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中文譯文
混合動力驅動車輛安裝高空作業(yè)平臺的控制策略
Janusz Krasucki a, Andrzej Rostkowski a, Lukasz Gozdek b, Micha? Barty? b,
a Construction Equipment Research Institute, Napoleona 2, 05-230 Kobyka, Poland
b Warsaw University of Technology, Institute of Automatic Control and Robotics, Boboli 8, 02-525 Warsaw, Poland
摘要
本文提出的發(fā)展過程即假設，建造，模擬和分析混合動力驅動車輛安裝高空作業(yè)平臺的控制策略。特別注意的是支付控制系統(tǒng)策略的發(fā)展，確保適當?shù)哪茉丛偕?，通過電化學形式儲存能量?？刂撇呗允菄@上下分層控制系統(tǒng)的概念建立起來的。高空作業(yè)平臺的高程控制被假定為控制系統(tǒng)的主要目標?？刂葡到y(tǒng)的第二個目標是制定明確的跟蹤和保持在預定義的范圍內的可再充電的電化學蓄電池的充電水平。在Matlab-Simulink環(huán)境下開發(fā)控制系統(tǒng)的仿真模型?？刂葡到y(tǒng)仿真的示范性成果被一個液壓動力結構驅動安裝在特殊車輛MONTRAKS上的高空作業(yè)平臺例子所顯示。
關鍵字：控制策略，混合動力驅動，能量恢復，環(huán)境的保護，模糊邏輯
從這篇文章中的圖和表：
如圖1所示.MONTRAKS 3PS的專用車
1.介紹
減少車輛的廢氣排放一直是多年的研究目標，部分是迫于日益嚴格的環(huán)保立法。在1997年12月的第三屆締約方會議通過的“京都議定書”，旨在減少相比于1990年的溫室氣體排放量（GHG）平均水平的5％。2005年2月16日由俄羅斯批準后生效。
作為一個用于減少溫室氣體排放，提高燃油經濟性和能源效率的裝置，混合動力系統(tǒng)正在受到關注。
混合驅動汽車市場動態(tài)的增長已經多年?，F(xiàn)代，有11個大型汽車制造商用于交付或深入發(fā)展混合動力驅動型的車輛。即使這些車商主要是專供乘用車部分，應當強調的是他們進行了顯著的努力，從而實現(xiàn)了混合動力驅動卡車，送貨車和公交車[1,2]。
West Start-CALSTART[3]，一個先進的運輸技術財團，在美國陸軍國家汽車中心（NAC）的支持下，組織一部分混合動力卡車用戶論壇（HTUF?）計劃試點項目，以加快和協(xié)助混合商業(yè)化。根據(jù)制定的CAL-START的預測，混合驅動車的市場份額在2010年將達到約9％的增長，2020年將達到近18.5％的增長。
還有重型機器和特殊用途車輛，都是實現(xiàn)混合動力驅動的解決方案可能出現(xiàn)的對象。但也有一些疑惑，該應用程序在經濟上是否是可行的。考慮到乘用車，在有關環(huán)保法規(guī)的制定下，需要重要的角色扮演“規(guī)模的影響”。在重負荷機器的情況下，高空作業(yè)平臺的挑選和攜帶移動式起重機專用車輛的升降設備，應考慮其在混合動力解決方案中的應用驅動與操作制約和應用。
在許多情況下，該類機械的工作條件強烈限制或甚至消除燃燒的應用引擎。特別是封閉的空間領域，如工廠商店，倉庫，本質安全區(qū)等。當前實現(xiàn)柴油 - 電力驅動，可大大推廣使用該種設備。另一方面，和其他用于加工的市政服務工程在人口高度密集的區(qū)域在夜間（街道噴霧器人士，垃圾車，電車的牽引網絡服務車輛等）的公共服務領域相比，是非常獨特的。經常由市民報道，有關于服務項目問題的解決是關乎于柴油發(fā)動機產生的噪聲的水平。
