殷國(guó)棟,金賢建,張 云,2
(1.東南大學(xué) 機(jī)械工程學(xué)院,南京 211189;2.福特汽車(chē)工程研究南京有限公司,南京 211100)
?
分布式驅(qū)動(dòng)電動(dòng)汽車(chē)底盤(pán)動(dòng)力學(xué)控制研究綜述
殷國(guó)棟1,金賢建1,張?jiān)?,2
(1.東南大學(xué) 機(jī)械工程學(xué)院,南京211189;2.福特汽車(chē)工程研究南京有限公司,南京211100)
分布式驅(qū)動(dòng)電動(dòng)汽車(chē)將電機(jī)直接置于輪輞中,在大幅簡(jiǎn)化車(chē)輛底盤(pán)結(jié)構(gòu)、提高能量效率的同時(shí),能實(shí)現(xiàn)輪轂轉(zhuǎn)矩的精確測(cè)量與驅(qū)動(dòng)力矩的快速響應(yīng),為改善車(chē)輛底盤(pán)動(dòng)力學(xué)控制系統(tǒng)的安全穩(wěn)定性提供了獨(dú)特的優(yōu)勢(shì),已經(jīng)逐漸被國(guó)際汽車(chē)領(lǐng)域研究學(xué)者認(rèn)為是最有發(fā)展?jié)摿Φ碾妱?dòng)汽車(chē)框架之一。分別從底盤(pán)縱向動(dòng)力學(xué)控制、橫向動(dòng)力學(xué)控制、集成動(dòng)力學(xué)控制等3方面對(duì)分布式驅(qū)動(dòng)電動(dòng)汽車(chē)動(dòng)力學(xué)控制研究進(jìn)展進(jìn)行了綜述,著重介紹了驅(qū)動(dòng)防滑系統(tǒng)、回饋與防抱死協(xié)調(diào)制動(dòng)系統(tǒng)、四輪獨(dú)立轉(zhuǎn)向系統(tǒng)、直接橫擺穩(wěn)定性控制系統(tǒng)、電子差速系統(tǒng)等電動(dòng)汽車(chē)底盤(pán)動(dòng)力學(xué)控制的新興研究熱點(diǎn),并對(duì)分布式驅(qū)動(dòng)電動(dòng)汽車(chē)動(dòng)力學(xué)控制研究未來(lái)的發(fā)展趨勢(shì)做了幾點(diǎn)展望。
分布式驅(qū)動(dòng)電動(dòng)汽車(chē);縱向動(dòng)力學(xué);橫向動(dòng)力學(xué);參數(shù)估計(jì);集成動(dòng)力學(xué)控制
隨著石油危機(jī)的不斷加劇和環(huán)境污染的日益凸顯,開(kāi)發(fā)安全、環(huán)保、節(jié)能的交通工具成為人類(lèi)所追求的共同目標(biāo)。電動(dòng)汽車(chē)使用電能直接驅(qū)動(dòng)車(chē)輛,可以實(shí)現(xiàn)城市交通的零排放,近年來(lái)美國(guó)、歐洲、日本、中國(guó)等國(guó)家紛紛提出自己的電動(dòng)汽車(chē)發(fā)展戰(zhàn)略,電動(dòng)汽車(chē)面臨著加速發(fā)展的戰(zhàn)略機(jī)遇,被認(rèn)為是21世紀(jì)廣泛采用的交通工具[1-7]。與傳統(tǒng)燃油汽車(chē)相比,分布式驅(qū)動(dòng)電動(dòng)汽車(chē)使用輪轂電機(jī)直接驅(qū)動(dòng)車(chē)輪。圖1是東京大學(xué)開(kāi)發(fā)的分布式驅(qū)動(dòng)電動(dòng)汽車(chē)“UOT March II”底盤(pán)架構(gòu)[1],其全電動(dòng)化的驅(qū)動(dòng)底盤(pán)擁有傳統(tǒng)車(chē)輛無(wú)法比擬的高能量效率,并能實(shí)現(xiàn)制動(dòng)過(guò)程中的能量回收。更重要的是分布式驅(qū)動(dòng)電動(dòng)汽車(chē)不需要附加傳感器就可實(shí)現(xiàn)輪轂轉(zhuǎn)矩的精確測(cè)量,能大幅提高車(chē)輛驅(qū)動(dòng)力矩的響應(yīng)速度,為提高車(chē)輛底盤(pán)動(dòng)力學(xué)控制提供了獨(dú)特的優(yōu)勢(shì),將對(duì)車(chē)輛底盤(pán)動(dòng)力學(xué)控制系統(tǒng)包括驅(qū)動(dòng)防滑系統(tǒng)(acceleration slip regulation,ASR)、回饋制動(dòng)系統(tǒng)(regenerative braking system,RBS)、四輪轉(zhuǎn)向系統(tǒng)(four wheel steer,4WS)、直接橫擺穩(wěn)定性控制系統(tǒng)(direct yaw moment control,DYC)、電子差速系統(tǒng)(electronic differential system,EDS)等的安全穩(wěn)定性改善有著極其重要的工程應(yīng)用意義[1-7]。
1.1驅(qū)動(dòng)防滑動(dòng)力學(xué)控制系統(tǒng)
