智能小車(chē)外文翻譯

1、窗體頂端 2015屆畢業(yè)設(shè)計(jì)（論文） 外文翻譯 院 、 部： 電氣與信息工程學(xué)院 學(xué)生姓名： 指導(dǎo)教師： 職 稱(chēng)： 講師 專(zhuān) 業(yè)： 通信工程 班 級(jí)： 學(xué) 號(hào)： 2015年 6 月車(chē)輛動(dòng)態(tài)避障控制器的發(fā)展窗體頂端窗體底端Geraint Paul Bevan美國(guó)俄亥俄州立大學(xué)摘 要安全在汽車(chē)行業(yè)依然占據(jù)著越來(lái)越重要的地位，有了重要意義的研究和進(jìn)展在封閉線(xiàn)路控制系統(tǒng)領(lǐng)域。為了防止車(chē)輪因急剎車(chē)或低摩擦轉(zhuǎn)向失控,最先開(kāi)始使用防抱死制動(dòng)系統(tǒng)（ABS）。車(chē)輛動(dòng)態(tài)控制進(jìn)一步發(fā)展包括牽引力控制：系統(tǒng)即最佳分配牽引力，并防止過(guò)度車(chē)輪打滑。最近的發(fā)展已經(jīng)在電子穩(wěn)定控制（ESC）的區(qū)域得到應(yīng)用。如今汽車(chē)技術(shù)已經(jīng)發(fā)展

2、了多年，ABS和ESC正在成為對(duì)大多數(shù)車(chē)輛的標(biāo)準(zhǔn)，不僅汽車(chē)制造商，還有各國(guó)政府和監(jiān)管機(jī)構(gòu)的標(biāo)準(zhǔn)有專(zhuān)門(mén)的程序，以確保標(biāo)準(zhǔn)和了解這些系統(tǒng)的局限性。其結(jié)果是，所做出的努力已經(jīng)完成開(kāi)發(fā)測(cè)試系統(tǒng)和測(cè)試機(jī)動(dòng)量化動(dòng)態(tài)屬性。這項(xiàng)研究的重點(diǎn)是研究標(biāo)準(zhǔn)試行、開(kāi)發(fā)新的戰(zhàn)略評(píng)估和配備了現(xiàn)代車(chē)輛動(dòng)態(tài)控制系統(tǒng)。 在過(guò)去十年里，另一個(gè)有重要意義的發(fā)展是自主（或無(wú)人）車(chē)輛。自主車(chē)輛的一個(gè)重要應(yīng)用是自動(dòng)化無(wú)人車(chē)輛測(cè)試，它代替了人類(lèi)進(jìn)行車(chē)輛測(cè)試。這增加可靠性和測(cè)試試行的可重復(fù)性，這是及其重要的在一些專(zhuān)門(mén)的試行中。大多數(shù)車(chē)輛動(dòng)態(tài)測(cè)試包括精確動(dòng)方向盤(pán)或剎車(chē)/油門(mén)踏板，轉(zhuǎn)向控制器和制動(dòng)機(jī)器人被設(shè)計(jì)努力做到這一點(diǎn)。SEA有限責(zé)

3、任公司設(shè)計(jì)出這樣的系統(tǒng)和被OSU研究人員廣泛的應(yīng)用，自動(dòng)化無(wú)人車(chē)輛測(cè)試已經(jīng)被證明可以準(zhǔn)確地執(zhí)行各種標(biāo)準(zhǔn)測(cè)試，還有適用范圍廣的車(chē)輛，也可用于由各種組織世界各地。車(chē)輛動(dòng)態(tài)控制和自主車(chē)輛在這一研究領(lǐng)域結(jié)合在一起;自動(dòng)化測(cè)試驅(qū)動(dòng)程序開(kāi)發(fā)應(yīng)用于執(zhí)行路徑跟蹤軍事試行評(píng)估車(chē)輛動(dòng)態(tài)控制器的性能，包括那些使用ESC的逃避駕駛狀況的汽車(chē)。 在回避演練的輪胎力不再打滑的線(xiàn)性函數(shù)角和所述車(chē)輛的響應(yīng)是非線(xiàn)性的和潛在不穩(wěn)定的，其中一個(gè)條件活性穩(wěn)定系統(tǒng)被設(shè)計(jì)為減輕。不足梯度的線(xiàn)性范圍的定義不適合于非線(xiàn)性動(dòng)態(tài)范圍的分析。這項(xiàng)研究的另一個(gè)重點(diǎn)是基于估計(jì)輪胎力，以評(píng)估穩(wěn)定性和可控性。車(chē)輛觀察員要專(zhuān)為檢測(cè)和測(cè)量轉(zhuǎn)向不足的動(dòng)態(tài)試行。