一個由瓦拉公司[4] 設計電池供電的起重機路線的例子，就如何滿足不斷增加的法規(guī)控制室內起重作業(yè)時的環(huán)境條件，最近對混合解決方案將報盤延期。另一例子是由伊頓公司[5,6]研究的，用于高空作業(yè)平臺設備的中型卡車的混合動力系統(tǒng)。伊頓公司從2007年8月開始使中型混合動力系統(tǒng)的各種應用商業(yè)化，例如一個：電信和直轄市，城市配送，拒絕，城市公交大巴，挑選和攜帶等。
一種混合動力車輛，被定義為一個具有一個以上的源功率。雖然幾種不同類型的混合解決方案雖已在過去被考慮，但目前仍在接受進一步的廣泛研究，如混合動力電動汽車（HEV）[1]，它使用的電動機/發(fā)電機和電池組（或其他電存儲設備）和機械混合動力汽車用飛輪來儲存能量?；旌弦簤旱能囕v（HHVs）[2]，車輛加速時的制動過程中它存儲捕獲的動能，并將其存儲在液壓氣動蓄能器并返回能量傳動系統(tǒng)。各個不同結構的混合驅動器（串行和并行）開發(fā)[7,8]。
混合電力系統(tǒng)維護傳統(tǒng)的傳動系體系結構,當添加一個能夠提高發(fā)動機功率的電氣時。
該系統(tǒng)的一個特點是它通常能夠恢復在制動和儲存時丟失的能量，并存儲在電池中。存儲的能量被用于改善燃油經濟性和車輛性，只能為給定速度或用于操作車輛的電力系統(tǒng)。
混合動力傳動系的控制比控制的ICE唯一的動力傳動系要復雜得多。首先，需要在五種可能的模式（只有電動機，僅發(fā)動機，動力輔助，充電和再生）中確定最佳的操作模式。此外，當動力輔助模式或再充電模式被選擇，則發(fā)動機功率和電機功率需要進行選擇，以達到最佳燃油經濟性，電池充電的平衡性和可操作性。隨著增加的動力傳動系的復雜性和需要實現(xiàn)多個的目標，最常用的是采用兩級控制體系結構[5]。
以下分析功率控制系統(tǒng)的優(yōu)化:功率效率因素，燃油消耗和排放量已給出[3,9,10]。調查主要集中在車輛制動階段的動能再生。
在本文中，設計一個動力管理控制系統(tǒng)，被描述成是一個配有液壓高空作業(yè)平臺（AWP）設備的專用汽車的驅動系統(tǒng)。AWP對該類型的車輛（被迫停止的占空比）處理應認真考慮負載勢能的可回收性[11,12]。
混合驅動相比其他被提議的解決方案的主要優(yōu)點是它是一個簡單的驅動架構。它不同于已知的解決方案，那些廣泛適用于私家車。經典方法（私家車）是需要完全重新設計動力傳動系統(tǒng)。創(chuàng)新的方法對于特殊用途的車輛，只需要擴展經典的ICE驅動和擴展單元。擴展單元組成的電動機加上液壓泵/馬達。該解決方案允許區(qū)分熱和電的功率流路徑借助于液壓子系統(tǒng)。然而，即使該解決方案不是簡單的從功率流的角度出發(fā)，它任需求先進的控制系統(tǒng)策略。
兩層分層控制系統(tǒng)結構在本文中被提到。較低的控制水平是被本地經典的比例 - 積分 - 微分（PID）控制器所應用建造的。一個更高的控制水平是周圍形成了一個模糊邏輯控制器(FLC)，目的是對低水平本地控制器動態(tài)設置控制規(guī)則。
2.目標系統(tǒng)的特點：
一個專業(yè)的汽車MONTRAKS的（圖1）打算利用市政通信服務維修和保養(yǎng)電車、有軌電車架空導線的系統(tǒng)，以及組裝和拆卸的軌道部。
圖2結構的混合動力驅動單元理念：X - 活塞桿的位移，V - 活塞桿速度，p1- 活塞式壓力，R 1 - 閥（8）的開關信號，p2的 - 供應壓力，R2 - 切換閥（7）的信號- EM轉速，U - 電池電壓，I - 電池電流，n2 - ICE轉速
通常，這種類型的車輛在設計的基礎上，為定期卡車的底盤配備了相應的工作配件。該設備是建立在架空工作嵌入式平臺（AWP）（1）驅動的動臂（2）的端部的兩個液壓缸和液壓回轉馬達（3）的集合。除了標準的道路上運行的輪胎，這些車輛的主要特征是可能在軌道上繼續(xù)運行。具有低速液壓馬達驅動的額外的（4）軌道輪組實現(xiàn)了這一目標。
