【摘要】：電動(dòng)汽車產(chǎn)業(yè)作為我國(guó)重點(diǎn)發(fā)展的戰(zhàn)略性新興產(chǎn)業(yè)之一,是我國(guó)應(yīng)對(duì)能源和環(huán)境挑戰(zhàn)、推動(dòng)傳統(tǒng)汽車產(chǎn)業(yè)轉(zhuǎn)型升級(jí)的緊迫任務(wù),也是加快經(jīng)濟(jì)發(fā)展方式轉(zhuǎn)變的戰(zhàn)略舉措。本課題針對(duì)目前電動(dòng)汽車電池管理系統(tǒng)發(fā)展的主要問(wèn)題,開展動(dòng)力電池荷電狀態(tài)估計(jì)技術(shù)及均衡技術(shù)的研究。鋰離子動(dòng)力電池在電動(dòng)車輛上應(yīng)用時(shí),受工況、環(huán)境等隨機(jī)因素影響,SOC具有很強(qiáng)的時(shí)變非線性,對(duì)電動(dòng)車輛動(dòng)力電池SOC估計(jì)進(jìn)行研究具有理論意義和應(yīng)用價(jià)值。本文對(duì)SOC估計(jì)的研究如下所述。在模型參數(shù)已知的條件下,提出基于SOH及模型離線參數(shù)分段矯正的鋰電池SOC估計(jì)方法,分段矯正方法研究思路:安時(shí)積分法是目前工程中常用的SOC估計(jì)方法,在應(yīng)用過(guò)程中存在的難點(diǎn)是積分過(guò)程中累積誤差的消除,本文首先利用電池健康狀態(tài)估算出電池當(dāng)前時(shí)刻的實(shí)際可用容量,作為安時(shí)積分法中的除數(shù)項(xiàng),對(duì)SOC估計(jì)值進(jìn)行矯正;其次,利用模型離線數(shù)據(jù)對(duì)安時(shí)積分法中的累積誤差進(jìn)行分段消除。仿真結(jié)果表明,本文所提方法比傳統(tǒng)的安時(shí)積分法具有更高的精度,能夠較好的消除累積誤差。在模型參數(shù)未知的條件下,提出基于最小二乘法及卡爾曼濾波法的聯(lián)合估算方法。聯(lián)合算法研究思路:首先根據(jù)動(dòng)力電池在充放電過(guò)程中端電壓的動(dòng)態(tài)響應(yīng),采用二階RC環(huán)路模型作為動(dòng)力電池等效模型;隨后,在此模型基礎(chǔ)上,利用帶遺忘因子的最小二乘法和自適應(yīng)無(wú)跡卡爾曼濾波法對(duì)動(dòng)力電池SOC進(jìn)行聯(lián)合估計(jì)。仿真試驗(yàn)表明,本文所提聯(lián)合估計(jì)算法比單一的自適應(yīng)無(wú)跡卡爾曼濾波法具有更高的精度和對(duì)初值誤差的收斂性。由于動(dòng)力電池組各單體電池的不一致性,動(dòng)力電池組的循環(huán)壽命成為制約當(dāng)前動(dòng)力電池發(fā)展的重要因素。為了消除不一致性對(duì)串聯(lián)動(dòng)力電池組循環(huán)壽命的影響,利用電感儲(chǔ)能原理,基于均衡路徑與均衡閾值的動(dòng)態(tài)調(diào)整,本文提出了兩種新型均衡電路。兩種新型均衡電路分別稱為基于多準(zhǔn)則限定的電池組均衡電路和基于分層策略的電池組均衡電路,兩種均衡電路均由若干均衡子電路組成�；诙鄿�(zhǔn)則限定的電池組均衡電路可用于整組電池單體個(gè)數(shù)較少時(shí)的均衡;當(dāng)電池組單體數(shù)量較多時(shí),為減小均衡路徑,可以考慮采用基于分層策略的均衡電路。仿真及實(shí)驗(yàn)結(jié)果表明,本文所提均衡電路結(jié)構(gòu)簡(jiǎn)單,均衡速度快,均衡電流大,具有出色的均衡性能。
[Abstract]:As one of the strategic emerging industries in China, the electric vehicle industry is an urgent task to meet the challenges of energy and environment and to promote the transformation and upgrading of the traditional automobile industry. It is also a strategic measure to speed up the transformation of the mode of economic development. Aiming at the main problems in the development of battery management system for electric vehicles at present, the research on the technology of state estimation and equalization for power batteries is carried out in this paper. When lithium-ion power battery is applied in electric vehicle, it is affected by random factors such as working condition and environment, and SOC has strong time-varying nonlinearity. It is of theoretical significance and application value to study SOC estimation of electric vehicle power battery. In this paper, the study of SOC estimation is described below. Under the condition that the model parameters are known, the SOC estimation method of lithium battery based on SOH and off-line parameter correction of the model is proposed. The research idea of piecewise correction method is as follows: the ampere-time integration method is the commonly used SOC estimation method in engineering at present. The difficulty in application is the elimination of accumulated errors in the integration process. Firstly, the actual available capacity of the current time of the battery is estimated by using the healthy state of the battery, which is used as the divisor in the ampere-time integration method to correct the SOC estimation. Secondly, the cumulative error is eliminated by using the off-line data of the model. The simulation results show that the method proposed in this paper has higher accuracy and better elimination of cumulative error than the traditional method of ampere-time integration. Under the condition that the model parameters are unknown, a joint estimation method based on least square method and Kalman filter method is proposed. According to the dynamic response of the terminal voltage in the process of charging and discharging, the second-order RC loop model is used as the equivalent model of the battery. On the basis of this model, the least square method with forgetting factor and the adaptive unscented Kalman filter method are used to jointly estimate the power cell SOC. Simulation results show that the proposed joint estimation algorithm has higher accuracy and convergence to the initial value error than the single adaptive unscented Kalman filter method. The cycle life of the power battery pack has become an important factor restricting the development of the power battery because of the inconsistencies of the individual cells of the power battery pack. In order to eliminate the influence of inconsistency on cycle life of series power batteries, two new equalization circuits are proposed in this paper, based on the dynamic adjustment of equilibrium path and equalization threshold based on the principle of inductor energy storage. The two new equalization circuits are called battery pack equalization circuit based on multi-criteria restriction and battery pack equalization circuit based on hierarchical strategy respectively. The two equalization circuits are composed of several equalizer sub-circuits. The equalization circuit based on multi-criteria can be used to equalize the whole battery when the number of cells is small, and when the number of cells is large, the equalization circuit based on hierarchical strategy can be considered to reduce the equalization path. The simulation and experimental results show that the proposed equalization circuit has the advantages of simple structure, fast equalization speed, large equalization current and excellent equalization performance.
【學(xué)位授予單位】：華南理工大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2016
【分類號(hào)】：U469.72

