發(fā)布時間：2018-09-12 20:45

【摘要】：鋰離子電池以其端電壓高、自放電率低、能量體積比大、無記憶效應(yīng)等優(yōu)良性能得到了廣泛應(yīng)用。本文主要研究鋰電池，重點研究鋰電池的工作狀態(tài)，并通過電池荷電狀態(tài)(SOC, State of Charge)來描述。電池荷電狀態(tài)是電池管理系統(tǒng)的重要指標，對電池管理系統(tǒng)有重要意義。根據(jù)電池荷電狀態(tài)采取調(diào)控措施，就可以在充放電過程中保護電池組，避免發(fā)生過充、過放而對電池造成損害。一般電池放電較為平穩(wěn)，電池荷電狀態(tài)的計算容易且準確，但在特殊環(huán)境下，如電流、環(huán)境溫度變化較大的場合，會使得電池工作過程中電壓波動劇烈，難以獲取準確的電池荷電狀態(tài)。目前為止電池荷電狀態(tài)的獲取已有多種估算方法，估算結(jié)果優(yōu)缺點各異。為提高估算準確性，估算過程中濾波方法的選取已成為當前電池荷電狀態(tài)研究的一個重要分支。 研究國內(nèi)外現(xiàn)狀可知，獲得準確的SOC表達式、建立合適的電池模型、選擇合適的SOC估算算法是準確預(yù)測電池荷電狀態(tài)的三個關(guān)鍵因素�；谝陨戏治觯疚尼槍OC估算的主要研究工作如下： ①研究一種動力學電池模型（KiBaM模型），該模型能形象描述電池的可用電荷和束縛電荷，通過對模型進行仿真，驗證電池容量的非線性特性和電池的自恢復效應(yīng)特性。 ②研究幾種常用的電池等效模型并進行對比，綜合考慮模型的計算量、精度、適用范圍后選取Thevenin模型。將Thevenin模型與上述KiBaM模型結(jié)合得到一種綜合Thevenin模型，通過對模型參數(shù)辨識后進行仿真，驗證模型精度。 ③研究電池剩余容量SOC常用的幾種估算方法及各自優(yōu)缺點，通過分析電池SOC的影響因素，分別研究環(huán)境溫度、充放電倍率、循環(huán)次數(shù)、電池內(nèi)阻與荷電狀態(tài)的關(guān)系，得到修正后的安時計量法。 ④研究無跡卡爾曼濾波（UKF）法，，及其核心思想UT變換，利用UKF濾波原理建立SOC估算模型，并在Matlab中仿真，以上述修正后的安時計量法估算結(jié)果為參考值，驗證UKF估算電池SOC的有效性。 本文以KiBaM模型結(jié)合Thevenin模型得到的綜合模型為基礎(chǔ)，利用UKF濾波算法估算電池SOC，以改進后的安時計量法為對比，仿真驗證UKF能有效估算電池SOC。
[Abstract]:Lithium ion batteries have been widely used for their high terminal voltage, low self-discharge rate, large energy volume ratio and no memory effect. In this paper, we mainly study lithium battery, especially the working state of lithium battery, and describe it by (SOC, State of Charge). The charged state of battery is an important index of battery management system, which is of great significance to battery management system. According to the charge state of the battery, the battery can be protected from overcharge and overdischarge during the charging and discharging process. In general, the discharge of the battery is relatively stable, and the calculation of the charged state of the battery is easy and accurate. However, in the special environment, such as the large change of the current and the ambient temperature, the voltage fluctuates sharply during the operation of the battery. It is difficult to obtain accurate battery charge state. Up to now, there are many methods to estimate the charged state of the battery, and the advantages and disadvantages of the estimation results are different. In order to improve the accuracy of estimation, the selection of filtering methods in the estimation process has become an important branch of the current battery charge state research. By studying the current situation at home and abroad, it is known that accurate SOC expression, establishment of appropriate battery model and selection of appropriate SOC estimation algorithm are three key factors to accurately predict the charged state of the battery. Based on the above analysis, the main research work of SOC estimation in this paper is as follows: 1 A dynamic battery model (KiBaM model), which can describe the available and bound charges of the battery vividly, is simulated. The nonlinear characteristics of the battery capacity and the characteristics of the self-recovery effect of the battery are verified. 2 several commonly used battery equivalent models are studied and compared. The Thevenin model is selected after considering the calculation amount and accuracy of the model. A comprehensive Thevenin model is obtained by combining the Thevenin model with the KiBaM model mentioned above. The model accuracy is verified by simulation after the model parameter identification. 3 several methods of estimating the battery residual capacity SOC and their respective advantages and disadvantages are studied. By analyzing the influence factors of battery SOC, studying the relationship between ambient temperature, charge / discharge rate, cycle times, battery resistance and charged state, the modified amperometric method is obtained. 4 the unscented Kalman filter (UKF) method is studied. And its core idea UT transform, using UKF filter principle to establish SOC estimation model, and simulation in Matlab, using the modified amperometric method as the reference value, to verify the effectiveness of UKF estimation of cell SOC. Based on the synthetic model of KiBaM model combined with Thevenin model, this paper uses UKF filter algorithm to estimate the SOC, of battery, compared with the improved amperometric method. The simulation results show that UKF can effectively estimate the SOC. of battery.
【學位授予單位】：重慶大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TM912

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本文編號：2240173