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基于LM算法的集群電機(jī)系統(tǒng)能耗評(píng)估校正模型

2018-10-10 06:54孫笑非張新鶴杜松懷翟慶志孫若男樓振義
關(guān)鍵詞:單臺(tái)校正損耗

屈 博,孫笑非,張新鶴,黃 偉,蘇 娟,杜松懷,翟慶志,孫若男,樓振義

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基于LM算法的集群電機(jī)系統(tǒng)能耗評(píng)估校正模型

屈 博1,2,孫笑非3,張新鶴2,黃 偉2,蘇 娟3※,杜松懷3,翟慶志3,孫若男3,樓振義3

(1.天津大學(xué)電氣自動(dòng)化與信息工程學(xué)院,天津 300072;2.中國(guó)電力科學(xué)研究院有限公司,北京 100192; 3.中國(guó)農(nóng)業(yè)大學(xué)信息與電氣工程學(xué)院,北京 100083)

為了保證和提高電機(jī)系統(tǒng)能耗模型的計(jì)算精度與評(píng)估能力,該文提出了一種基于參數(shù)辨識(shí)理論的集群電機(jī)系統(tǒng)能耗校正方法。采用列文伯格-馬夸爾特(levenberg-marquardt algorithm,LM)算法,對(duì)單臺(tái)電機(jī)和集群電機(jī)系統(tǒng)的額定效率、額定可變損耗及不變損耗參數(shù)進(jìn)行辨識(shí),建立了電機(jī)能耗計(jì)算的校正模型。在此基礎(chǔ)上,以典型三機(jī)集群電機(jī)系統(tǒng)為算例,搭建真實(shí)物理試驗(yàn)平臺(tái),對(duì)集群電機(jī)系統(tǒng)進(jìn)行全域負(fù)載率能耗計(jì)算。結(jié)果表明,該文提出的能耗校正模型的計(jì)算誤差遠(yuǎn)遠(yuǎn)小于能耗出廠模型(誤差率不到1%),可以大幅降低集群電機(jī)系統(tǒng)的能耗計(jì)算誤差,工程實(shí)用性較強(qiáng),為電機(jī)用能系統(tǒng)的能耗評(píng)估和節(jié)能改造提供了一種有效的技術(shù)手段。

模型;試驗(yàn);集群電機(jī)系統(tǒng)能耗;列文伯格-馬夸爾特算法;參數(shù)辨識(shí)

0 引 言

中國(guó)是農(nóng)業(yè)大國(guó),電機(jī)是農(nóng)業(yè)生產(chǎn)用電中主要能源消耗設(shè)備。隨著全球能源消耗的不斷增長(zhǎng),環(huán)境與能源問(wèn)題日益突出,電機(jī)系統(tǒng)節(jié)能已成為中國(guó)“十二五”及“十三五”期間節(jié)能減排重點(diǎn)關(guān)注領(lǐng)域。為在工程應(yīng)用中更好地評(píng)估電機(jī)系統(tǒng)能耗情況及節(jié)能水平,能耗模型計(jì)算的準(zhǔn)確性與實(shí)用性研究不容忽視。

電機(jī)系統(tǒng)常規(guī)能耗計(jì)算方法主要為3類,一類是通過(guò)監(jiān)測(cè)電機(jī)輸入與輸出數(shù)據(jù),實(shí)時(shí)計(jì)算系統(tǒng)能耗量[1],但此方法局限于僅對(duì)當(dāng)前能耗水平監(jiān)測(cè),無(wú)法進(jìn)行全域負(fù)載率下的能耗分析;另一類是基于電機(jī)出廠銘牌構(gòu)建系統(tǒng)能耗模型,結(jié)合可測(cè)數(shù)據(jù)計(jì)算能耗量[2-5],但隨著電機(jī)使用時(shí)長(zhǎng)的增加與維護(hù)不當(dāng),或是因?yàn)闇囟?、濕度及電機(jī)老化等因素對(duì)電機(jī)運(yùn)行狀態(tài)的影響,其能耗模型中能耗參數(shù)的真實(shí)值往往達(dá)不到初始值,造成較大的計(jì)算誤差;最后一類是通過(guò)測(cè)量并計(jì)算鐵損耗、銅損耗、機(jī)械損耗與雜散損耗,構(gòu)建電機(jī)損耗模型,進(jìn)而分析其能耗情況,但此方法要求較高的數(shù)據(jù)測(cè)量能力且計(jì)算復(fù)雜,甚至需要停機(jī)操作,在實(shí)際應(yīng)用中實(shí)用性較差。