4、該方法可用于基準(zhǔn)不論被動(dòng)或主動(dòng)控制的車(chē)輛。 作為自主轉(zhuǎn)向控制問(wèn)題的延伸，該項(xiàng)目涉及研究中的應(yīng)用主動(dòng)轉(zhuǎn)向系統(tǒng)的車(chē)輛穩(wěn)定性控制的?？刂扑惴ㄩ_(kāi)發(fā)使用信息從輪胎力估計(jì)和駕駛意圖車(chē)型得到由主動(dòng)轉(zhuǎn)向系統(tǒng)線(xiàn)性和可預(yù)測(cè)的車(chē)輛側(cè)向響應(yīng)。 本研究匯集自動(dòng)化測(cè)試驅(qū)動(dòng)程序的開(kāi)發(fā)，活性車(chē)輛運(yùn)動(dòng)控制系統(tǒng)和檢測(cè)動(dòng)態(tài)穩(wěn)定性通過(guò)使用輪胎力估計(jì)。第1簡(jiǎn)介1.1簡(jiǎn)介與動(dòng)機(jī) 自主車(chē)在汽車(chē)技術(shù)上的重大進(jìn)步技術(shù)。大量的無(wú)人地面車(chē)輛研究方案已經(jīng)在各級(jí)政府，研究機(jī)構(gòu)以及學(xué)院展開(kāi)研究。這些研究包括自動(dòng)公路研究，其中自主公路主要應(yīng)用于乘用車(chē)鋪設(shè)道路和無(wú)人駕駛越野駕駛，如DARPA地面大挑戰(zhàn)。自主車(chē)中另一個(gè)非常重要的應(yīng)用是自動(dòng)化無(wú)人駕駛測(cè)試，這是

5、無(wú)人車(chē)代替人類(lèi)進(jìn)行車(chē)輛測(cè)試，無(wú)人測(cè)試得到的可靠的結(jié)果是提高了可靠性和測(cè)試試行的重復(fù)性。安全在汽車(chē)設(shè)計(jì)中占據(jù)了非常重要的地位，動(dòng)態(tài)測(cè)試受到了很多人的關(guān)注。 大多數(shù)車(chē)輛動(dòng)態(tài)測(cè)試都涉及到方向盤(pán)或剎車(chē)/油門(mén)踏板的動(dòng)作準(zhǔn)確性。轉(zhuǎn)向系統(tǒng)控制器和制動(dòng)機(jī)器人被設(shè)計(jì)來(lái)做到這一點(diǎn)。SEA有限責(zé)任公司設(shè)計(jì)出這樣的系統(tǒng)和被OSU研究人員廣泛的應(yīng)用，已經(jīng)被證明準(zhǔn)確地執(zhí)行各種標(biāo)準(zhǔn)測(cè)試，適用范圍廣的車(chē)輛，也可用于由各種組織世界各地。這項(xiàng)研究的重點(diǎn)是自動(dòng)化測(cè)試驅(qū)動(dòng)開(kāi)發(fā)（ATD）（轉(zhuǎn)向控制和制動(dòng)，油門(mén)機(jī)器人（BTR），以及延長(zhǎng)ATD的適用性進(jìn)行動(dòng)態(tài)路徑跟蹤試行和變速測(cè)試。窗體底端窗體頂端1.2目的和范圍 如今汽車(chē)技術(shù)已經(jīng)發(fā)展了