分布式驅(qū)動(dòng)電動(dòng)汽車(chē)的驅(qū)動(dòng)防滑控制系統(tǒng)主要是利用電動(dòng)汽車(chē)驅(qū)動(dòng)力矩獨(dú)立可控,轉(zhuǎn)速容易獲得的特點(diǎn),在車(chē)輛啟動(dòng)加速過(guò)程中起防滑作用,主要控制目標(biāo)是將車(chē)輪滑轉(zhuǎn)率控制在最優(yōu)范圍內(nèi),從而使車(chē)輪在加速過(guò)程中獲得比較大的附著力,防止因驅(qū)動(dòng)輪過(guò)度滑轉(zhuǎn)而降低車(chē)輛的驅(qū)動(dòng)性能,從而有效地提高車(chē)輛加速行駛的安全性。國(guó)內(nèi)外學(xué)者分別采用不同的控制方法,如模糊邏輯控制、最優(yōu)控制、滑模變結(jié)構(gòu)控制、模型跟蹤控制、等對(duì)ASR進(jìn)行了研究[8-12]。文獻(xiàn)[8]提出了基于門(mén)限角加速度和最優(yōu)滑轉(zhuǎn)率的模糊滑轉(zhuǎn)率控制方法,以實(shí)際角加速度與門(mén)限角加速度之差和實(shí)際滑轉(zhuǎn)率與最優(yōu)滑轉(zhuǎn)率之差作為模糊控制器輸入,使得實(shí)際角加速度接近門(mén)限角加速度,控制各輪的驅(qū)動(dòng)力矩實(shí)現(xiàn)驅(qū)動(dòng)防滑。仿真結(jié)果表明:相比傳統(tǒng)控制算法,基于門(mén)限角加速度的模糊滑轉(zhuǎn)率控制能有效降低滑轉(zhuǎn)率。文獻(xiàn)[9]提出了基于轉(zhuǎn)矩選擇器的驅(qū)動(dòng)防滑系統(tǒng)控制算法(如圖2所示),其控制邏輯是根據(jù)識(shí)別的路面條件來(lái)確定當(dāng)前的最優(yōu)滑移率,并增加了轉(zhuǎn)矩選擇器結(jié)合駕駛員的轉(zhuǎn)矩控制命令與當(dāng)前最優(yōu)滑移率下的轉(zhuǎn)矩來(lái)選擇電機(jī)轉(zhuǎn)矩輸出,繼而自動(dòng)實(shí)現(xiàn)最優(yōu)驅(qū)動(dòng)防滑控制,仿真結(jié)果表明了該設(shè)計(jì)控制器的有效性。

圖1 東京大學(xué)分布式驅(qū)動(dòng)電動(dòng)汽車(chē)“UOT March II”底盤(pán)架構(gòu)

圖2 基于轉(zhuǎn)矩選擇器的驅(qū)動(dòng)防滑系統(tǒng)控制邏輯
1.2制動(dòng)動(dòng)力學(xué)控制系統(tǒng)
與傳統(tǒng)的內(nèi)燃機(jī)車(chē)輛相比,分布式驅(qū)動(dòng)電動(dòng)汽車(chē)在制動(dòng)過(guò)程中,電動(dòng)機(jī)以發(fā)電方式工作,能將電動(dòng)汽車(chē)的動(dòng)能或勢(shì)能轉(zhuǎn)換為電能進(jìn)行存儲(chǔ),是提高車(chē)輛能源利用率的一項(xiàng)重要技術(shù)。考慮到電機(jī)的制動(dòng)效能以及制動(dòng)過(guò)程中的穩(wěn)定性,作為保證車(chē)輛制動(dòng)主動(dòng)安全最廣泛的防抱死制動(dòng)系統(tǒng)仍舊會(huì)被電動(dòng)汽車(chē)大量應(yīng)用,目前國(guó)內(nèi)外的研究熱點(diǎn)集中從之前單純?nèi)绾问鼓芰炕仞佇首畲蠡饾u轉(zhuǎn)向到在保證車(chē)輛制動(dòng)穩(wěn)定性的同時(shí)如何使能量回饋效率最大化,針對(duì)電動(dòng)汽車(chē)回饋制動(dòng)系統(tǒng)和防抱死制動(dòng)系統(tǒng)的集成協(xié)調(diào)控制策略被持續(xù)關(guān)注[6,13-17,44]。例如:Bera等[6]提出了在鍵合圖理論上的協(xié)調(diào)RBS和ABS策略;Castro等[13]提出了基于自適應(yīng)的滑移率控制的RBS和ABS協(xié)調(diào)制動(dòng)控制策略,該文頗有新意的是考慮了輪轂電機(jī)飽和等多種條件的約束,對(duì)于不確定路面條件具有極強(qiáng)的自適應(yīng)性和魯棒性。Jin和Yin等[14]針對(duì)輪轂式電動(dòng)汽車(chē),提出了一種新的RBS和ABS協(xié)調(diào)制動(dòng)控制策略(如圖3所示)。首先為適應(yīng)制動(dòng)系統(tǒng)的強(qiáng)非線(xiàn)性、時(shí)變特征,設(shè)計(jì)了一個(gè)上層指數(shù)趨近率降低抖振的魯棒滑模控制器將車(chē)輪滑移控制在最佳范圍內(nèi)來(lái)以產(chǎn)生虛擬總的制動(dòng)轉(zhuǎn)矩,然后根據(jù)電池SOC、電機(jī)轉(zhuǎn)速和制動(dòng)強(qiáng)度等約束因素采用固定點(diǎn)法求解二次規(guī)劃的轉(zhuǎn)矩分配策略,將總的制動(dòng)轉(zhuǎn)矩動(dòng)態(tài)分配到RBS和ABS。NEDC工況仿真結(jié)果表明:該協(xié)調(diào)控制策略能在保證車(chē)輛制動(dòng)穩(wěn)定性的同時(shí)有效地提高制動(dòng)能量的回收效率,且具有較強(qiáng)的魯棒性。

圖3 基于轉(zhuǎn)矩分配的RBS與ABS協(xié)調(diào)制動(dòng)控制系統(tǒng)
2.1四輪獨(dú)立轉(zhuǎn)向系統(tǒng)
