本文選題：不確定度　切入點(diǎn)：高斯過(guò)程　出處：《哈爾濱工業(yè)大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：電池管理系統(tǒng)作為電動(dòng)汽車的核心部件之一,它的性能直接關(guān)系到電動(dòng)汽車的使用安全與使用壽命。隨著電動(dòng)汽車的普及,電池管理系統(tǒng)的檢測(cè)成為當(dāng)前電動(dòng)汽車行業(yè)發(fā)展需要解決的問(wèn)題。動(dòng)力電池組荷電狀態(tài)SOC(state of charge)的估算精度成為電池管理系統(tǒng)檢測(cè)的核心內(nèi)容,本文主要針對(duì)電池管理系統(tǒng)SOC的檢測(cè),提出了評(píng)定動(dòng)力電池SOC測(cè)量不確定度的方法。本文通過(guò)分析鋰電池工作原理及充放電數(shù)據(jù)特點(diǎn),提出了基于高斯過(guò)程的鋰電池充放電數(shù)據(jù)處理方法,與最小二乘擬合和高斯擬合相比,充放電曲線的預(yù)測(cè)精度更高。針對(duì)標(biāo)準(zhǔn)QC/T897-2011《電動(dòng)汽車用電池管理系統(tǒng)技術(shù)條件》中SOC檢測(cè)項(xiàng)目規(guī)程,設(shè)計(jì)了電池電量測(cè)量不確定度評(píng)定的方案,根據(jù)電量測(cè)量的特點(diǎn),建立基于高斯過(guò)程的電池充放電模型,分析影響電量測(cè)量模型的不確定因素,確定電量測(cè)量模型中輸入量的概率密度函數(shù),利用蒙特卡洛法評(píng)定出不同充放電模式下電量測(cè)量的不確定度。分析電池老化對(duì)放電電量產(chǎn)生的影響,提出了利用高斯過(guò)程回歸算法估算電池健康狀態(tài)(SOH)的方法,采用不同的核函數(shù)進(jìn)行SOH估算,并根據(jù)SOH的估算方法提出容量估算的不確定性,進(jìn)行可用容量的測(cè)試,評(píng)定出可用容量不確定度。設(shè)計(jì)了基于虛擬儀器測(cè)量技術(shù)的SOC測(cè)試系統(tǒng),搭建了硬件測(cè)試平臺(tái),同時(shí)選用NI公司的Labwindows/CVI設(shè)計(jì)其軟件平臺(tái)。用該測(cè)試系統(tǒng)來(lái)完成對(duì)電池管理系統(tǒng)SOC估算精度的檢測(cè)實(shí)驗(yàn),SOC測(cè)試系統(tǒng)搭建完成后,進(jìn)行電池充放電數(shù)據(jù)的采樣,以及不同工況下的SOC測(cè)試,最后根據(jù)實(shí)驗(yàn)數(shù)據(jù)評(píng)定出SOC測(cè)量不確定度。
[Abstract]:As one of the core components of electric vehicles, battery management system has a direct bearing on the safety and service life of electric vehicles. The detection of battery management system has become a problem that needs to be solved in the development of electric vehicle industry. The estimation accuracy of SOC(state of charge status of power battery pack becomes the core content of battery management system detection. This paper presents a method to evaluate the uncertainty of power battery SOC measurement based on the detection of battery management system (SOC). The principle of lithium battery and the characteristics of charging and discharging data are analyzed in this paper. A charging and discharging data processing method for lithium battery based on Gao Si process is proposed, which is compared with least square fitting and Gao Si fitting. The prediction accuracy of charge-discharge curve is higher. According to the SOC test item specification in the standard QC/T897-2011 "Technical condition of Battery Management system for Electric vehicles", a scheme to evaluate the uncertainty of battery quantity measurement is designed, and according to the characteristics of electric quantity measurement, a method is designed to evaluate the uncertainty of battery quantity measurement. The battery charge and discharge model based on Gao Si process is established. The uncertain factors affecting the electric quantity measurement model are analyzed, and the probability density function of the input quantity in the electric quantity measurement model is determined. The uncertainty of electric quantity measurement under different charging and discharging modes was evaluated by Monte Carlo method. The effect of battery aging on discharge quantity was analyzed, and a method of estimating battery healthy state by Gao Si process regression algorithm was put forward. Different kernel functions are used to estimate SOH, and uncertainty of capacity estimation is proposed according to the estimation method of SOH. The uncertainty of available capacity is evaluated by testing the available capacity. A SOC test system based on virtual instrument measurement technology is designed. The hardware test platform is built, and the software platform is designed by Labwindows/CVI of NI Company. The battery charge and discharge data are sampled after the test system is built to test the accuracy of SOC estimation of battery management system. Finally, the uncertainty of SOC measurement is evaluated according to the experimental data.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TM912

【參考文獻(xiàn)】

相關(guān)期刊論文 前3條

1 盧文斌;海迪;;電池電量測(cè)量不確定度評(píng)定的方法研究[J];計(jì)量與測(cè)試技術(shù);2016年08期

2 孫斌;姚海濤;劉婷;;基于高斯過(guò)程回歸的短期風(fēng)速預(yù)測(cè)[J];中國(guó)電機(jī)工程學(xué)報(bào);2012年29期

3 沈峗;張麗清;;基于高斯過(guò)程模型的語(yǔ)音增強(qiáng)[J];計(jì)算機(jī)工程;2010年05期

相關(guān)碩士學(xué)位論文 前8條

1 李征;基于虛擬儀器的電源自動(dòng)校準(zhǔn)系統(tǒng)的研究[D];天津大學(xué);2015年

2 張正綱;直流大電流測(cè)量技術(shù)研究[D];華北電力大學(xué);2014年

3 李曉宇;電動(dòng)汽車電池管理系統(tǒng)測(cè)試平臺(tái)的研制[D];哈爾濱工業(yè)大學(xué);2013年

4 仝如松;基于蒙特卡洛法計(jì)量校準(zhǔn)不確定度評(píng)定方法的研究[D];河北大學(xué);2013年

5 薛輝;動(dòng)力鋰離子電池組SOH估計(jì)方法研究[D];吉林大學(xué);2013年

6 孟學(xué)東;電池管理系統(tǒng)測(cè)試平臺(tái)的研究[D];北京交通大學(xué);2013年

7 田芳寧;實(shí)驗(yàn)室認(rèn)可中的測(cè)量不確定度評(píng)定[D];合肥工業(yè)大學(xué);2012年

8 楊春雷;電動(dòng)汽車電池管理系統(tǒng)關(guān)鍵技術(shù)的研究[D];哈爾濱工業(yè)大學(xué);2011年

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本文編號(hào)：1593148