本文選題：鋰離子電池　切入點：容量損失預(yù)測　出處：《哈爾濱工業(yè)大學(xué)》2017年博士論文　論文類型：學(xué)位論文

【摘要】：動力電池的梯級利用技術(shù),作為一項重大的前沿應(yīng)用科學(xué)研究,其內(nèi)涵為通過對電池的機(jī)制診斷、壽命預(yù)測、狀態(tài)估計等技術(shù)手段將不再滿足電動汽車動力性能要求的退役電池,降級應(yīng)用至能量、功率密度要求較低的通信基站、分布式儲能等領(lǐng)域,進(jìn)而延長動力電池的使用壽命,降低電動汽車的使用成本,同時避免廢棄物排放對環(huán)境造成的污染。但目前對于動力鋰離子電池特性及其老化過程的研究一般僅停留在電池容量損失率小于20%的階段,相關(guān)研究成果并不能被簡單推衍至電池的整個壽命周期,因而無法在全壽命周期內(nèi)保證對電池容量損失機(jī)制的可靠診斷與對電池梯級替換時間點的有效預(yù)測。此外,作為電池退役時間點的在線判斷依據(jù),現(xiàn)有車用電池健康狀態(tài)(SOH)估計方法也面臨著溫度適用范圍與電動汽車實際工作環(huán)境不匹配的問題。為了解決以上問題,本文從對鋰離子電池的容量損失機(jī)制診斷研究入手,分別對電池在全壽命周期內(nèi)的容量損失預(yù)測問題及車用階段的電池SOH在線估計問題進(jìn)行了有針對性的研究,其主要研究內(nèi)容如下:首先,針對現(xiàn)有用于容量損失機(jī)制診斷的開路電壓(OCV)老化模型在電池老化中后期,對OCV曲線擬合逐漸失真,進(jìn)而導(dǎo)致診斷結(jié)論不可靠的問題,提出了基于電極電勢曲線非均勻壓縮特性的OCV老化改進(jìn)模型。該模型通過建立電池固有電極坐標(biāo)系與可用電極坐標(biāo)系之間的非均勻壓縮轉(zhuǎn)換函數(shù),表征了電極材料單一粒子尺寸變化與多粒子尺寸分布情況變化對電極電勢曲線上單相區(qū)和兩相共存區(qū)占比情況的影響,從而使得OCV老化模型在整個壽命周期中保持了良好的擬合精度。通過電池在1C電流倍率、常溫25℃循環(huán)老化條件下的全壽命OCV特性實驗表明,相較于現(xiàn)有模型,本模型將整個壽命周期內(nèi)的OCV擬合RMS誤差由11 m V減小至2 mV。其次,針對現(xiàn)有容量損失預(yù)測模型僅適用于表征電池老化前期的容量變化規(guī)律,進(jìn)而導(dǎo)致無法對電池在全壽命周期內(nèi)梯級利用替換時間點進(jìn)行合理規(guī)劃的問題,建立了基于擴(kuò)散應(yīng)力分布理論的可循環(huán)鋰損失-活性材料損失(LLILAM)復(fù)合容量損失模型。該模型在現(xiàn)有LLI損失模型的基礎(chǔ)上,利用球形粒子的擴(kuò)散應(yīng)力分布理論,建立了電極粒子脫嵌鋰過程中由往復(fù)變化應(yīng)力所引起的材料疲勞斷裂效應(yīng)模型,表征了耦合老化條件(工作溫度與電流倍率)與電池LAM損失速率之間的定量關(guān)系,進(jìn)而獲得了對電池在全壽命周期下容量損失軌跡的預(yù)測能力。通過電池在1C電流倍率、40℃條件下與0.5C電流倍率、25℃老化條件下的驗證實驗表明,與現(xiàn)有模型相比,本模型在5%的容量損失率預(yù)測誤差容限內(nèi),將容量損失預(yù)測模型的適用范圍由容量損失率小于20%的階段擴(kuò)展至電池的整個壽命周期。此外,針對現(xiàn)有電池健康狀態(tài)(SOH)估計方法局限于室溫工作條件,導(dǎo)致與電動汽車實際工作環(huán)境不匹配的問題,提出了一種適用于寬溫度范圍的鋰離子電池健康狀態(tài)在線估計方法。該方法利用固態(tài)電解質(zhì)界面膜生成過程中,可循環(huán)鋰消耗所引起的歐姆內(nèi)阻增加量與電池容量損失量之間的函數(shù)關(guān)系,結(jié)合溫度變化對電池歐姆內(nèi)阻各組分阻值的作用規(guī)律模型,從原理上突破了現(xiàn)有電池SOH在線估計方法溫度適用范圍的局限。實驗證明本方法在與現(xiàn)有方法具有同等估計精度(誤差小于5%)的前提下,將SOH估計的溫度適用范圍由20℃~30℃拓寬至-10℃~50℃。
[Abstract]:By using the technology of power battery cascade, as a major application of cutting-edge scientific research, its connotation is through the mechanism of diagnosis, the battery life prediction, state estimation technique will no longer meet the retired battery electric vehicle power performance requirements, application to downgrade energy, low power density requirements of communication base station, distributed storage etc., and prolongs service life of the battery, reduce the cost of electric vehicles, while avoiding waste pollution emissions on the environment. But the study on the dynamic characteristics of lithium ion battery and its aging process generally only in battery capacity loss rate is less than 20% of the stage, the relevant research results cannot be simply extrapolated to the life cycle of the battery, and thus cannot be in the full life cycle to ensure reliable diagnosis of the loss mechanism of the battery capacity and battery replacement time of cascade The effective prediction point. In addition, as online time judging retired battery, battery health with existing vehicle (SOH) estimation method is also facing the temperature range and the actual work environment of electric vehicle does not match the problem. In order to solve the above problems, this paper from the research on diagnosis capacity loss mechanism of lithium ion battery with of battery capacity loss in the whole life cycle prediction problems and car issues targeted on stage SOH battery on-line estimation, the main research contents are as follows: firstly, aiming at the existing for open