【摘要】：電動汽車產(chǎn)業(yè)作為我國重點(diǎn)發(fā)展的戰(zhàn)略性新興產(chǎn)業(yè)之一,是我國應(yīng)對能源和環(huán)境挑戰(zhàn)、推動傳統(tǒng)汽車產(chǎn)業(yè)轉(zhuǎn)型升級的緊迫任務(wù),也是加快經(jīng)濟(jì)發(fā)展方式轉(zhuǎn)變的戰(zhàn)略舉措。本課題針對目前電動汽車電池管理系統(tǒng)發(fā)展的主要問題,開展動力電池荷電狀態(tài)估計(jì)技術(shù)及均衡技術(shù)的研究。鋰離子動力電池在電動車輛上應(yīng)用時,受工況、環(huán)境等隨機(jī)因素影響,SOC具有很強(qiáng)的時變非線性,對電動車輛動力電池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:安時積分法是目前工程中常用的SOC估計(jì)方法,在應(yīng)用過程中存在的難點(diǎn)是積分過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)前時刻的實(shí)際可用容量,作為安時積分法中的除數(shù)項(xiàng),對SOC估計(jì)值進(jìn)行矯正;其次,利用模型離線數(shù)據(jù)對安時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)動力電池在充放電過程中端電壓的動態(tài)響應(yīng),采用二階RC環(huán)路模型作為動力電池等效模型;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)無跡卡爾曼濾波法對動力電池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)無跡卡爾曼濾波法具有更高的精度和對初值誤差的收斂性。由于動力電池組各單體電池的不一致性,動力電池組的循環(huán)壽命成為制約當(dāng)前動力電池發(fā)展的重要因素。為了消除不一致性對串聯(lián)動力電池組循環(huán)壽命的影響,利用電感儲能原理,基于均衡路徑與均衡閾值的動態(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。基于多準(zhǔn)則限定的電池組均衡電路可用于整組電池單體個數(shù)較少時的均衡;當(dāng)電池組單體數(shù)量較多時,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)位級別】：博士
【學(xué)位授予年份】：2016
【分類號】：U469.72

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