6、多年，ABS和ESC正在成為對(duì)大多數(shù)車(chē)輛的標(biāo)準(zhǔn)，不僅汽車(chē)制造商，還用各國(guó)政府和監(jiān)管機(jī)構(gòu)的標(biāo)準(zhǔn)有專(zhuān)門(mén)的程序，以確保標(biāo)準(zhǔn)和了解這些系統(tǒng)的局限性。其結(jié)果是，所做出的努力來(lái)已經(jīng)完成開(kāi)發(fā)測(cè)試系統(tǒng)和測(cè)試機(jī)動(dòng)量化動(dòng)態(tài)屬性。這項(xiàng)研究的重點(diǎn)是研究標(biāo)準(zhǔn)試行和開(kāi)發(fā)新的戰(zhàn)略評(píng)估和配備了現(xiàn)代車(chē)輛動(dòng)態(tài)控制系統(tǒng)。 該項(xiàng)目的目標(biāo)是開(kāi)發(fā)測(cè)試系統(tǒng)，該測(cè)試系統(tǒng)用于自主車(chē)輛測(cè)試。一個(gè)測(cè)試信號(hào)將被設(shè)計(jì)來(lái)評(píng)估現(xiàn)代汽車(chē)車(chē)輛的穩(wěn)定性和車(chē)輛動(dòng)態(tài)控制器的有效性。在不足轉(zhuǎn)向梯度提供有用的信息對(duì)車(chē)輛方向的穩(wěn)定性，在線(xiàn)性范圍,它并沒(méi)有提供一個(gè)完整的圖片,因?yàn)樗雎粤朔蔷€(xiàn)性范圍。在規(guī)避機(jī)動(dòng)的輪胎力量不再是線(xiàn)性函數(shù)滑動(dòng)角和車(chē)輛非線(xiàn)性響應(yīng)和潛在不穩(wěn)定,一個(gè)

7、條件活躍的穩(wěn)定系統(tǒng)旨在減輕。 在避讓操作的輪胎力不再滑移角的線(xiàn)性函數(shù)和該車(chē)輛的響應(yīng)是非線(xiàn)性的和潛在的不穩(wěn)定性，其中活性穩(wěn)定系統(tǒng)被設(shè)計(jì)為減輕的病癥。新的參數(shù)，提出了研究中定義來(lái)衡量汽車(chē)的動(dòng)力不足，轉(zhuǎn)向過(guò)度的狀態(tài)。這項(xiàng)研究的另一個(gè)重點(diǎn)是基于估計(jì)輪胎力，以評(píng)估穩(wěn)定性和可控性。車(chē)輛觀測(cè)的目的是檢測(cè)和測(cè)量轉(zhuǎn)向不足indynamic試行。這種方法可用于基準(zhǔn)不論被動(dòng)或主動(dòng)控制的車(chē)輛：性能評(píng)估將基于在輪胎開(kāi)發(fā)的橫向力，而不是僅在車(chē)輛的傳統(tǒng)的可測(cè)量狀態(tài)。車(chē)輛的操控性能將與支配車(chē)輛運(yùn)動(dòng)輪胎和路面之間的力的知識(shí)。方法將開(kāi)發(fā)在試運(yùn)行的基礎(chǔ)比較力量來(lái)評(píng)估ESC的有效性。第二章2.1 介紹窗體頂端 為了響應(yīng)嚴(yán)重的交通事故

