，進一步提高算法的預測精度，同時加入了仿真分析對方案的可行性進行了驗證。 文中采用數(shù)理統(tǒng)計的F分布概率密度函數(shù)實現(xiàn)用SOC和工作電壓對一致性評價的綜合分析。根據(jù)動力電池的實際參數(shù)，給出相應對概率密度函數(shù)的描述，進而得到概率密度曲線，通過設定一致性預警閾值，得出符合預期的結(jié)果區(qū)域，將實驗數(shù)據(jù)代入函數(shù)表達式后得出的計算結(jié)果，如果計算結(jié)果在該區(qū)域中，則可以得出該組實驗電池的一致性較好的結(jié)論。
[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.
【學位授予單位】：哈爾濱理工大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TM912

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