發(fā)布時(shí)間：2018-03-27 18:45

  本文選題：退化數(shù)據(jù)　切入點(diǎn)：鋰離子電池　出處：《西安理工大學(xué)》2017年碩士論文

【摘要】：隨著衛(wèi)星技術(shù)的發(fā)展,衛(wèi)星載體中的許多關(guān)鍵部件變得越來越復(fù)雜。在設(shè)備運(yùn)行的環(huán)境中,由于復(fù)雜性和多種不確定因素的作用,其功能與性能都將不可避免的發(fā)生退化,進(jìn)而造成設(shè)備的最終失效。假如,能夠在部件開始出現(xiàn)性能退化的時(shí)候?qū)ζ溥M(jìn)行剩余使用壽命(Remaining Useful Life, RUL)估計(jì),并在此基礎(chǔ)上確定對(duì)設(shè)備的最佳維修時(shí)機(jī),可以有效地避免可能會(huì)發(fā)生的重大故障,從而達(dá)到降低設(shè)備運(yùn)行的風(fēng)險(xiǎn)的目的,這對(duì)于提高設(shè)備運(yùn)行的安全性和可靠性具有重要意義。本課題是來自XXXX測(cè)控中心的委托項(xiàng)目,是該項(xiàng)目的子課題,以衛(wèi)星的關(guān)鍵部件——鋰離子電池為對(duì)象研究其剩余使用壽命預(yù)測(cè)方法。首先,本文在對(duì)鋰離子電池(Lithium Ion Battery,LIB)工作原理和失效機(jī)理清楚認(rèn)識(shí)的基礎(chǔ)上,針對(duì)衛(wèi)星鋰離子電池在軌實(shí)際運(yùn)行失效數(shù)據(jù)難以獲得的問題,采用了美國航空航天實(shí)驗(yàn)室(National Aeronautics and Space Administration, NASA)對(duì)外公布的鋰離子試驗(yàn)退化數(shù)據(jù)替代失效數(shù)據(jù),并分析了試驗(yàn)數(shù)據(jù)的統(tǒng)計(jì)特性,從而采用相應(yīng)的算法進(jìn)行剩余使用壽命估計(jì)。其次,針對(duì)單一算法存在一些不可避免的缺陷,如,擴(kuò)展卡爾曼濾波、粒子濾波強(qiáng)烈地依賴于鋰離子電池的模型,而自回歸方法只與樣本數(shù)據(jù)有關(guān)。不管是依賴模型還是只依賴數(shù)據(jù)的統(tǒng)計(jì)特性,都會(huì)對(duì)估計(jì)的結(jié)果產(chǎn)生影響,因此提出了一種混合模型算法,該模型既依賴于數(shù)據(jù)的統(tǒng)計(jì)特性,又依賴于研究對(duì)象的模型,取其各自算法的優(yōu)勢(shì),使混合模型算法的預(yù)測(cè)性能得到改善。最后,借助一些算法的性能評(píng)估指標(biāo),量化地分析了本文中使用的RUL預(yù)測(cè)算法的性能。通過量化指標(biāo),更進(jìn)一步地說明了,提出的混合模型的預(yù)測(cè)的算法性能相對(duì)于單一算法的預(yù)測(cè)性能有所提高。鋰離子電池剩余使用壽命預(yù)測(cè)問題對(duì)許多領(lǐng)域的應(yīng)用都至關(guān)重要,準(zhǔn)確實(shí)現(xiàn)RUL估計(jì)對(duì)視情維修和提高系統(tǒng)可靠性具有重要意義。本文中的預(yù)測(cè)方法都已用MATLAB仿真實(shí)現(xiàn),驗(yàn)證了算法的有效性。
[Abstract]:With the development of satellite technology, many key components in satellite carrier become more and more complex. If it is possible to estimate the remaining service life of the components at the beginning of performance degradation, and on this basis determine the optimal repair time for the equipment, It can effectively avoid the major failures that may occur, thus reducing the risk of equipment operation, which is of great significance for improving the safety and reliability of the equipment operation. This project is a commissioned project from the XXXX Measurement and Control Center. Lithium Ion battery is a sub-project of the project. The residual service life prediction method of Lithium Ion battery is studied with the key component of satellite as the object. Firstly, based on a clear understanding of the working principle and failure mechanism of Lithium Ion Battery Lib, a key component of the satellite, Lithium Ion BatteryLib is studied in this paper. Aiming at the problem that it is difficult to obtain the failure data of the satellite lithium ion battery in orbit, the degradation data of the lithium ion test published by the National Aeronautics and Space Administration (NASAA) of the American Aeronautics and Astronautics Laboratory are used to replace the failure data. The statistical characteristics of the experimental data are analyzed, and the corresponding algorithm is used to estimate the remaining service life. Secondly, there are some unavoidable defects in the single algorithm, such as extended Kalman filter. Particle filter strongly depends on the model of lithium-ion battery, and autoregressive method is only related to sample data. Whether it depends on the model or only on the statistical characteristics of the data, it will have an effect on the estimated results. Therefore, a hybrid model algorithm is proposed, which depends on both the statistical properties of the data and the model of the research object. The prediction performance of the hybrid model algorithm is improved by taking advantage of their respective algorithms. The performance of the RUL prediction algorithm used in this paper is quantitatively analyzed with the help of some performance evaluation indexes of the algorithm. The predictive performance of the proposed hybrid model is better than that of the single algorithm. The residual life prediction of lithium ion batteries is of great importance in many applications. Accurate realization of RUL estimation is of great significance to maintenance of visual condition and improvement of system reliability. All the prediction methods in this paper have been realized by MATLAB simulation, which verifies the validity of the algorithm.
【學(xué)位授予單位】：西安理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TM912

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本文編號(hào)：1672772