8、，在過(guò)去的幾年里，一個(gè)新的研究重點(diǎn)出現(xiàn)了，這個(gè)研究是關(guān)于車(chē)輛動(dòng)態(tài)測(cè)試的。汽車(chē)制造商、政府機(jī)構(gòu)和消費(fèi)群體已經(jīng)計(jì)劃致力于開(kāi)發(fā)和評(píng)估車(chē)輛穩(wěn)定性和安全性的優(yōu)點(diǎn)。 NHTSA包括防碰撞，垃圾再利用和生物力學(xué)等領(lǐng)域。防撞類(lèi)別涉及包括翻車(chē)測(cè)試，旋轉(zhuǎn)，制動(dòng)性能等。大多數(shù)測(cè)試程序都存在有有用的關(guān)車(chē)輛穩(wěn)定性的信息。一些操作輸入將被稱(chēng)為“開(kāi)環(huán)”。還有一些需要?jiǎng)x車(chē)油門(mén)驅(qū)動(dòng)縱向動(dòng)力學(xué)研究測(cè)試。另一個(gè)類(lèi)別的演練涉及關(guān)于路徑跟隨。一個(gè)ATD可以執(zhí)行不僅是開(kāi)環(huán)測(cè)試，也可以在預(yù)期的路徑和預(yù)期的速度測(cè)試駕駛車(chē)輛。這種演練被稱(chēng)為閉環(huán)（相對(duì)于到位置和速度），并且是該研究的焦點(diǎn)。2.1.1車(chē)輛穩(wěn)定性 成千上萬(wàn)的互聯(lián)網(wǎng)短語(yǔ)搜索結(jié)果顯示“

9、翻車(chē)”。翻車(chē)事故是被討論的最多的在車(chē)禍報(bào)道。不需要太多的數(shù)據(jù)，一個(gè)統(tǒng)計(jì)是值得一提的：大約三分之一的美國(guó)交通死亡事故涉及單車(chē)翻車(chē)。側(cè)翻事故通常是基于各種汽車(chē)開(kāi)環(huán)測(cè)試；J-Turn和NHTSA魚(yú)鉤（滾動(dòng)速度反饋魚(yú)鉤機(jī)動(dòng)）1。在演練時(shí)必須嚴(yán)格檢查車(chē)輛的兩輪升降（TWL）頻率。這些,以及各種ISO試行,消費(fèi)者聯(lián)盟的雙車(chē)道改變和大量的汽車(chē)制造商具體操作分為動(dòng)態(tài)測(cè)試的范疇。靜態(tài)類(lèi)型的翻轉(zhuǎn)是指基于測(cè)量的靜態(tài)穩(wěn)定性因素,傾斜角度和至關(guān)重要的滑動(dòng)速度可分為靜態(tài)測(cè)試的范疇。一般后者不包括瞬態(tài)輪胎行為、懸架的運(yùn)動(dòng)效果、順應(yīng)性、穩(wěn)定性控制器的影響。其他側(cè)翻指標(biāo)已經(jīng)被調(diào)查在側(cè)翻預(yù)警和防側(cè)翻預(yù)警算法的基礎(chǔ)上。陳等人提出了

10、競(jìng)技場(chǎng)指標(biāo)來(lái)預(yù)測(cè)即將發(fā)生的翻轉(zhuǎn)。越野車(chē)的翻車(chē)難以從一個(gè)或一個(gè)動(dòng)態(tài)試行動(dòng)作去感知。第三章 本章概述了一些重要的車(chē)輛狀態(tài)和在文獻(xiàn)中討論他們的估計(jì)方法。這個(gè)卡爾曼濾波器將被解釋和應(yīng)用于估計(jì)輪胎強(qiáng)度。進(jìn)行討論輪胎強(qiáng)度評(píng)估的重要性以及它如何可以用來(lái)提供車(chē)輛操作狀態(tài)有用信息。接下來(lái)的章節(jié)將討論主動(dòng)穩(wěn)定控制和路徑跟隨算法。 閉環(huán)車(chē)輛動(dòng)力學(xué)控制的有效性依靠于對(duì)車(chē)輛的狀態(tài)準(zhǔn)確的了解。一些數(shù)據(jù)關(guān)于偏航率、橫向加速度、車(chē)輪速度等，可以很容易的被傳感器測(cè)量。另外的狀態(tài)車(chē)輛側(cè)滑、縱向速度等，被使用其他方法估算著包括測(cè)量信號(hào)、車(chē)輛動(dòng)態(tài)模型和其他復(fù)雜的工具。一些狀態(tài)經(jīng)常被獲得經(jīng)過(guò)直接測(cè)量信號(hào)的集成-過(guò)程中容易出錯(cuò),對(duì)干擾高