辨識(shí)技術(shù)的發(fā)展已經(jīng)十分成熟,方法很多,并不斷創(chuàng)新[6-8],為提高電機(jī)系統(tǒng)能耗評(píng)估與計(jì)算的準(zhǔn)確性,國(guó)內(nèi)外學(xué)者對(duì)電機(jī)系統(tǒng)參數(shù)辨識(shí)與模型優(yōu)化做了大量研究。文獻(xiàn)[9]基于銘牌參數(shù)和序列二次規(guī)劃算法,提出一種以效率偏差最小為目標(biāo)的電機(jī)參數(shù)辨識(shí)方法,通過(guò)辨識(shí)出定子與轉(zhuǎn)子電抗值,分析電機(jī)效率、功率因數(shù)等性能參數(shù),但該方法基于出廠銘牌數(shù)據(jù)且忽略鐵損影響,計(jì)算會(huì)帶來(lái)一定誤差;文獻(xiàn)[10]提出一種將遞推最小二乘與模型參考自適應(yīng)相結(jié)合的異步電機(jī)參數(shù)在線辨識(shí)方法,該方法可實(shí)時(shí)獲取辨識(shí)值,并利用等效電路法完成電機(jī)能效的動(dòng)態(tài)評(píng)估;文獻(xiàn)[11-12]利用李亞普洛夫定理構(gòu)建參數(shù)自適應(yīng)律,并基于模型參考自適應(yīng)方法進(jìn)行多參數(shù)辨識(shí),該方法具有算法簡(jiǎn)單的優(yōu)點(diǎn),但如何針對(duì)電機(jī)系統(tǒng)能耗模型建立誤差方程和構(gòu)造恰當(dāng)?shù)淖赃m應(yīng)律是該方法的難點(diǎn);文獻(xiàn)[13]基于變頻器驅(qū)動(dòng)的直線感應(yīng)電機(jī)等效電路,根據(jù)不同頻率下的堵轉(zhuǎn)特性,辨識(shí)出電機(jī)電阻與漏感參數(shù),該方法計(jì)算簡(jiǎn)單、可行,但在對(duì)電機(jī)能耗參數(shù)分析時(shí)略有不足。

在電機(jī)能耗模型的相關(guān)研究中,文獻(xiàn)[14]指導(dǎo)并建立并聯(lián)方式下考慮鐵損耗的感應(yīng)電機(jī)旋轉(zhuǎn)坐標(biāo)系等效電路,并在穩(wěn)態(tài)運(yùn)行時(shí)對(duì)其簡(jiǎn)化;文獻(xiàn)[15]提出一種基于時(shí)步有限元的感應(yīng)電機(jī)鐵損改進(jìn)模型,試驗(yàn)結(jié)果表明該模型有較高的準(zhǔn)確性,為電機(jī)損耗分析與計(jì)算提供新思路;文獻(xiàn)[16]通過(guò)分析電機(jī)氣隙磁場(chǎng),將雜散損耗分解到轉(zhuǎn)子銅損耗與鐵損耗2部分,進(jìn)而得到新型雜散損耗模型;文獻(xiàn)[17]基于定子磁鏈定向坐標(biāo)系,建立了計(jì)及鐵損耗的感應(yīng)電機(jī)損耗模型;文獻(xiàn)[18]考慮鐵耗影響的情況下建立了感應(yīng)電機(jī)數(shù)學(xué)模型,采用了基于鐵耗模型的感應(yīng)電機(jī)矢量控制,通過(guò)對(duì)電機(jī)運(yùn)行過(guò)程中損耗進(jìn)行分析,推導(dǎo)了輕載時(shí)最優(yōu)磁通實(shí)現(xiàn)效率最優(yōu)的原理。上述研究雖然在電機(jī)的能耗建模與分析方法上有所創(chuàng)新,但是所需測(cè)量的參數(shù)類別較多,較為復(fù)雜,且僅對(duì)單機(jī)系統(tǒng)進(jìn)行能耗模型研究。由于很多工業(yè)系統(tǒng)具有電機(jī)集群運(yùn)行的特點(diǎn),對(duì)于集群式電機(jī)系統(tǒng)的應(yīng)用缺少驗(yàn)證,因此,在實(shí)際工程中難以應(yīng)用。