常常，牽引網絡的維護和修理要耗時整晚，大都消耗在操作上。對于在維修工作的時間期間進行的，該車輛被停放;代替發(fā)動機連續(xù)不斷地運行，并且驅動液壓泵供應油給液壓設備。在這個執(zhí)行階段周期，工作設備的功率需求很低 - 值不超過3％，由于柴油發(fā)動機的額定功率[2] 接近它的低效率和重大排放量操作點的區(qū)域。同時，柴油機還產生特別惱人的噪音。
上述缺點可以消除，例如通過引入額外的由一個電化學電池組成的電動機（EM）。在這種情況下，ICE將提供機械動力當車輛偏移操作區(qū)域時。停車時車輛的動力向EM以及可選的ICE工作設備索取，從而保持車輛平衡。
討論的混合動力驅動系統(tǒng)的結構示意圖 2。
用于電機的能源供給的是一組電化學蓄能器（5）。驅動設備單元的主要動力源是EM。電動機牽引參數(shù)由脈沖寬度調制器（6）控制。它可能扭轉電動機運行到發(fā)電機模式。EM運行的液壓泵（3）供應液壓傳動系統(tǒng)。 ICE，選擇適當?shù)墓ぷ鼽c進行試轉，成為第二液壓泵（2）。液壓油流量（2）和（3）在公共電源線上被添加在一起。液壓切換閥（7）和（8）重定向油流量在干線電源上通過，要么儲罐溢流到油箱閥或液壓缸下活塞的腔室（9）?；钊祝?）控制仰角臂（10）和間接高空作業(yè)平臺部（11）的位置。很明顯，氣缸（9）控制負載的勢能Q從而影響平臺的提升或降低。
圖3 結構的控制系統(tǒng)，概念:sp xp -定位點的位置。光伏xp -實際值的位置；e xp -用位置控制誤差；sp vp -定位點取消或降低速度的實際工作壓力；光伏vp -實際價值,用速度；sp SOC -定位點的電池SOC；太陽能光伏電池SOC -實際價值的電池SOC；pv p1 -實際價值的壓力p1；光伏p2 -實際價值的壓力p2；OUT2 - PID控制器的輸出。
圖4 用隸屬函數(shù)的位置控制誤差
以下幾個階段是加以區(qū)別的占空比混合動力驅動單元：
?SPL階段 - 提升的AWP，
?SPD階段 - 較低的AWP，
?SPP階段 - 停車的AWP。
在SPL階段，由于氣缸（9）的活塞式運轉以及適當?shù)牡鯒U上升運轉，油流的添加或分化從泵（2）和（3）發(fā)生。萬一流動減少，一個泵流量的一部分會被引導到主電源線，所述提供一部分驅動流量的泵（3）切換到電動機模式。在SPD階段，油的流動方向在主油壓供給線上發(fā)生變化，油運行泵（3）和機械耦合的電動馬達（4）。在這兩個階段中它可能供給汽缸（9）通過油供給泵（3）由電動馬達（4）驅動。電池充電（5）發(fā)生在SPP階段。在此階段中， AWP是被固定的，泵（3）是由石油供給給泵（2）所驅動的。
3.控制策略
在一般情況下，功率控制策略的主要目標是操作混合動力驅動時盡可能達到高的能源效率和低的排放量，同時保持指定車的輛性能[13]?？刂葡到y(tǒng)的主要任務是最大限度地利用電力的混合動力驅動。MONTRAKS車輛的噪聲水平和經濟運行符合相對應的具體要求。
這可以通過應用被建議的功率控制戰(zhàn)略來實現(xiàn)。這一戰(zhàn)略是基于通過控制一組電池的電荷（SOC）的狀態(tài)從而操作AWP使其速度接近于所需的軌跡以及捕獲有效的再生能量。因為它是唯一可能的，SPL和SPD占空比的階段，應使用電力驅動。
SOC是目前電池充電時瞬間可能存儲在電池中最大比例的電荷。
t = T時，可表示為：
;
其中：
Q（t0）= Q max的最大容量的電池中，SOC（t0）= 1，
i(t)的電池充電或充電電流。
同時，一個電池組的SOC應控制在最小的SOC和最大的SOC之間，從而有效的得到能源的再生制動，使能量最少的丟失和對電池組的壓力最小。最低和最高的SOC的標準是根據(jù)電池吸收再生能量的能力，并重新啟動交通工具系統(tǒng)所確定的。在一般情況下，最小的SOC標準和最大SOC標準之間的差異，在于電池更多的可再生能源能有效地吸收。然而，對于在SOC標準內大跨度地操作可能會降低電池的使用壽命，同時受放電深度的影響。因此，SOC水平應適當?shù)卮_定在最佳的最小和最大之間的水平[SOC min, SOC max].?？紤]到電池的充電和放電效率，本文的SOC范圍被設置為[0.3，0.8]。