11、度敏感。另外的方法獲得依賴(lài)狀態(tài)信息包括融合不同的傳感器和結(jié)合不同個(gè)體傳感器獲得的測(cè)量系統(tǒng)。最近的事態(tài)發(fā)展使用嵌入式處理器已經(jīng)成為可能，結(jié)合使用使用計(jì)算密集型的卡爾曼濾波器和各種傳感器等方法建立數(shù)學(xué)模型完成實(shí)時(shí)狀態(tài)估計(jì)。3.1狀態(tài)和估計(jì)方法 了解車(chē)輛狀態(tài)是穩(wěn)定控制系統(tǒng)必要的工作。偏航率和橫向加速度可以通過(guò)便宜的傳感器測(cè)量。其他參數(shù)例如側(cè)滑角、橫搖角和輪胎部隊(duì)等，不容易通過(guò)其他方法測(cè)量。在當(dāng)前穩(wěn)定系統(tǒng)的汽車(chē)生產(chǎn)中各種個(gè)樣的算法已經(jīng)被討論和錄用。直接集成慣性傳感器信號(hào)的累積誤差時(shí)間是不現(xiàn)實(shí)的。更復(fù)雜的方法包括融合傳感器的數(shù)據(jù) ，GPS子系統(tǒng)和車(chē)輛動(dòng)力學(xué)模型來(lái)更好地估計(jì)無(wú)法估量的狀態(tài)。接下來(lái)是一個(gè)簡(jiǎn)明

12、的討論關(guān)于感興趣的各種信號(hào)和用于估量他們的系統(tǒng)。3.1.1側(cè)滑 側(cè)滑可以結(jié)合慣性導(dǎo)航系統(tǒng)和全球定位系統(tǒng)(GPS)信號(hào)進(jìn)行預(yù)測(cè)。GPS提供絕對(duì)的前進(jìn)方向標(biāo)志和速度相對(duì)較慢的速度測(cè)量，結(jié)合慣性傳感器。從慣性導(dǎo)航系統(tǒng)得到絕對(duì)的GPS航向和速度測(cè)量消除錯(cuò)誤反之,慣性導(dǎo)航系統(tǒng)的GPS測(cè)量傳感器可以提供更高的更新的車(chē)輛的狀態(tài)。無(wú)論如何，在城市駕駛環(huán)境，機(jī)械計(jì)裝故障錯(cuò)誤，可能導(dǎo)致GPS信號(hào)丟失，最終導(dǎo)致錯(cuò)誤的估計(jì)。有一種方法研究出來(lái)預(yù)算側(cè)滑而不需要GPS。而不是一個(gè)組合測(cè)量值， 3軸陀螺儀,3軸加速度計(jì)和車(chē)輛數(shù)學(xué)模型用于估算側(cè)滑。 在生產(chǎn)的電動(dòng)助力轉(zhuǎn)向系統(tǒng)車(chē)輛提供了另一種側(cè)滑估算方法。轉(zhuǎn)矩的絕對(duì)測(cè)量可以從車(chē)

13、輛側(cè)滑角估計(jì)。轉(zhuǎn)向力矩直接關(guān)系到外側(cè)輪胎強(qiáng)度，輪流依賴(lài)側(cè)滑角度和車(chē)輛狀態(tài)。轉(zhuǎn)向角和角速度傳感器都是廉價(jià)的和結(jié)合現(xiàn)已裝備好穩(wěn)定控制系統(tǒng)。一個(gè)觀察干擾者根據(jù)轉(zhuǎn)向系統(tǒng)模型估計(jì)輪胎調(diào)整的時(shí)刻;這個(gè)估計(jì)成為測(cè)量車(chē)輛側(cè)滑狀態(tài)的一部分觀測(cè)器和偏航率。3.1.2傾側(cè)角和道路傾斜角度 傾側(cè)角和道路傾斜角度作為不良干擾因素破壞于加速度測(cè)量?jī)x器和可靠的橫向加速度與橫向速度(或估計(jì)側(cè)滑角)。許多研究人員強(qiáng)調(diào)傾側(cè)角和道路傾斜角度對(duì)于穩(wěn)定性控制系統(tǒng)的重要性?；谶@些研究，本文提出了一種新的識(shí)別傾側(cè)角和汽車(chē)搖晃的方法，該方法使用擾動(dòng)觀測(cè)器和動(dòng)態(tài)模型。首先,介紹了一個(gè)包括車(chē)輛搖晃狀態(tài)和道路傾斜干擾的動(dòng)態(tài)模型。這個(gè)擾動(dòng)觀測(cè)器的