對(duì)于分布式獨(dú)立驅(qū)動(dòng)電動(dòng)汽車(chē)可以實(shí)現(xiàn)全輪獨(dú)立驅(qū)動(dòng)獨(dú)立轉(zhuǎn)向功能,其獨(dú)立轉(zhuǎn)向功能可以看成是傳統(tǒng)汽車(chē)四輪轉(zhuǎn)向技術(shù)的擴(kuò)展。但是電動(dòng)汽車(chē)具備更多、更靈活的轉(zhuǎn)向驅(qū)動(dòng)模式,能通過(guò)車(chē)輪轉(zhuǎn)向和驅(qū)動(dòng)協(xié)調(diào)控制顯著改善車(chē)輛的動(dòng)力性、操縱性和安全性,代表了未來(lái)高級(jí)電動(dòng)汽車(chē)的發(fā)展方向。針對(duì)分布式獨(dú)立驅(qū)動(dòng)電動(dòng)獨(dú)立轉(zhuǎn)向車(chē)輛的研究目前尚處于起步階段[18-21]。Yin等[19-20]在四輪轉(zhuǎn)向領(lǐng)域的研究成果具有廣泛的國(guó)際影響,其針對(duì)實(shí)際汽車(chē)行駛時(shí)承擔(dān)的不同載荷以及運(yùn)行狀態(tài)(如速度)的變化,設(shè)計(jì)了4ws汽車(chē)μ綜合控制閉環(huán)系統(tǒng)(如圖4所示),以橫擺角速度跟蹤反饋為控制邏輯,采用μ綜合魯棒控制器來(lái)抑制外部干擾,優(yōu)化權(quán)函數(shù),實(shí)現(xiàn)了傳統(tǒng)四輪轉(zhuǎn)向車(chē)輛控制器難以達(dá)到的性能指標(biāo)。仿真結(jié)果表明:所設(shè)計(jì)的綜合魯棒控制器不僅具有良好的操縱性和穩(wěn)定的魯棒性,即對(duì)外界干擾具有較好的抑制性能且不敏感于車(chē)輛參數(shù)變化,而且改善了以往控制器設(shè)計(jì)偏于保守的問(wèn)題。

圖4 4ws汽車(chē)μ綜合控制閉環(huán)系統(tǒng)
2.2直接橫擺穩(wěn)定性控制系統(tǒng)
與傳統(tǒng)汽車(chē)?yán)闷?chē)ABS不對(duì)稱(chēng)制動(dòng)來(lái)使車(chē)輛發(fā)生偏轉(zhuǎn)不同的是,分布式獨(dú)立驅(qū)動(dòng)電動(dòng)汽車(chē)是在發(fā)現(xiàn)車(chē)身在轉(zhuǎn)向時(shí)發(fā)生了甩尾、偏移等失穩(wěn)現(xiàn)象時(shí)直接利用輪轂電機(jī)的驅(qū)動(dòng)力矩分配來(lái)實(shí)現(xiàn)車(chē)輛的橫擺穩(wěn)定性控制,從而保證車(chē)輛正常的行駛姿態(tài)。對(duì)于分布式獨(dú)立驅(qū)動(dòng)電動(dòng)汽車(chē)直接橫擺穩(wěn)定性控制系統(tǒng)是電動(dòng)汽車(chē)研究學(xué)者包括國(guó)際車(chē)輛領(lǐng)域權(quán)威學(xué)者Hedrick J K, Masato Abe等最集中研究的問(wèn)題,近年來(lái)國(guó)內(nèi)外已經(jīng)有不少成果顯現(xiàn),如預(yù)測(cè)控制、滑模控制、魯棒控制、非線(xiàn)性控制等[3-4,7,22-23],其基本控制框架分兩層:上層控制器根據(jù)駕駛員命令確定總的直接橫擺力矩;下層控制器根據(jù)輪胎狀態(tài)實(shí)際分配電機(jī)轉(zhuǎn)矩。這里不做過(guò)多贅述,感興趣的讀者可以參考相關(guān)文獻(xiàn)。值得注意的是雖然不同的控制邏輯開(kāi)始被運(yùn)用,但是多數(shù)處于仿真研究階段,研究成果大多缺乏實(shí)車(chē)驗(yàn)證。
2.3其他橫向動(dòng)力學(xué)控制系統(tǒng)
其他四輪獨(dú)立驅(qū)動(dòng)電動(dòng)汽車(chē)橫向動(dòng)力學(xué)控制系統(tǒng)也主要是利用輪轂電機(jī)轉(zhuǎn)矩能獨(dú)立控制的優(yōu)點(diǎn),這里主要介紹電動(dòng)汽車(chē)電子差速系統(tǒng)。傳統(tǒng)汽車(chē)上的差速器是幫助車(chē)輛在轉(zhuǎn)彎過(guò)程中實(shí)現(xiàn)內(nèi)外圈車(chē)輪的差速,讓內(nèi)外車(chē)輪都能以純滾動(dòng)的形式轉(zhuǎn)動(dòng)。而四輪獨(dú)立驅(qū)動(dòng)電動(dòng)汽車(chē)輪轂電機(jī)與輪胎直接連接在一起,沒(méi)有了傳統(tǒng)汽車(chē)的機(jī)械減速器和差速裝置,所以四輪獨(dú)立驅(qū)動(dòng)電動(dòng)汽車(chē)的電子差速研究也是一個(gè)嶄新的課題。另外,在分布式驅(qū)動(dòng)電動(dòng)汽車(chē)正常直線(xiàn)行駛中,也需要考慮前后左右4個(gè)電機(jī)的轉(zhuǎn)速精確同步控制問(wèn)題。如果前后車(chē)輪速度不同,會(huì)造成車(chē)輛行駛系統(tǒng)(輪胎輪轂)的過(guò)度磨損;車(chē)輛在高速直線(xiàn)行駛時(shí),左右輪速的誤差會(huì)使車(chē)輛偏移目標(biāo)軌道,因此電動(dòng)汽車(chē)直線(xiàn)行駛的轉(zhuǎn)速精確同步可以看作是電子差速系統(tǒng)的特殊應(yīng)用,其國(guó)際研究文獻(xiàn)還不多見(jiàn)[24-26]。由于電動(dòng)汽車(chē)的各輪轉(zhuǎn)矩獨(dú)立可控,故電動(dòng)汽車(chē)電子差速主要研究方向是在A(yíng)ckerman-Jeantand模型的基礎(chǔ)上,通過(guò)算法對(duì)內(nèi)外輪胎的電機(jī)力矩進(jìn)行分配控制來(lái)實(shí)現(xiàn)輔助轉(zhuǎn)向。例如文獻(xiàn)[25]等設(shè)計(jì)四輪獨(dú)立驅(qū)動(dòng)電動(dòng)汽車(chē)驅(qū)動(dòng)輪轉(zhuǎn)矩比為