發(fā)動機和電動機之間的流量分布可以通過驅動反應的程度（DOH）來確定：
其中：PICE - 發(fā)動機的功率，PMOT - 電機功率。
合并后的電源管理/設計優(yōu)化問題可寫為如下：
在 SPL 和SPD 階段出現(xiàn)最大值DOH
其中：
XSP（T）所需的AWP軌跡
XPV（t）實際的AWP軌跡。
為這個目的所設計出的控制系統(tǒng)的結構在圖3。
圖3示出的控制系統(tǒng)的結構。該控制系統(tǒng)由兩個循環(huán)：
- AWP的位置和速度的控制，
- 控制電池組的SOC。
每個回路可以控制電動機控制器?？刂菩盘柺鞘苓壿媶卧芾?。它的目標是適當?shù)臅r刻供應平穩(wěn)切換的控制信號。AWP控制系統(tǒng)用一個級聯(lián)結構來定位和控制速度。模糊控制器處理AWP的速度。其是從實際的和需求的平臺位移來計算的。輔助控制器SP_vp的速度信號，被美聯(lián)儲以經典的PID控制器作為參考，把它與實際速度的平臺PV_sp相比。第二控制回路電池的SOC保持在預定義的限制范圍。這個循環(huán)是由PID控制器和邏輯單元組成的。 PID單元通過連續(xù)調節(jié)的液壓閥位置控制管理電池的充電水平。
3.1 AWP位置控制器
AWP控制器的開發(fā)是基于已經開發(fā)的經典的級聯(lián)控制器PID和控制器FLC。 FLC已經被選中，因為其適合控制的非線性，多領域的控制，并隨時間變化有多種不確定因素[3]的工廠。該控制器有兩個輸入：一個AWP（SP_xp-PV_xp）控制位置誤差，和一個AWP（PV_vp）測當前速度。 FLC為PID控制器的電動馬達計算AWP的速度SP_vp的定位值。
FLC[14]由三個基本的??的塊組成：模糊化，推斷和非模糊化?？刂破鞯妮斎胧窃谀：龎K被統(tǒng)一標準模糊化。事實上，模糊化把清晰的空間映射到模糊的空間。在這個過程中，對于適當?shù)哪：担：?，把每個鮮明的輸入信號的每個樣品被轉變?yōu)橐唤M數(shù)字信號理解為這個樣本的隸屬度。 同一的模糊化標準輸入被供應到一個推理機。 推理機是在模糊輸入，模糊邏輯規(guī)則和知識嵌入在規(guī)則庫中（圖6）進行模糊輸出。該規(guī)則是根據(jù)相應的知識或通過依靠資料學習或從真實的后天獲得或模擬實驗建立起來的。模糊輸出從推理機被轉化成鮮明值通過依靠非模糊化程序。模糊化的過程中，專門三角形和梯形隸屬函數(shù)已被使用。每個模糊AWP速度控制器的輸入，都是依靠同一模糊化標準的7個隸屬函數(shù)的裝置來實現(xiàn)的（參見圖4和5）。
推理過程中應用的規(guī)則庫描繪在圖 6。規(guī)則庫被設定定量的知識集?？偣灿?9個規(guī)則已經被FLC論證。對于清晰度，規(guī)則庫以彩色矩陣的形式顯示。每個條目的矩陣對應于適當?shù)哪：妮敵觯⊿P_vp）;呈現(xiàn)在圖6的右側垂直條的形式 。
圖6 速度規(guī)則基于FLC使用，使用概念是表1中給出
傳統(tǒng)的重力中心[14]的方法已被應用于模糊輸出的非模糊化。先進的FLC的控制面已示于圖7中。正如上面提到的，從FLC輸出供應到AWP的速率PID控制器。AWP的速率被控制輸入到后續(xù)的控制系統(tǒng)，通過控制油壓泵（圖2）旋轉的速度。速度控制器的設置經過精心調校，以確保非周期性過渡（不過沖），即使在分步激發(fā)的情況下（參見圖10和11）。
3.2 SOC控制器