14、用于擾動(dòng)觀測(cè)，側(cè)滑角、偏航率,滾轉(zhuǎn)率和車(chē)輛傾斜角(傾側(cè)角和道路傾斜角度的總和）。汽車(chē)的偏航率和滾轉(zhuǎn)角速度的很容易使用速率陀螺儀測(cè)量。利用GPS和INS可以準(zhǔn)確測(cè)量車(chē)輛側(cè)滑角和傾斜角。從擾動(dòng)觀測(cè)器可以分別估計(jì)道路傾斜角度和車(chē)輛搖晃程度。附件2：外文原文 Development of an Autonomous Test Driver and Strategies for Vehicle DynamicsTesting and Lateral Motion ControlDissertationPresented in Partial Fulfillment of the Requirements

15、 forthe Degree Doctor of Philosophy in theGraduate School of the Ohio State UniversityByAnmol Sidhu, M.S. Mechanical Engineering Graduate ProgramThe Ohio State University2010 As safety continues to take an increasingly important place in the automobile industry, there has been significant research a

16、nd development in the area of closed loop control of vehicle dynamics. It first started with antilock brake systems (ABS) thatprevented loss of steering control due to wheels locking up with hard braking or lowfriction. Vehicle dynamics control further developed to include traction control: a system

17、that optimally distributes tractive forces and prevents excessive wheel slip. The most recent developments have been in the area of electronic stability control (ESC). As vehicle technology has evolved over the years and ABS and ESC are now becoming standard on most vehicles, not only automobile man

18、ufacturers but even governments and regulation bodies have programs dedicated to ensure standards and understand limitations of these systems. As a result, efforts have been made to develop testing systems and test maneuvers to quantify dynamic properties. This research focuses on studying standard

19、maneuvers and developing new strategies to evaluate and rate the performance of modern vehicles equipped with advanced vehicle dynamic control systems. Another significant development of the last decade is autonomous (or unmanned) vehicles. An important application of autonomous vehicles is automate

20、d test drivers, which are systems that replace human drivers in vehicle dynamic testing. This increases the reliability and repeatability of test maneuvers, which is imperative for dependable results in some specialized maneuvers. Most vehicle dynamic tests involve precise actuation of steering whee

21、l or brake/throttle pedals. Steering controllers and braking robots are designed to do just that. One such system designed by SEA, Ltd and used extensively by OSU researchers, has been demonstrated to perform various standard tests accurately for a wide range of vehicles and is also used by various

22、organizations worldwide. In this research the areas of vehicle dynamics control and autonomous vehicles come together; the automated test driver is developed to execute path-following maneuvers to evaluate the performance of vehicle dynamics controllers, including those used in ESC, in evasive drivi

23、ng situations. During evasive maneuvers the tire forces are no longer a linear function of slip angles and the vehicle response is nonlinear and potentially unstable, a condition which the active stability systems are designed to mitigate. The definition of understeer gradient in the linear-range do

24、es not lend itself to analysis of nonlinear-range dynamics. Another focus of this research is to assess stability and controllability based on estimation of tire forces. A vehicle observer is designed for the purpose of detecting and measuring understeer and oversteer in dynamic maneuvers. The metho