本文基于現(xiàn)有研究理論,考慮工程適用條件,以數(shù)據(jù)可觀測(cè)為前提,構(gòu)建一種基于levenberg-marquardt(LM)算法的集群電機(jī)系統(tǒng)能耗校正模型。將系統(tǒng)額定效率、可變損耗與不變損耗作為待辨識(shí)參數(shù),基于實(shí)測(cè)數(shù)據(jù),并結(jié)合LM算法,對(duì)系統(tǒng)能耗參數(shù)進(jìn)行辨識(shí),進(jìn)而建立集群電機(jī)系統(tǒng)能耗的校正模型,為電機(jī)性能評(píng)估與系統(tǒng)能耗分析提供有效的技術(shù)手段。

1 電機(jī)能耗模型

1.1 單臺(tái)電機(jī)能耗模型

基于功率平衡原理,電機(jī)能耗情況可表示為[19]

對(duì)電機(jī)損耗進(jìn)一步分析,可變損耗由銅損耗與雜散損耗組成,不變損耗由鐵損耗與機(jī)械損耗組成[20]。

電機(jī)可變損耗大小與負(fù)載率和額定可變損耗有關(guān),計(jì)算公式為

將式(1)與式(3)整理可得單臺(tái)電機(jī)能耗模型為

根據(jù)式(4),單臺(tái)電機(jī)主要能耗參數(shù)為負(fù)載率、額定效率與不變損耗。

1.2 集群電機(jī)系統(tǒng)能耗模型

對(duì)于多個(gè)電機(jī)并聯(lián)運(yùn)行的集群電機(jī)系統(tǒng),其主測(cè)量點(diǎn)為同一電壓等級(jí)下所有電機(jī)總輸入端,常為變壓器二次端,所以系統(tǒng)能耗情況可表示為

考慮系統(tǒng)中各臺(tái)電機(jī)能耗情況,由式(4)與式(5)可以得出

由式(3)與式(6)可得出集群電機(jī)系統(tǒng)能耗模型為

根據(jù)式(7),集群電機(jī)系統(tǒng)主要能耗參數(shù)為各臺(tái)電機(jī)的負(fù)載率、額定可變損耗與總不變損耗。

在系統(tǒng)實(shí)際運(yùn)行中,常常出現(xiàn)電機(jī)能耗參數(shù)偏離出廠參數(shù)的情況,表現(xiàn)在額定效率與損耗參數(shù)上。在對(duì)集群電機(jī)系統(tǒng)進(jìn)行能耗計(jì)算時(shí),系統(tǒng)內(nèi)每臺(tái)電機(jī)的能耗計(jì)算誤差,最終反映在整個(gè)集群電機(jī)系統(tǒng)中。

2 基于Levenberg-Marquardt算法的集群電機(jī)系統(tǒng)能耗校正模型

2.1 Levenberg-Marquardt算法

最小二乘辨識(shí)方法原理簡(jiǎn)單,應(yīng)用廣泛,在最小二乘算法基礎(chǔ)上優(yōu)化得到的算法可以方便地耦合在其他優(yōu)化辨識(shí)算法[21-25]。阻尼最小二乘法最早由Levenberg與Marquardt共同提出,因此又稱為levenberg-marquardt算法,即LM算法。在高斯—牛頓法的基礎(chǔ)上,LM算法引進(jìn)了阻尼因子概念[26],對(duì)于非線性方程

基于最小二乘法的思想,保證計(jì)算殘差平方和最小,得到系統(tǒng)最優(yōu)解[27]。計(jì)算公式為

式中為雅可比矩陣。

關(guān)系矩陣為:

式中為單位矩陣。

最終迭代公式為

2.2 單臺(tái)電機(jī)能耗校正模型

在對(duì)單臺(tái)電機(jī)分析時(shí),根據(jù)式(4)設(shè)其能耗求解模型為

由式(9)構(gòu)建殘差最小模型為

2.3 集群電機(jī)系統(tǒng)能耗校正模型

在對(duì)集群電機(jī)系統(tǒng)分析時(shí),根據(jù)式(7)設(shè)其能耗求解模型為

基于校正模型可準(zhǔn)確計(jì)算單臺(tái)電機(jī)及集群電機(jī)系統(tǒng)在全域負(fù)載率下的能耗情況,并且,可以通過(guò)能耗參數(shù)辨識(shí)結(jié)果對(duì)系統(tǒng)能耗水平分析,參考相關(guān)標(biāo)準(zhǔn)[28],對(duì)能耗水平不達(dá)標(biāo)的設(shè)備進(jìn)行維修或淘汰,對(duì)能耗水平差的集群電機(jī)系統(tǒng)進(jìn)行運(yùn)行調(diào)整或節(jié)能改造。