(1)
式中:u為車(chē)身質(zhì)心處速度;h為質(zhì)心到地面高度;g為重力加速度;d為輪距;δ為前輪轉(zhuǎn)角。從式(1)可以看到:電動(dòng)汽車(chē)驅(qū)動(dòng)轉(zhuǎn)矩比是根據(jù)車(chē)輛速度與前輪轉(zhuǎn)向角來(lái)確定的。在電子差速控制下,提高外側(cè)電機(jī)的驅(qū)動(dòng)力矩,減小內(nèi)側(cè)電機(jī)的驅(qū)動(dòng)力矩,從而使內(nèi)側(cè)和外側(cè)的電機(jī)力矩差值增大,同時(shí)內(nèi)外側(cè)輪胎的角速度差速也增大,進(jìn)而使電子差速系統(tǒng)可以有效幫助車(chē)輛完成轉(zhuǎn)向。
3.1車(chē)輛動(dòng)力學(xué)系統(tǒng)集成控制
分布式驅(qū)動(dòng)電動(dòng)汽車(chē)動(dòng)力學(xué)集成控制可以大致分成兩大類(lèi):第一大類(lèi)是從整車(chē)底盤(pán)動(dòng)力學(xué)集成角度考慮將縱向動(dòng)力學(xué)控制、橫向動(dòng)力學(xué)控制等子系統(tǒng)通過(guò)協(xié)調(diào)控制集成起來(lái),減少各子系統(tǒng)的功能干涉,從而最大程度地發(fā)揮各子系統(tǒng)功能以提高電動(dòng)汽車(chē)底盤(pán)動(dòng)力學(xué)的安全穩(wěn)定性。這一大類(lèi)的研究與傳統(tǒng)內(nèi)燃機(jī)車(chē)輛動(dòng)力學(xué)集成相比基本類(lèi)似[13,27-30]。例如文獻(xiàn)[27]等將非線(xiàn)性的模型預(yù)測(cè)應(yīng)用于底盤(pán)動(dòng)力學(xué)主動(dòng)轉(zhuǎn)向系統(tǒng)與直接橫擺系統(tǒng)的集成控制,其主要的集成控制框架如圖5所示。首先通過(guò)在線(xiàn)的非線(xiàn)性模型預(yù)測(cè)來(lái)確定主動(dòng)轉(zhuǎn)向角與總的直接橫擺力矩,然后通過(guò)制動(dòng)邏輯分配車(chē)輛的車(chē)輪執(zhí)行器;第二大類(lèi)是分布式驅(qū)動(dòng)電動(dòng)汽車(chē)獨(dú)特的研究方向,主要包括電動(dòng)汽車(chē)整車(chē)能量?jī)?yōu)化與容錯(cuò)控制策略。例如Junmin Wang等[31-32]就分布式驅(qū)動(dòng)電動(dòng)汽車(chē)整車(chē)效率進(jìn)行了深入的研究,其核心思想是根據(jù)輪轂電機(jī)的MAP效率圖,在路面行駛不同工況下,綜合考慮各驅(qū)動(dòng)電機(jī)的控制效能,針對(duì)電機(jī)的執(zhí)行器設(shè)計(jì)卡羅需-庫(kù)恩-塔克條件(KKT)全局最優(yōu)的能量消耗目標(biāo)函數(shù),進(jìn)而提高整車(chē)的驅(qū)動(dòng)效率,并用實(shí)車(chē)試驗(yàn)驗(yàn)證了該控制策略的有效性。由于電動(dòng)汽采用電傳線(xiàn)控系統(tǒng),驅(qū)動(dòng)電機(jī)一旦出現(xiàn)故障,整個(gè)車(chē)輛有可能失穩(wěn),同時(shí)由于整個(gè)電動(dòng)汽車(chē)還未完成市場(chǎng)化,還缺乏實(shí)際的車(chē)輛失效模式與故障案例,因此電動(dòng)汽車(chē)的故障建模與容錯(cuò)控制也是一個(gè)嶄新的課題,例如文獻(xiàn)[33]設(shè)計(jì)失效因子來(lái)簡(jiǎn)單處理電機(jī)故障,而文獻(xiàn)[34]采用最優(yōu)控制來(lái)設(shè)計(jì)容錯(cuò)控制律,但總的來(lái)說(shuō)目前該方向的研究文獻(xiàn)寥寥。

圖5 基于MPC的底盤(pán)集成控制框架
3.2車(chē)輛動(dòng)力學(xué)系統(tǒng)路面參數(shù)估計(jì)