circuit voltage loss diagnosis mechanism (OCV) in the aging model of battery aging period, the curve of OCV the fitting gradually distortion, which led to the diagnosis conclusion is not reliable, non uniform compression characteristics of aging OCV improved model curve of electrode potential is proposed based on the model through the establishment of the battery. Non uniform compression conversion function between the electrode and the electrode can coordinate the inherent coordinate system, characterization of electrode materials of single particle size change and particle size distribution change of the electrode potential curve of single-phase region and two-phase region accounted for the effect, so that the OCV aging model in the whole life cycle to maintain good fitting accuracy the battery in the 1C. Through the current rate, temperature 25 C cycling aging life OCV characteristics under experimental conditions show that, compared with the existing models, this model will be RMS error OCV fitting the whole life cycle from 11 m V reduced to 2 mV. second, according to the existing capacity loss prediction model is only suitable for the characterization of battery aging capacity early changes, which led to the replacement time reasonable planning problem of cascade in the whole life cycle of the battery was established based on the stress diffusion The theory of circular cloth Li loss - active material loss (LLILAM) composite capacity loss model is proposed based on the existing LLI loss model, the stress distribution by using the theory of diffusion of spherical particles, fatigue fracture effect model of particle electrode of lithium intercalation process by reciprocating the stress change caused by the characterization the coupling of aging conditions (temperature and current ratio) and the quantitative relationship between LAM cell loss rate, and then obtained the ability to predict battery capacity loss in the whole life cycle under the trajectory. Through the battery at 1C current ratio, the temperature of 40 DEG C and 0.5C current ratio, 25 degrees aging show that under the experimental conditions. Compared with the existing models, this model prediction error tolerance in the capacity loss of 5%, the capacity loss prediction model suitable for the capacity loss rate of less than 20% stage extended to the entire life of the battery Cycle. In addition, the existing battery state of Health (SOH) estimation methods are confined to work at room temperature conditions, problems caused and electric vehicle does not match the actual working environment, put forward a kind of lithium ion battery health online for wide temperature range estimation method. This method uses solid electrolyte interface film formation process, can be recycled lithium consumption caused by the increase in the ohmic resistance function and the relationship between the amount of battery capacity loss, rule model combined with the temperature change on the ohmic resistance components of resistance, in principle, to break the existing battery SOH online estimation of temperature range limitations. The experiment proved that this method has the same accuracy in existing methods (error less than 5%) under the premise of the temperature range of SOH estimation by 20 DEG ~30 DEG to -10 DEG ~50 DEG. Broaden

【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2017
【分類號】：TM912

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