3 現(xiàn)場(chǎng)測(cè)試和模型計(jì)算實(shí)例

圖1 電機(jī)試驗(yàn)平臺(tái)

在空載試驗(yàn)與負(fù)載試驗(yàn)下,分別對(duì)3臺(tái)電機(jī)進(jìn)行額定參數(shù)測(cè)量。設(shè)定電機(jī)在額定電壓與頻率下運(yùn)行,將空載損耗近似為不變損耗,并取10次測(cè)量平均值作為電機(jī)的真實(shí)能耗參數(shù),如表1所示。

表1 電機(jī)真實(shí)能耗參數(shù)

考慮實(shí)際應(yīng)用中數(shù)據(jù)的可觀測(cè)性,在額定電壓下,以系統(tǒng)輸入與輸出功率作為測(cè)量數(shù)據(jù),選取表1所涉及的相同負(fù)載試驗(yàn)數(shù)據(jù),分別對(duì)3臺(tái)電機(jī)的額定效率與不變損耗進(jìn)行參數(shù)辨識(shí)計(jì)算并進(jìn)行誤差分析,如表2所示。

在對(duì)單臺(tái)電機(jī)辨識(shí)結(jié)果分析中,第3臺(tái)電機(jī)誤差最大,最大誤差率不超過(guò)2%;第1臺(tái)電機(jī)誤差最小,最小誤差率僅為0.04%,辨識(shí)結(jié)果理想。以第1臺(tái)電機(jī)為例,由銘牌參數(shù)計(jì)算出廠能耗參數(shù)。電機(jī)額定效率為

不變損耗(包括鐵損耗與機(jī)械損耗)由電機(jī)出廠試驗(yàn)獲得,本文令其為額定總損耗的40%[29-30],則

根據(jù)式(4)構(gòu)建單臺(tái)電機(jī)的能耗出廠模型為:

表2 單臺(tái)電機(jī)參數(shù)辨識(shí)結(jié)果與誤差

通過(guò)對(duì)3臺(tái)電機(jī)進(jìn)行空載與負(fù)載試驗(yàn)后獲得電機(jī)設(shè)備真實(shí)能耗參數(shù)(見表1),由此構(gòu)建單臺(tái)電機(jī)的能耗真實(shí)模型為:

根據(jù)單臺(tái)電機(jī)參數(shù)辨識(shí)結(jié)果(見表2),由此構(gòu)建基于辨識(shí)結(jié)果的單臺(tái)電機(jī)能耗校正模型為:

基于上述3臺(tái)電機(jī)所構(gòu)成的集群電機(jī)系統(tǒng),進(jìn)行能耗校正模型研究。在額定電壓下,測(cè)量集群電機(jī)系統(tǒng)內(nèi)各臺(tái)電機(jī)在不同負(fù)載率下的輸出功率及系統(tǒng)總輸入功率。根據(jù)所測(cè)數(shù)據(jù),對(duì)集群電機(jī)系統(tǒng)的額定可變損耗與總不變損耗參數(shù)進(jìn)行辨識(shí),并結(jié)合表1進(jìn)行誤差分析,分析結(jié)果如表3與表4所示。

表3 集群電機(jī)系統(tǒng)額定可變損耗參數(shù)辨識(shí)結(jié)果與誤差

表4 集群電機(jī)系統(tǒng)不變損耗參數(shù)辨識(shí)結(jié)果與誤差

基于辨識(shí)結(jié)果對(duì)集群電機(jī)系統(tǒng)進(jìn)行能耗模型校正,根據(jù)式(7)構(gòu)建系統(tǒng)的能耗出廠模型為

根據(jù)空載與負(fù)載試驗(yàn)后獲得電機(jī)真實(shí)能耗參數(shù)(見表1),由此構(gòu)建集群電機(jī)系統(tǒng)的能耗真實(shí)模型為

根據(jù)集群電機(jī)系統(tǒng)額定可變損耗與不變損耗參數(shù)辨識(shí)結(jié)果(見表3與表4),由此構(gòu)建基于辨識(shí)結(jié)果的集群電機(jī)系統(tǒng)能耗校正模型為:

基于上述模型,構(gòu)建單臺(tái)電機(jī)與集群電機(jī)系統(tǒng)在全域負(fù)載率下的能耗曲線對(duì)比圖,并分析校正模型能耗計(jì)算誤差,如圖2所示。

分析圖2可知,系統(tǒng)出廠能耗曲線大幅低于試驗(yàn)所測(cè)的真實(shí)能耗曲線,說(shuō)明電機(jī)設(shè)備能耗參數(shù)已有較大改變,能耗出廠模型不能準(zhǔn)確計(jì)算系統(tǒng)能耗情況;校正后的能耗曲線與真實(shí)能耗曲線基本重合,能耗校正模型的計(jì)算誤差遠(yuǎn)遠(yuǎn)小于能耗出廠模型(誤差率不到1%),說(shuō)明校正模型可準(zhǔn)確計(jì)算單臺(tái)電機(jī)和集群電機(jī)系統(tǒng)在全域負(fù)載率下的能耗情況。例如,在負(fù)載率為1.0的情況下,基于出廠能耗模型計(jì)算出集群電機(jī)系統(tǒng)能耗量為457.26 W,經(jīng)校正模型計(jì)算其能耗量為563.48 W,而系統(tǒng)真實(shí)能耗量為567.73 W;出廠能耗模型計(jì)算誤差達(dá)到110.47 W,誤差率19.46%,而校正模型計(jì)算誤差僅為4.25 W,誤差率0.75%。此外,系統(tǒng)通過(guò)較少的可測(cè)量數(shù)據(jù)完成模型校正,能耗計(jì)算僅需運(yùn)行負(fù)載率參數(shù),從而解決常規(guī)能耗計(jì)算方法在實(shí)際應(yīng)用中的問(wèn)題與困難,具有很強(qiáng)的實(shí)用性。

圖2 電機(jī)系統(tǒng)能耗情況對(duì)比

4 結(jié) 論

針對(duì)實(shí)際計(jì)算與評(píng)估的需要,本文基于LM算法,設(shè)計(jì)出一種集群電機(jī)系統(tǒng)能耗校正模型。為研究該能耗校正模型的可靠性和有效性,進(jìn)行試驗(yàn)測(cè)試和計(jì)算。選定單臺(tái)電機(jī)和集群電機(jī)系統(tǒng)的額定效率、額定可變損耗與不變損耗為待辨識(shí)參數(shù),利用實(shí)測(cè)數(shù)據(jù)結(jié)合LM算法對(duì)上述參數(shù)進(jìn)行辨識(shí),根據(jù)辨識(shí)結(jié)果建立電機(jī)系統(tǒng)能耗計(jì)算的校正模型。搭建真實(shí)物理試驗(yàn)平臺(tái),選用3臺(tái)同型號(hào)、容量為100 W的異步電機(jī)構(gòu)建典型集群電機(jī)系統(tǒng),通過(guò)采集真實(shí)試驗(yàn)數(shù)據(jù)對(duì)仿真工作驗(yàn)證。測(cè)試結(jié)果表明:

1)按照系統(tǒng)實(shí)際評(píng)估條件,通過(guò)可觀測(cè)數(shù)據(jù),能夠準(zhǔn)確辨識(shí)單臺(tái)電機(jī)和集群電機(jī)系統(tǒng)的額定效率、額定可變損耗及不變損耗參數(shù),并構(gòu)建系統(tǒng)能耗校正模型,由此對(duì)電機(jī)系統(tǒng)進(jìn)行能耗水平評(píng)估與計(jì)算,為節(jié)能減排工作提供有效的技術(shù)手段。

2)本文所提出的能耗校正模型,可大幅提高單臺(tái)電機(jī)和集群電機(jī)系統(tǒng)的能耗計(jì)算精度,避免常規(guī)能耗計(jì)算方法帶來(lái)的計(jì)算誤差與操作困難。文中通過(guò)構(gòu)建電機(jī)物理試驗(yàn)平臺(tái),分別以單臺(tái)電機(jī)與典型三機(jī)集群系統(tǒng)為試驗(yàn)對(duì)象,進(jìn)行單臺(tái)電機(jī)與電機(jī)系統(tǒng)對(duì)比驗(yàn)證。單臺(tái)電機(jī)參數(shù)辨識(shí)結(jié)果誤差率最小為0.04%,最大為1.84%;集群電機(jī)系統(tǒng)額定可變損耗與不變損耗辨識(shí)誤差率分別為0.57%與2.29%;并且能耗校正模型的計(jì)算誤差率最大不到1%,可準(zhǔn)確計(jì)算系統(tǒng)在全域負(fù)載率下的能耗情況。

