本文選題：新能源 + 電動汽車��； 參考：《西安工業(yè)大學(xué)》2014年碩士論文

【摘要】：蓄電池作為電動汽車的主要動力源,其儲能能力的不足一直是制約電動汽車發(fā)展的重要因素,解決這個問題,除了不斷研制出存儲容量大的蓄電池以外,如何最大限度的發(fā)揮現(xiàn)有蓄電池的使用效率也是解決這個問題關(guān)鍵技術(shù)之一。 為了最大限度地發(fā)揮蓄電池的使用效率,現(xiàn)階段的研究一般都是從以下幾個方面開展的：一、加強保護,防止各種意外對蓄電池造成傷害；二、為蓄電池創(chuàng)造一種合適的工作環(huán)境；三、對串聯(lián)的蓄電池組,加強充電過程中的均衡度控制,以及及早發(fā)現(xiàn)群體中存在的受損個體并將其更換;四、對蓄電池的剩余電量(SOC)的準確估測,不僅為蓄電池進行合理的充放電,而且也為電動汽車整車的能量管理提供了必要的依據(jù)。將這些功能集中在一起,就組成了現(xiàn)階段的蓄電池管理系統(tǒng)(BMS),這些功能都是通過VB軟件控制實現(xiàn)的,它能最終實現(xiàn)發(fā)揮蓄電池的使用效率和壽命、增加電動汽車續(xù)駛里程等功效。 為了實現(xiàn)上述功能,本項目設(shè)計了一個蓄電池管理系統(tǒng),該系統(tǒng)由信號處理模塊、輸出驅(qū)動模塊、工業(yè)A/D采集卡、I/0接口卡和一臺工業(yè)計算機組成。信號處理模塊將采集到的蓄電池電壓、電流、溫度等數(shù)據(jù)濾波放大后輸入到A/D卡,經(jīng)計算機采集以后,通過計算,決定是否需要實現(xiàn)相應(yīng)的控制以及完成SOC的計算,控制信號的輸出經(jīng)輸出驅(qū)動模塊作用到對應(yīng)的設(shè)備,實現(xiàn)各種保護功能；對于SOC的計算,為了提高其估算精度,嘗試利用Matlab-Simulink工具,建立蓄電池放電整體模型,分別將卡爾曼濾波法和安時積分法與電池模型有效結(jié)合,實現(xiàn)對蓄電池SOC的估測的仿真。同時,利用蓄電池端電壓與SOC的關(guān)系,得到實際結(jié)果。 實驗結(jié)果表明,本設(shè)計中的蓄電池管理系統(tǒng)基本實現(xiàn)了蓄電池最大化利用,保證了蓄電池安全可靠的運行。通過對比研究,我們發(fā)現(xiàn)利用卡爾曼濾波Matlab仿真得到的曲線比安時法計算得到的曲線更接近實際測量結(jié)果。從而驗證了卡爾曼濾波法相比于其他傳統(tǒng)方法更能有效準確的對蓄電池sOC進行估測。
[Abstract]:As the main power source of the electric vehicle, the lack of energy storage capacity has been an important factor restricting the development of electric vehicles. In addition to developing the storage battery with large storage capacity, how to maximize the efficiency of the existing storage battery is also one of the key technologies to solve this problem.
In order to maximize the use efficiency of the battery, the research at the present stage is generally carried out from the following aspects: first, to strengthen the protection, prevent all kinds of accidents from causing damage to the battery; two, to create a suitable working environment for the battery; three, to the battery group in series, to strengthen the balance control during the charging process. Four, the accurate estimation of the residual quantity of the battery (SOC) not only provides a reasonable charge and discharge for the battery, but also provides the necessary basis for the energy management of the electric vehicle. The current storage battery management is formed by concentrating these functions together. System (BMS), these functions are achieved through the control of the VB software. It can eventually realize the efficiency and life of the battery, and increase the driving range of the electric vehicle.
In order to realize the above function, this project has designed a battery management system, which consists of signal processing module, output driver module, industrial A/D acquisition card, I/0 interface card and an industrial computer. The signal processing module amplifies the data filter of accumulator battery voltage, current, temperature and so on into the A/D card and passes through the computer. After collecting, through calculation, it decides whether to realize the corresponding control and to complete the calculation of SOC. The output of the control signal is acted by the output drive module to the corresponding equipment to realize various protection functions. For the calculation of SOC, in order to improve its estimation accuracy, the Matlab-Simulink tool is used to establish the whole model of the battery discharge. The Calman filter method and the time integration method and the battery model are effectively combined to achieve the simulation of the battery SOC estimation. At the same time, the actual results are obtained by using the relationship between the terminal voltage of the battery and the SOC.
The experimental results show that the battery management system in this design basically realizes the maximum utilization of the battery and ensures the safe and reliable operation of the battery. Through the comparative study, we find that the curve obtained by the Calman filter Matlab simulation is more close to the actual measurement result than the curve calculated by the time method. Thus, Calman has been verified. Compared with other traditional methods, the filtering method is more effective and accurate for battery sOC estimation.
【學(xué)位授予單位】：西安工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：U469.72;TM912

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本文編號：1952031