本文關(guān)鍵詞：FSEC電動賽車鋰離子動力電池狀態(tài)估計及均衡控制　出處：《哈爾濱工業(yè)大學(xué)》2016年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 鋰電池 SOC估算 均衡控制策略 反激式變壓器

【摘要】：隨著國家新能源產(chǎn)業(yè)的長足進步,中國大學(xué)生電動方程式大賽的參與度日益提升,對電動賽車的整體性能要求也不斷提升。而電池管理系統(tǒng)的發(fā)展滯后一直是電動汽車性能提升的瓶頸。通過對CSG-HRT15E用鈷酸鋰電池的綜合性能開展研究,設(shè)計一套適用于鈷酸鋰電池的管理系統(tǒng),實現(xiàn)對電池狀態(tài)實時監(jiān)測并在必要情況下介入電池組進行均衡管理,使電池組在實際工況中的可靠性得到有效提升。本文選用鈷酸鋰電池作為探究對象,圍繞電池外特性進行一定的研究,通過多次實驗以獲得電池開路電壓特性,在不同SOC(State of charge)階段下的回彈電壓的研究,辨識出了電池在不同SOC階段下的二階戴維南電池模型參數(shù)。并通過MATLAB仿真模擬電池在模擬實際工況下的電壓變化情況,驗證了擬合參數(shù)的可靠性。將無跡卡爾曼濾波與電池模型相匹配對電池SOC實施在線估算,為解決無跡卡爾曼濾波在運行過程中出現(xiàn)的協(xié)方差非正定問題,引入平方根無跡卡爾曼濾波以增強濾波器的強健性。在復(fù)雜工況下對電池SOC進行估算,結(jié)果表明,基于較高精度的電池模型,平方根無跡卡爾曼濾波的擬合精度較為理想,估算精度誤差小于1.5%。將反激式變壓器作為均衡拓撲核心結(jié)構(gòu),通過Or CAD軟件對均衡電路進行調(diào)試驗證。將電池SOC值確定為均衡判據(jù),根據(jù)電池實際工況制定電池組充放電后期均衡策略,利用MATLAB/Simulink對均衡系統(tǒng)及均衡策略進行仿真調(diào)試。對于多種均衡環(huán)境,以反激式變壓器為核心的均衡結(jié)構(gòu)結(jié)合基于電池確定的均衡判據(jù)能夠有效預(yù)防電池過度充放,提高電池工作效率。設(shè)計電池管理系統(tǒng)的軟硬件,選用HRT14YL01作為電池管理系統(tǒng)的主控模塊,該模塊主要完成對電池組總電壓、總電流的檢測,對電池SOC的估算以及各模塊的CAN通信。設(shè)計包含電池組溫度、單體電壓實時監(jiān)測以及電池組內(nèi)單體間均衡的從控模塊,同時完成對系統(tǒng)的軟件設(shè)計。
[Abstract]:With the rapid progress of the national new energy industry, the participation of Chinese university students in the electric equation competition is increasing day by day. The development of battery management system has been the bottleneck of the performance improvement of electric vehicles. Through the comprehensive performance of lithium cobalt battery used in CSG-HRT15E. Exhibition research. A management system suitable for lithium cobalt battery is designed to realize the real-time monitoring of the battery status and the balanced management of the battery pack if necessary. In order to improve the reliability of battery pack in actual working conditions, this paper selects lithium cobalt battery as the research object, carries on certain research around the battery external characteristic, obtains the battery open circuit voltage characteristic through many experiments. The study of springback voltage under different SOC(State of charge stages. The parameters of the second-order Davinan battery model under different SOC stages were identified, and the voltage variation of the battery under simulated conditions was simulated by MATLAB simulation. The reliability of fitting parameters is verified. The unscented Kalman filter is matched with the battery model to estimate the battery SOC online to solve the problem of non-positive covariance of unscented Kalman filter. Square root unscented Kalman filter is introduced to enhance the robustness of the filter. The battery SOC is estimated under complex conditions. The results show that the battery model is based on high accuracy. The square root unscented Kalman filter has an ideal fitting accuracy, and the error of estimation accuracy is less than 1.5. The flyback transformer is regarded as the core structure of the equalization topology. The equalization circuit is debugged and verified by or CAD software. The SOC value of the battery is determined as the equalization criterion. According to the actual condition of the battery, the later equalization strategy of the battery pack charge and discharge is worked out. The equalization system and strategy are simulated and debugged by MATLAB/Simulink. The equalization structure based on flyback transformer combined with the equalization criterion determined by battery can effectively prevent battery overcharging and improve battery working efficiency and design the hardware and software of battery management system. HRT14YL01 is selected as the main control module of the battery management system, which mainly completes the detection of the total voltage and current of the battery pack. The design includes battery temperature, cell voltage real-time monitoring and slave control module with equalization between the cells. At the same time, the software design of the system is completed.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2016
【分類號】：U469.72

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