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Correction model of energy consumption evaluation of cluster motor system based on levenberg-marquardt algorithm

Qu Bo1,2, Sun Xiaofei3, Zhang Xinhe2, Huang Wei2, Su Juan3※, Du Songhuai3, Zhai Qingzhi3, Sun Ruonan3, Lou Zhenyi3

(1.3000722.1001923.100083,)

China is a large agricultural country. Motor is the main energy consuming equipment in agricultural production. With the continuous growth of global energy consumption, environmental and energy problems are becoming increasingly prominent. Energy-saving of motor systems has become the focus of attention in China. There are 3 main methods for calculating the conventional energy consumption of motor systems. One is to calculate the energy consumption of the system in real time by monitoring the input and output data of the motor. However, this method is limited to monitor the current energy consumption level and cannot analyze the energy consumption under the global load rate. The other is to construct the energy consumption model of the system based on the nameplate of the motor manufacturer and calculate the energy consumption with the measurable data. However, with the increase of the use time of the motor and the improper maintenance, or because of the influence of temperature, humidity and aging of the motor on the running state of the motor, the real value of the energy consumption parameters in the energy consumption model often cannot reach the initial value. The initial value leads to large calculation error. The last one is to build motor loss model by measuring and calculating iron loss, copper loss, mechanical loss and stray loss, and then analyze its energy consumption. However, this method requires high data measurement ability and complex calculation, and even requires shutdown operation, which is not practical in application.The aim of this study was to propose an energy consumption correction method for cluster motor system based on the parameter identification theory to ensure and increase the calculation accuracy and evaluation capability of the energy consumption model. The levenberg–marquardt (LM) algorithmwas used to recognize the rated efficiency, rated variable loss and constant loss parameters of a single motor and cluster motor system, then a calibration model for energy consumption calculation of the motor based on recognized parameters was constructed to achieve correction of system energy consumption model. Based on the above theory, a typical three-motor cluster motor system was set up as a physical experiment platform sample to acquire real operating data, which included rated voltageU=220 V, rated current=0.5 A, rated frequency=50 Hz, rated power=1 000 W, as well as rated rotor speed=1 420 r/min. The results showed that the calibration energy consumption model of this study can dramatically decrease the error of energy consumption calculation of cluster motor system and have strong engineering practicability, and it provided an effective technical approach for energy evaluation and energy saving modification of motor energy consumption system.

models; experiments; cluster motor system energy consumption; levenberg-marquardt algorithm; parameter identification

10.11975/j.issn.1002-6819.2018.18.006

TM306

A

1002-6819(2018)-18-0044-07

2018-03-06

2018-06-01

國(guó)家電網(wǎng)公司總部科技項(xiàng)目資助“能效基準(zhǔn)數(shù)據(jù)庫(kù)數(shù)據(jù)驗(yàn)證服務(wù)技術(shù)合同”(YDB51201701973)

屈 博,博士生,高級(jí)工程師,主要從事電能替代、綜合能源優(yōu)化研究。Email:qubo@epri.sgcc.com.cn

蘇 娟,博士,主要從事電力節(jié)能與需求側(cè)管理研究。 Email:sujuan@cau.edu.cn

中國(guó)農(nóng)業(yè)工程學(xué)會(huì)會(huì)員:蘇娟(E041200880S)

屈 博,孫笑非,張新鶴,黃 偉,蘇 娟,杜松懷,翟慶志,孫若男,樓振義. 基于LM算法的集群電機(jī)系統(tǒng)能耗評(píng)估校正模型[J]. 農(nóng)業(yè)工程學(xué)報(bào),2018,34(18):44-50. doi:10.11975/j.issn.1002-6819.2018.18.006 http://www.tcsae.org

Qu Bo, Sun Xiaofei, Zhang Xinhe, Huang Wei, Su Juan, Du Songhuai, Zhai Qingzhi, Sun Ruonan, Lou Zhenyi.Correction model of energy consumption evaluation of cluster motor system based on levenberg-marquardt algorithm[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2018, 34(18): 44-50. (in Chinese with English abstract) doi:10.11975/j.issn.1002-6819.2018.18.006 http://www.tcsae.org

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