【摘要】：環(huán)境污染和能源危機(jī),使人類迫切需要找一種新能源汽車來替代傳統(tǒng)機(jī)動(dòng)車。電動(dòng)汽車在電池能量轉(zhuǎn)換和尾氣排放等方面具有很大優(yōu)勢(shì),電動(dòng)汽車成為人們替代傳統(tǒng)機(jī)動(dòng)車首選,而鋰電池管理制約了電動(dòng)汽車普及和推廣。 本文對(duì)鋰離子電池種類進(jìn)行分析比較,最終選擇磷酸鐵鋰電池作為電動(dòng)汽車用鋰電池管理研究對(duì)象。本文首先介紹了國(guó)內(nèi)外電動(dòng)汽車產(chǎn)業(yè)發(fā)展現(xiàn)狀和電動(dòng)汽車在推廣普及中遇到一些難題,鋰電池管理技術(shù)是電動(dòng)汽車發(fā)展遇到最為突出的難點(diǎn),隨后對(duì)鋰電池管理技術(shù)難點(diǎn)進(jìn)行分析研究。 鋰電池剩余電量(SOC)估算精度和鋰電池組單體電池之間不一致性是鋰電池管理難點(diǎn)。通過對(duì)磷酸鐵鋰電池進(jìn)行大量充放電試驗(yàn),得到電池關(guān)鍵性能基本特性參數(shù),其中基本特性參數(shù)包括充放電特性、倍率特性、溫度特性以及靜置特性。本文在對(duì)電動(dòng)汽車用鋰電池高效運(yùn)行管理進(jìn)行設(shè)計(jì)研究,提出了基于擴(kuò)展卡爾曼濾波算法(EKF)復(fù)合算法的SOC估算和基于GS7708芯片主動(dòng)均衡控制策略,是本文重點(diǎn)研究部分。 在電動(dòng)汽車使用過程中,鋰電池組沒有得到有效管理,不能實(shí)時(shí)估算鋰電池工作狀態(tài),降低鋰電池整體性能,導(dǎo)致汽車?yán)m(xù)駛里程短以及使用成本激增。本文結(jié)合安時(shí)計(jì)量法、開路電壓法以及擴(kuò)展卡爾曼濾波算法,提出了基于EKF復(fù)合算法的SOC估算,并對(duì)復(fù)合算法建立Thevenin電池模型,采用了MATLAB仿真驗(yàn)證了基于EKF復(fù)合算法精度及可行性。另外針對(duì)單體鋰電池在循環(huán)工作一段時(shí)間后,存在不一致性,容易導(dǎo)致鋰電池過充過放,提出了基于GS7708芯片電感主動(dòng)均衡控制策略以及全局最優(yōu)化算法,設(shè)計(jì)了相關(guān)主動(dòng)均衡控制電路。此外還對(duì)磷酸鐵鋰電池電池組進(jìn)行了主動(dòng)均衡實(shí)驗(yàn),比較均衡前后電壓變化,驗(yàn)證本文主動(dòng)均衡策略的可行性。通過提高了SOC估算準(zhǔn)確性以及減少鋰電池主動(dòng)均衡時(shí)間,實(shí)現(xiàn)了對(duì)鋰電池有效管理。 在硬件上,設(shè)計(jì)了基于STM32F103VBT6芯片的電動(dòng)汽車用鋰電池組整體硬件電路,主要包括CPU最小系統(tǒng)、電源模塊、EEPROM、RS485通信接口電路、人機(jī)界面以及鋰電池組充放電電壓電流信號(hào)采樣,并采用專門電池監(jiān)控芯片AD7280A進(jìn)行信號(hào)數(shù)據(jù)采樣。軟件設(shè)計(jì)上對(duì)STM32的Keil uVision4開發(fā)環(huán)境及功能作了簡(jiǎn)要概述,在硬件電路基礎(chǔ)上,完成鋰電池充放電管理系統(tǒng)的軟件程序設(shè)計(jì),并設(shè)計(jì)了相應(yīng)的程序和電路流程圖。最后,對(duì)本文進(jìn)行了一些總結(jié)和展望。
[Abstract]:Because of environmental pollution and energy crisis, it is urgent to find a new energy vehicle to replace the traditional motor vehicle. Electric vehicles have great advantages in battery energy conversion and exhaust emissions. Electric vehicles have become the first choice to replace traditional vehicles, while lithium battery management has restricted the popularization and promotion of electric vehicles. In this paper, the types of lithium-ion batteries are analyzed and compared. Finally, the lithium-iron phosphate battery is selected as the research object of the management of lithium-ion batteries for electric vehicles. This paper first introduces the development of electric vehicle industry at home and abroad and some difficult problems encountered in the promotion and popularization of electric vehicle. Lithium battery management technology is the most prominent difficulty in the development of electric vehicle. Then the technical difficulties of lithium battery management are analyzed and studied. The precision of (SOC) estimation and the inconsistency between lithium battery and lithium battery are difficult to manage lithium battery. The basic performance parameters of lithium ferric phosphate battery were obtained by a large number of charge-discharge tests, including charge-discharge characteristics, rate-doubling characteristics, temperature characteristics and static characteristics. In this paper, the efficient operation management of lithium battery for electric vehicle is designed and studied, and the SOC estimation based on extended Kalman filter algorithm (EKF) compound algorithm and the active equalization control strategy based on GS7708 chip are put forward, which is the focus of this paper. In the process of using electric vehicle, lithium battery pack is not managed effectively, can not estimate the working state of lithium battery in real time, reduces the overall performance of lithium battery, and results in the short driving mileage and the rapid increase in using cost. In this paper, combined with amperometric method, open circuit voltage method and extended Kalman filter (EKF) algorithm, the SOC estimation based on EKF composite algorithm is proposed, and the Thevenin battery model is established for the composite algorithm. The accuracy and feasibility of the composite algorithm based on EKF are verified by MATLAB simulation. In addition, aiming at the inconsistency of lithium battery after a period of cycle operation, which can easily lead to overcharging and discharge of lithium battery, the active equalization control strategy and global optimization algorithm based on GS7708 chip inductor are proposed. An active equalization control circuit is designed. In addition, the active equalization experiment of lithium iron phosphate battery pack is carried out to compare the voltage change before and after the equalization, and verify the feasibility of the active equalization strategy in this paper. By improving the accuracy of SOC estimation and reducing the active equalization time of lithium batteries, the effective management of lithium batteries is realized. In hardware, the whole hardware circuit of lithium-ion battery pack for electric vehicle based on STM32F103VBT6 chip is designed, which mainly includes CPU minimum system, power module, EEPROM,RS485 communication interface circuit, man-machine interface, charge-discharge voltage and current signal sampling of lithium battery pack. The special battery monitor chip AD7280A is used to sample the signal data. In the software design, the development environment and function of Keil uVision4 of STM32 are briefly summarized. On the basis of hardware circuit, the software program design of charge and discharge management system for lithium battery is completed, and the corresponding program and circuit flow chart are designed. Finally, this paper makes some summary and prospect.
【學(xué)位授予單位】：安徽理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TM912

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