對(duì)于電動(dòng)汽車(chē)無(wú)論是縱向動(dòng)力學(xué)控制系統(tǒng)(包括驅(qū)動(dòng)防滑動(dòng)力學(xué)控制系統(tǒng)與制動(dòng)動(dòng)力學(xué)控制系統(tǒng)),還是橫向動(dòng)力學(xué)系統(tǒng)(包括四輪獨(dú)立轉(zhuǎn)向系統(tǒng)與直接橫擺力矩控制系統(tǒng)),其動(dòng)力學(xué)的控制性能與路面附著條件有著極其緊密的聯(lián)系,因此能否準(zhǔn)確、實(shí)時(shí)估計(jì)路面利用附著系數(shù)直接影響著電動(dòng)汽車(chē)動(dòng)力學(xué)控制系統(tǒng)的有效性。目前根據(jù)測(cè)量方法和測(cè)量參數(shù)的不同可以將路面附著系數(shù)估算方法歸納為Cause-based和Effect-based兩種[35-43,45]。Cause-based方法是測(cè)量對(duì)路面附著系數(shù)影響較大的一些因素,然后結(jié)合經(jīng)驗(yàn)來(lái)預(yù)測(cè)當(dāng)前路面附著系數(shù)。文獻(xiàn)[35-36,40]是利用光學(xué)傳感器測(cè)量路面對(duì)光的吸收和反射情況,以此判斷能降低路面附著系數(shù)的物質(zhì),從而判別路面附著系數(shù)的變化情況。但由于傳感器測(cè)量的光信號(hào)中含有許多干擾信號(hào),因此進(jìn)行濾波將有很大困難,路面附著系數(shù)的估計(jì)值有一定程度的失真。隨著光學(xué)的發(fā)展和光學(xué)傳感器的不斷改進(jìn),近年來(lái)出現(xiàn)了采用毫米波和雷達(dá)波對(duì)路面進(jìn)行識(shí)別的方法。該方法是通過(guò)一種光學(xué)裝置向路面發(fā)射電磁波,由微波傳感器接收這些經(jīng)路面反射的電磁波,對(duì)反射波的頻譜進(jìn)行分析,然后根據(jù)頻譜差異識(shí)別路面情況。以上方法需要加裝額外的光學(xué)傳感器,而這些傳感器往往都十分昂貴,這就增加了電動(dòng)汽車(chē)的使用成本,不利于電動(dòng)汽車(chē)的商業(yè)化發(fā)展,同時(shí)這種方法的精確程度與經(jīng)驗(yàn)有很大關(guān)系,否則不能對(duì)路面進(jìn)行準(zhǔn)確的識(shí)別。Effect-based方法是利用電動(dòng)汽車(chē)的傳感器和動(dòng)力學(xué)系統(tǒng)方程對(duì)路面進(jìn)行實(shí)時(shí)識(shí)別。這種方法很大程度上依賴(lài)于動(dòng)力學(xué)方程的精確程度和算法的可靠性,所以成本較低。例如先利用算法估計(jì)車(chē)輛動(dòng)力學(xué)模型計(jì)算輪胎與路面之間的附著力,然后采用卡爾曼濾波或最小二乘法判斷當(dāng)前路面附著系數(shù)[37,41,43]。然而,如何發(fā)展路面附著系數(shù)的實(shí)時(shí)估計(jì)方法仍舊是值得深入研究的熱點(diǎn)。
本文分別從底盤(pán)縱向動(dòng)力學(xué)控制、橫向動(dòng)力學(xué)控制、集成動(dòng)力學(xué)控制等3方面對(duì)分布式驅(qū)動(dòng)電動(dòng)汽車(chē)動(dòng)力學(xué)控制研究進(jìn)展進(jìn)行了介紹,由于篇幅限制,對(duì)電動(dòng)汽車(chē)相關(guān)動(dòng)力學(xué)控制系統(tǒng)研究綜述還有待繼續(xù)深入,還有一些先進(jìn)的電動(dòng)汽車(chē)車(chē)輛動(dòng)力學(xué)控制系統(tǒng)(例如輪轂電機(jī)垂向懸架系統(tǒng)等)未進(jìn)行討論。盡管分布式驅(qū)動(dòng)電動(dòng)汽車(chē)底盤(pán)動(dòng)力學(xué)控制研究有了初步的進(jìn)展,但是國(guó)際在該領(lǐng)域的研究總體還處于起步階段,未來(lái)的研究發(fā)展趨勢(shì)有以下兩點(diǎn):
1) 更安全。電動(dòng)汽車(chē)全電動(dòng)化控制系統(tǒng)方便利用車(chē)載傳感器來(lái)感知車(chē)輛周?chē)h(huán)境,并根據(jù)感知所獲得的道路、車(chē)輛位置和障礙物信息,更容易精確控制車(chē)輛,從而使車(chē)輛能夠安全、可靠地在道路上自動(dòng)行駛,更易實(shí)現(xiàn)電動(dòng)汽車(chē)無(wú)人駕駛技術(shù),能為汽車(chē)沒(méi)有駕駛員或者無(wú)駕駛能力的人(如殘疾人)提供方便,更能在駕駛?cè)藛T技術(shù)不熟練、經(jīng)驗(yàn)不足、缺乏安全行車(chē)常識(shí),或在復(fù)雜道路行駛時(shí)遇有突然情況和發(fā)生操作錯(cuò)誤時(shí)減少人為失誤事故的發(fā)生數(shù)量,為人與車(chē)輛的安全提供保證。
2) 更智能。電動(dòng)汽車(chē)的車(chē)載網(wǎng)絡(luò)更易實(shí)現(xiàn)車(chē)聯(lián)網(wǎng)集成。車(chē)聯(lián)網(wǎng)將車(chē)與車(chē)相連、車(chē)與物相連,實(shí)現(xiàn)實(shí)時(shí)信息交換,通過(guò)車(chē)輛網(wǎng)絡(luò)動(dòng)態(tài)地收集分發(fā)和處理數(shù)據(jù),使用無(wú)線(xiàn)通信方式共享信息,能實(shí)現(xiàn)車(chē)與車(chē)、車(chē)與物的信息交換,將汽車(chē)與城市網(wǎng)絡(luò)相互連接,實(shí)現(xiàn)交通信息與實(shí)時(shí)導(dǎo)航服務(wù)、安全駕駛與車(chē)輛故障診斷、娛樂(lè)及通信服務(wù)。因此,汽車(chē)在車(chē)聯(lián)網(wǎng)的幫助下,將更加智能、更加人性化。