25、d can be used to benchmark a vehicle regardless of passive or active control.As an extension of the autonomous steering control problem, this project involves the study of application of active steering for vehicle stability control. Control algorithms are developed that use the information from tir

26、e force estimator and driver intent models to yield linearized and predictable vehicle lateral response by an active steering system. This research brings together the development of an automated test driver, active vehicle motion control systems and testing for dynamic stability by using tire force

27、 estimation.1.1 Introduction and Motivation Autonomous vehicles are a major technological advancement in automobiletechnology. Numerous research programs have been undertaken by various governments,research organizations and institutes towards development of unmanned ground vehicles.These include Au

28、tomated highway research where autonomy is applied to passenger carsto drive on paved roads and unmanned off road driving such as the DARPA grand challenge. Another very important application of autonomy in vehicles is automated test drivers which are systems that replace human drivers in vehicle dy

29、namic testing. This increases the reliability and repeatability of test maneuvers which is imperative for dependable results. As safety takes an important place in vehicle design, testing for dynamic response has gained significant attention. Most vehicle dynamic tests involve precise actuation of s

30、teering wheel or brake/throttle pedals. Steering controllers and braking robots are designed to do just that. One such system designed by SEA, Ltd and used extensively by OSU researchers, has been demonstrated to perform various standard tests accurately for a range of vehicles and is also used by v

31、arious organizations worldwide. This research is focused on development of the Automated Test Driver (ATD) (steering control and brake-throttle robot (BTR) as well as extending the applicability of the ATD for dynamic path following maneuvers and variable speed tests. 1.2 Purpose and Scope Vehicle t

32、echnology has evolved over the years and ABS and ESC are now becoming standard on most vehicles. Furthermore, not only automobile manufacturers but even governments and regulation bodies have programs dedicated to ensure standards and understand limitations of these systems. As a result, efforts hav

33、e been made to develop test maneuvers to quantify dynamic properties. This research focuses on studying standard maneuvers and developing new strategies to evaluate and rate the performance of modern vehicles equipped with advanced vehicle dynamic control systems. The goal of this project is to deve

34、lop testing methodologies to test vehicle dynamics using an automated test driver. A test signal will be designed to evaluate vehicle stability and effectiveness of vehicle dynamic controllers of modern vehicles.Where understeer gradient provides useful information about vehicle directional stabilit

35、y in the linear range, it does not provide a complete picture because it ignores the nonlinearrange. During evasive maneuvers the tire forces are no longer a linear function of slip angles and the vehicle response is nonlinear and potentially unstable, a condition which the active stability systems

36、are designed to mitigate. New parameters are proposed in this study defined to measure a vehicles dynamic understeer-oversteer state. Another focus of this research is to assess stability and controllability based on estimation of tire forces. A vehicle observer is designed to detect and measure und

37、ersteer and oversteer in dynamic maneuvers. This method can be used to benchmark a vehicle regardless of passive or active control: evaluation of performance will be based on the lateral forcesdeveloped at the tires and not only on traditional measurable states of the vehicle. Vehicle handling chara

38、cteristics will be related to the knowledge of forces between the tires and road that govern vehicle motion. Methodology will be developed to evaluate effectiveness of ESC by comparing the forces in a test run to the baseline. CHAPTER 2VEHICLE DYNAMICS TESTING2.1 Introduction In response to statisti

39、cs of severe vehicle crashes, a new focus on vehicle dynamic testing has emerged in the past few years. Auto manufacturers, government agencies and consumer groups, have programs dedicated to developing maneuvers to evaluate vehicle stability and safety merits. NHTSA covers the areas of crash avoida

40、nce, crash worthiness,and biomechanics. The category of crash avoidance involves testing for roll-over, spin outs, braking performance, etc. Numerous test procedures exist, which yield useful information about vehicle stability. Some involve steering inputs and will be referred to as “Open loop”. Th

41、ere are also tests that require brake-throttle actuation to study longitudinal dynamics. Another category of maneuvers is the one involving pathfollowing. An ATD can perform not only open-loop tests but can drive a vehicle on a desired path at desired speed. Such maneuvers are referred to as closed-