【相似文獻(xiàn)】

中國(guó)期刊全文數(shù)據(jù)庫(kù) 前6條

1 聶永萍;胡昌恩;;寬帶多入多出系統(tǒng)的迭代均衡技術(shù)[J];重慶工商大學(xué)學(xué)報(bào)(自然科學(xué)版);2005年06期

2 黃海元 ,方正;美國(guó)的均衡技術(shù)倡議和常規(guī)防御倡議[J];系統(tǒng)工程與電子技術(shù);1988年04期

3 肖長(zhǎng)期;;無(wú)線通信信道均衡技術(shù)研究[J];科技創(chuàng)新與應(yīng)用;2014年14期

4 林虎;;最新的高速信號(hào)虛擬探測(cè)和均衡技術(shù)[J];國(guó)外電子測(cè)量技術(shù);2007年09期

5 郭經(jīng)紅,張官元;基于多相分解的盲信道辨識(shí)和均衡技術(shù)[J];電力系統(tǒng)通信;2003年02期

6 ;[J];;年期

中國(guó)重要會(huì)議論文全文數(shù)據(jù)庫(kù) 前2條

1 馬俊;;直接數(shù)字化X攝影中組織均衡技術(shù)的實(shí)際應(yīng)用[A];2009中華醫(yī)學(xué)會(huì)影像技術(shù)分會(huì)第十七次全國(guó)學(xué)術(shù)大會(huì)論文集[C];2009年

2 彭海民;;基于電光濾波的LiNbO_3在動(dòng)態(tài)增益均衡技術(shù)中的應(yīng)用[A];武漢市第二屆學(xué)術(shù)年會(huì)、通信學(xué)會(huì)2006年學(xué)術(shù)年會(huì)論文集[C];2006年

中國(guó)博士學(xué)位論文全文數(shù)據(jù)庫(kù) 前2條

1 郭向偉;電動(dòng)汽車電池荷電狀態(tài)估計(jì)及均衡技術(shù)研究[D];華南理工大學(xué);2016年

2 唐先鋒;高速光纖通信中的幾種均衡技術(shù)研究[D];北京郵電大學(xué);2011年

中國(guó)碩士學(xué)位論文全文數(shù)據(jù)庫(kù) 前10條

1 劉茂才;室內(nèi)可見(jiàn)光通信系統(tǒng)均衡技術(shù)研究[D];哈爾濱工業(yè)大學(xué);2015年

2 路良友;Turbo均衡技術(shù)研究[D];河南工業(yè)大學(xué);2015年

3 張琳;分層調(diào)制系統(tǒng)中的迭代均衡技術(shù)的研究[D];電子科技大學(xué);2010年

4 丁博;不同載波體制下均衡技術(shù)的研究[D];哈爾濱工業(yè)大學(xué);2010年

5 鐘蕓;Turbo均衡技術(shù)的研究[D];南京航空航天大學(xué);2004年

6 潘玉竹;高速背板互連均衡技術(shù)的研究[D];南昌大學(xué);2009年

7 魏?jiǎn)⒚?無(wú)線通信中的Turbo碼及Turbo均衡技術(shù)研究[D];電子科技大學(xué);2008年

8 陸峗峗;LDPC碼及其反饋迭代均衡技術(shù)的研究[D];南京航空航天大學(xué);2008年

9 高浩;寬帶數(shù)字陣列中通道均衡技術(shù)的研究及應(yīng)用[D];安徽大學(xué);2013年

10 吳瑩;高效LDPC編譯碼及其組合均衡技術(shù)在無(wú)線通信中的研究[D];南京航空航天大學(xué);2007年

，

本文編號(hào)：2460680