[1]HORI Y.Future vehicle driven by electricity and control-research on four-wheel-motored ‘UOT Electric March II’[J].IEEE Transactions on Industrial Electronics,2004,51(5):954-962.
[2]FLORESCU A,BRATU A I,MUNTEANU I.LQG Optimal Control Applied to On-Board Energy Management System of All-Electric Vehicles[J].IEEE Transactions on Control Systems Technology,2015,23(4):1427-1439.
[3]JIN X,YIN G.Robust Guaranteed Cost State-delayed Vehicle Lateral Stability Control with Applications to In-Wheel-Motor-Driven Electric Vehicles[C] //Proc Amer Control Conf.2015:5408-5413.
[4]GENG C,MOSTEFAI L,DENA M,et al.Direct yaw-moment control of an in-wheel-motored electric vehicle based on body slip angle fuzzy observer[J].IEEE Transactions on Industrial Electronics,2009,56(5):1411-1419.
[5]NAM K,FUJIMOTO H,HORI Y.Advanced motion control of electric vehicles based on robust lateral tire force control via active front steering[J].IEEE/ASME Transections on Mechatronics,2014,19(1):289-299.
[6]BERA T K,BHATTACHARYA K,SAMANTARAY A K.Bond graph model-based evaluation of a sliding mode controller for a combined regenerative and antilock braking system[J].Proceedings of the Institution of Mechanical Engineers,Part I:Journal of Systems and Control Engineering,2011,225(7):918-934.
[7]GOODARZI A,ESMAILZADEHE.Design of a VDC system for all-wheel independent drive vehicles[J].IEEE/ASME Trans.Mechatronics,2007,12(6):632-639.
[8]YIN G,WANG S,JIN X.Optimal Slip Ratio Based Fuzzy Control of Acceleration Slip Regulation for Four-Wheel Independent Driving Electric Vehicles[J].Mathematical Problems in Engineering,2013(11):1-7.
[9]XU K,XU G,LI W,et al.Anti-skid for Electric Vehicles Based on Sliding Mode Control with Novel Structure[C]//IEEE Internation Conference on Information and Automation.[S.l.]:IEEE,2011:650-655.
[10]WU L,GOU J,WANG L,et al.Acceleration Slip Regulation Strategy for Distributed Drive Electric Vehicles with Independent Front Axle Drive Motors[J].Energies,2015,8(5):4043-4072.
[11]XU P,CAO J,GUO G,et al.Torque coordinated control of independent driving electric vehicles base on BP neural network[C]// IEEE International Conference on Automation and Logistics.[S.l.]:IEEE,2008:710-714.