42、loop (with respect to position and speed) and are the focus of this research.2.1.1 Vehicle Roll Stability Hundreds of thousands of results show up on the Internet from the search phrase,“Vehicle rollover”. Rollover accidents are the most discussed in vehicle crash reports.Without getting into much d

43、etail, one statistic is worth mentioning; roughly one-third oftraffic fatalities in the US involve single-vehicle rollovers. Rollover propensity of vehicles is typically rated based on various open loop tests namely; J-Turn and NHTSA Fishhook (Roll rate feedback fishhook maneuver) 1. Severity and fr

44、equency of vehicle Two-Wheel-Lift (TWL) is examined under these maneuvers. These, as well as various ISO maneuvers, Consumer Unions double lane change and a host of auto manufacturers specific maneuvers fall into the category of dynamic testing. The static type of rollover metrics based on measureme

45、nts of static stability factor, tilt table angle and critical sliding velocity fall into the category of static testing. The latter in general do not incorporate the effects of transient tire behavior, effects of suspension motions and compliances, effects of stability controllers and so forth. Othe

46、r rollover metrics have beeninvestigated to form the basis of rollover warning and anti-rollover warning algorithms. Chen et. al. 2, 3 proposed a Time-To-Rollover (TTR) metric to predict an impending rollover. Susceptibility of SUVs to rollovers is difficult to be concluded from one or ahandful of d

47、ynamic maneuvers. CHAPTER 3APPLICATIONS OF OBSERVERS AND ESTIMATORS This chapter outlines some of the important vehicle states and their estimation methods discussed in literature. The Kalman filter method is explained and applied to estimate tire forces. Importance of tire force estimation and how

48、it can be used to supply useful information of vehicle operating conditions is discussed. The use of this knowledge is discussed in later chapters about active stability control and path-following algorithms. The effectiveness of closed loop vehicle dynamics control is dependent onaccurate knowledge

49、 of vehicle states. Some of the states like yaw rate, lateral acceleration, wheel speeds, etc can be easily measured using inexpensive sensors. Other states like vehicle side-slip, longitudinal speed, etc have to be estimated using other means involving measured signals, vehicle dynamic models and o

50、ther sophisticated tools. ome of the states are often obtained by direct integration of measured signals a process which is prone to errors and highly sensitive to disturbances. Other ways to obtain reliable state information include fusion of different sensors and redundancy in measurement systems

51、combining various properties of individual sensors to obtain reliable state estimation. Recent developments in embedded processors has made possiblethe use of computationally intensive methods like Kalman filters to be used to combine various sensor data and mathematical models in real time for stat

52、e estimation. 3.1 States and Estimation Methods Knowledge of vehicle states is necessary for stability control systems to work. Yaw rate and lateral acceleration are easily measured by inexpensive sensors. Other parameters like sideslip angle, roll angle and tire forces, etc. are not readily measure

53、d and must be estimated by other methods. Various estimators have been discussed in the literature and are employed by current stability systems available on production cars that use different methods. Direct integration of inertial sensor signals accumulates error over time and is unpractical to im

54、plement. More sophisticated methods involve sensor fusion in which data is combined from inertial sensors, GPS, subsystems on board and vehicle dynamics models to better estimate immeasurable states. The following is a brief discussion of various signals of interest and the method and systems used i

55、n theirestimation.3.1.1 Sideslip Side slip can be estimated by a method combining inertial navigation system (INS) and Global Positioning Systems (GPS) signals. GPS provides absolute heading and velocity measurements at a relatively slow rate which complements the faster updates of inertial sensors.

56、 Absolute GPS heading and velocity measurements eliminate the errors from INS integration; conversely, INS sensors complement the GPS measurements by providing higher update rate estimates of the vehicle states. However, during periods of GPS signal loss, which frequently occur in urban driving environments, integration errors can still accumulate and lead to faulty estimates. There are methods developed for sideslip estimation without the use of GPS. Instead a combination of measurements from 3 axis rate gyros, 3 axis accelerometers and vehicle ma