[12]周斯加,羅玉濤,黃向東,等.4WD電動(dòng)車(chē)的滑轉(zhuǎn)率識(shí)別及防滑控制[J].華南理工大學(xué)學(xué)報(bào)(自然科學(xué)版),2008,36(6):95-100.
[13]DE CASTRO R,ARAúJO R E,TANELLI M,et al.Torque blending and wheel slip control in EVs with in-wheel motors[J].Vehicle System Dynamics,2012,50(sup1):71-94.
[14]JIN X,YING.Coordinated braking control for In-Wheel-Motor-Driven Electric Vehicles with regenerative and antilock braking system based on Control Allocation[Z].The Dynamics of Vehicles on Roads and Tracks:Proceedings of the 24th Symposium of the International Association for Vehicle System Dynamics (IAVSD 2015)August 17-24,2015,Graz,Austria,pp.87-96.
[15]金賢建,殷國(guó)棟,陳南,等.混合動(dòng)力汽車(chē)回饋制動(dòng)與防抱死制動(dòng)協(xié)調(diào)魯棒控制[J].汽車(chē)工程,2015,37(9):1011-1016.
[16]WANG B,HUANG X,WANG J,et al.A robust wheel slip ratio control design combining hydraulic and regenerative braking systems for in-wheel-motors-driven electric vehicles[J].Journal of the Franklin Institute,2015,352(2):577-602.
[17]YU H,TAHERI S,DUAN J,et al.An Integrated Cooperative Antilock Braking Control of Regenerative and Mechanical System for a Hybrid Electric Vehicle Based on Intelligent Tire[J].Asian Journal of Control,2016,18(1):55-68.
[18]MARINO R,SCALZI S.Asymptotic sideslip angle and yaw rate decoupling control in four-wheel steering vehicles[J].Vehicle System Dynamics,2010,48(9):999-1019.
[19]YIN G,CHEN N,LI P.Improving handling stability performance of four-wheel steering vehicle via μ-synthesis robust control[J].Vehicular Technology,IEEE Transactions on,2007,56(5):2432-2439.
[20]殷國(guó)棟,陳南,李普.4WS 汽車(chē)橫擺角速度跟蹤μ綜合魯棒控制[J].機(jī)械工程學(xué)報(bào),2005,41(10):221-225.
[21]FAHIMI F.Full drive-by-wire dynamic control for four-wheel-steer all-wheel-drive vehicles[J].Vehicle System Dynamics,2013,51(3):360-376.
[22]CHEN Y,HEDRICK J K,GUO K.A novel direct yaw moment controller for in-wheel motor electric vehicles[J].Vehicle System Dynamics,2013,51(6):925-942.
[23]Suzuki Y,Kano Y,Abe M.A study on tyre force distribution controls for full drive-by-wire electric vehicle[J].Vehicle System Dynamics,2014,52(sup1):235-250.
[24]ZHAO Y,ZHANG J.Modelling and simulation of the electronic differential system for an electric vehicle with two-motor-wheel drive[J].International Journal of vehicle systems Modelling and Testing,2009,4(1/2):117-131.
[25]HARTANI K,BOURAHLA M,MILOUD Y,et al.Electronic differential with direct torque fuzzy control for vehicle propulsion system[J].Turkish Journal of Electrical Engineering & Computer Sciences,2009,17(1):21-38.
[26]OZKOP E,ALTAS I H,OKUMUS H I,et al.A fuzzy logic sliding mode controlled electronic differential for a direct wheel drive EV[J].International Journal of Electronics,2015,102(11):1919-1942.
[27]FALCONE P,TSENG H E,BORRELLIF,et al.MPC-based yaw and lateral stabilisation via active front steering and braking[J].Vehicle System Dynamics,2008,46(S1):611-628.
[28]SONG P,TOMIZUKA M,ZONG C.A novel integrated chassis controller for full drive-by-wire vehicles[J].Vehicle System Dynamics,2015,53(2):215-236.
[29]DI CAIRANO S,TSENG H E,BEMARDINI D,et al.Vehicle yaw stability control by coordinated active front steering and differential braking in the tire sideslip angles domain[J].IEEE Transactions on Control Systems Technology,2013,21(4):1236-1248.
[30]YANG X,WANG Z,PENG W.Coordinated control of AFS and DYC for vehicle handling and stability based on optimal guaranteed cost theory[J].Vehicle System Dynamics,2009,47(1):57-79.
[31]CHEN Y,WANG J.Design and experimental evaluations on energy efficient control allocation methods for overactuated electric vehicles:Longitudinal motion case[J].IEEE/ASME Transactions on Mechatronics,2014,19(2):538-548.
[32]CHEN Y,WANG J.Fast and global optimal energy-efficient control allocation with applications to over-actuated electric ground vehicles[J].IEEE Transactions on Control Systems Technology,2012,20(5):1202-1211.
[33]YANG H,COCQUEMPOT V,JIANG B.Optimal fault-tolerant path-tracking control for 4WS4WD electric vehicles[J].IEEE Transactions on Intelligent Transportation Systems,2010,11(1):237-243.
[34]IFEDI C J,MECROW B C,BROCKWAY S T M,et al.Fault-tolerant in-wheel motor topologies for high-performance electric vehicles[J].IEEE Transactions on Industry Applications,2013,49(3):1249-1257.
[35]HONG S,ERDOGAN G,HEDRICK K,et al.Tyre-road friction coefficient estimation based on tyre sensors and lateral tyre deflection:modelling,simulations and experiments[J].Vehicle System Dynamics,2013,51(5):627-647.
[36]LEE C,HEDRICK K,YI K.Real-time slip-based estimation of maximum tire-road friction coefficient[J].IEEE/ASME Transactions On Mechatronics,2004,9(2):454-458.[37]RAJAMANI R,PHANOMCHOENG G,PIYABONGKARN D,et al.Algorithms for real-time estimation of individual wheel tire-road friction coefficients[J].IEEE/ASME Transactions on Mechatronics,2012,17(6):1183-1195.[38]ENISZ K,SZALAY I,KOHLRUSZ G,et al.Tyre-road friction coefficient estimation based on the discrete-time extended Kalman filter[J].Proceedings of the Institution of Mechanical Engineers,Part D:Journal of Automobile Engineering,2015,229(9):1158-1168.
[39]JIN X,YIN G,LIN Y.Interacting Multiple Model Filter-Based Estimation of Lateral Tire-Road Forces for Electric Vehicles[M].[S.l.]:SAE Technical Paper,2014.
[40]ERDOGAN G,ALEXANDER L,RAJAMANI R.Estimation of tire-road friction coefficient using a novel wireless piezoelectric tire sensor[J].IEEE Sensors Journal,2011,11(2):267-279.
[41]褚文博,羅禹貢,陳龍,等.分布式電驅(qū)動(dòng)車(chē)輛的無(wú)味粒子濾波狀態(tài)參數(shù)聯(lián)合觀(guān)測(cè)[J].機(jī)械工程學(xué)報(bào),2013,49(24):117-127.
[42]宋健,楊財(cái),李紅志,等.AYC 系統(tǒng)基于多傳感器數(shù)據(jù)融合的路面附著系數(shù)估計(jì)算法[J].清華大學(xué)學(xué)報(bào)(自然科學(xué)版),2009,49(5):715-718.
[43]RAJAMANI R,PIYABONGKARN D,LEW J Y,et al.Tire-road friction-coefficient estimation[J].IEEE Control Systems,2010,30(4):54-69.
[44]YIN G,JIN X.Cooperative Control of Regenerative Braking and Antilock Braking for a Hybrid Electric Vehicle[J].Mathematical Problems in Engineering,2013(4):1-9.
[45]YIN G,JIN X,QING Z,et al.Lateral Stability Region Conservativeness Estimation and Torque Distribution for FWIA Electric Vehicle Steering[J].Sciences China Technological Sciences,2015,58(4):669-676.
(責(zé)任編輯劉舸)
Overview for Chassis Vehicle Dynamics Control of Distributed Drive Electric Vehicle
YIN Guo-dong1, JIN Xian-jian1, ZHANG Yun1, 2
(1.School of Mechanical Engineering, Southeast University, Nanjing 211189,China;2.Ford Motor Research & Engineering(Nanjing) Co., Ltd., Nanjing 211100,China)
The motors of distributed drive electric vehicle will be placed directly in the rim, which greatly simplify the structure of the vehicle chassis and improve efficiency on energy, moreover, wheel motors can accurately measure hub torque and possess rapid response in the driving torque so as to provide a great convenience for improving security and stability of the vehicle chassis dynamics control systems. This paper reviewed the vehicle chassis dynamics control in term of longitudinal dynamics control, lateral dynamics control and integrated dynamics control, and focused on these emerging hotspots including acceleration slip regulation, regenerative and anti-lock braking system, four wheel steer, direct yaw moment control, electronic differential system in chassis dynamics control for distributed drive electric vehicle, and then made several forecasts about research directions of the distributed drive electric vehicle’s dynamics control in the future.
distributed drive electric vehicle;longitudinal dynamics;lateral dynamics; parameter estimation;integrated dynamics control
2016-04-21
國(guó)家自然科學(xué)基金資助項(xiàng)目(51575103);東南大學(xué)杰青培育基金項(xiàng)目(2242016K41056);江蘇省六大人才高峰培養(yǎng)計(jì)劃(2014-JXQC-001)
殷國(guó)棟(1976—),男,博士,教授,博士生導(dǎo)師,東南大學(xué)機(jī)械工程學(xué)院副院長(zhǎng),主要從事新能源汽車(chē)整車(chē)設(shè)計(jì)與系統(tǒng)估計(jì)及控制、智能網(wǎng)聯(lián)汽車(chē)、車(chē)輛動(dòng)力學(xué)及其控制等方面研究,E-mail:ygd@seu.edu.cn。
format:YIN Guo-dong, JIN Xian-jian, ZHANG Yun.Overview for Chassis Vehicle Dynamics Control of Distributed Drive Electric Vehicle[J].Journal of Chongqing University of Technology(Natural Science),2016(8):13-19.
10.3969/j.issn.1674-8425(z).2016.08.002
U461.3
A
1674-8425(2016)08-0013-07
引用格式:殷國(guó)棟,金賢建,張?jiān)?分布式驅(qū)動(dòng)電動(dòng)汽車(chē)底盤(pán)動(dòng)力學(xué)控制研究綜述[J].重慶理工大學(xué)學(xué)報(bào)(自然科學(xué)),2016(8):13-19.