線性PID控制器的已被應用于控制電池的SOC（圖3）。SOC的實際值從Ep被連續(xù)地估算。（1）使用電池電流測量。一個額外的控制單元允許用于驅動電動液壓閥的線圈閥R1和R2。電動液壓閥的控制信號，用于獲得供應壓力p2的測量，根據(jù)活塞壓力P1，以及電池的電流和電壓（I，U）。
在提升階段的AWP，所述的控制單元提供了的電動液壓閥（7）和（8）的一個適當?shù)募ぐl(fā)。結果，根據(jù)氣缸的滑閥腔的與主油壓供給線連接。后一個AWP要求的位置達到時，閥（8）朝著它的中間位置驅動，這將完成的平臺的移動。在這里，內燃機燃燒的能量可用于電池充電。在電池充電階段，充電控制器還在控制壓合液壓缸的滑閥腔室。這防止不愉快情況，AWP的意外震搖所導致的負載變化。電動液壓閥（7）將切換到位置，引導油從泵（2）到油箱在達到所要求的電池充電水平之后。
從低級階段的平臺開始，控制單元再次切換閥（7），均衡的供應和根據(jù)活塞油的壓力。緊隨其后，閥（8）將被切換成上下移動的平臺。勢能平臺在這一運動期間被轉換成電的形式，并用于電池充電。
圖7 控制表面的FLC
3.3 無沖擊切換系統(tǒng)
模擬實驗顯示，在控制單元的操作模式切換期間會出現(xiàn)控制信號的逐步變化。這種現(xiàn)象應該被消除，因為它可能降低混合動力驅動的可靠性數(shù)據(jù)。例如，一個逐步改變的的控制信號，強制電動馬達動態(tài)變化的旋轉速度，導致壓力在供油線擺動。
一個特別小組已經開發(fā)，以避免突然變化的混合動力驅動控制信號的潛在影響。 “
本單元的概念已被示于圖 8。
塊P1，I1，D1分別表示：成比例的PID1控制器的加-積分 加-導數(shù)成分。控制器的主要部分是配有設置控制器輸出初始值的輸入配置。切換單元跟蹤各自的輸出：控制器PID1和PID2的OUT1和OUT2。在控制器輸出切換的時刻，跟蹤系統(tǒng)的設置輸出的積分動作I1和I2的值滿足下列條件：
一）I1= OUT1切換到SOC控制器，
二）I2=OUT2時，切換到AWP速度控制器。
控制誤差值e切換的時刻（t = 0時）補償輔助值e k，由校正單元生成。校正值e k從值E0= SP_vp-PV_vp下降到零值，在預定義的時間間隔Δt內。這意味著，OUT1和OUT2的值將等于在轉換i.e. 控制值時對于直流電動機控制器的不會改變切換時刻。此操作可確保的切換電動機控制裝置設定值時無沖擊。后來Δt消逝i.e.= 0時，輸入的PID1控制器er=e 。
4.模擬調查
混合動力驅動在Matlab的Simulink環(huán)境下的分析模型的基礎上已經進行了模擬調查。圖
[11]中給出。模型的調整參數(shù)部分是從專用汽車MONTRAKS的開發(fā)調查[12]所得的。開發(fā)的仿真模型具有的一般框圖被示于圖 9。
圖8 交換單元的方塊圖
圖9 MONTRAKS驅動裝置模型的方塊圖
以下組的主要參數(shù)已被用于模擬調查：
電解鉛蓄電池標稱容量Q nom=200Ah;額定電壓U nom=48 V，
?DC電機：額定功率P nom = 5千瓦，標稱轉速速度n nom =2300 rpm，
?柴油機額定功率N = 120千瓦
?液壓泵提供的標稱單位QP =42.3?10-6 m3/rev
?液壓缸活塞直徑D = 10毫米，最大行程S =0.65米
?AWP的慣性負載：M= 680千克
?AWP允許以V max=0.5米/秒速度的提升/降低：
?電池充電的初級水平SOC（T0）= 0.8。
模擬調查被作為循環(huán)周期為T =18秒假設的職務執(zhí)行的，以下是幾個階段：
?SPL階段 - 解除平臺ΔH=1.6米，
?SPP階段 - 停車平臺，tp=5秒，
?SPD階段 - 降低平臺ΔH=1.6米。
提升和下降AWP速度的模擬結果已給定圖10和11。
圖10. AWP 的速度在 SPL 階段.
圖11. AWP 的速度在SPD 階段
如3.1節(jié)中提到的，速度設定值由FLC生成。在早期開始的平臺提升階段（圖10）和更低的階段（圖11），當控制誤差最大，F(xiàn)LC快速推動最大的輸出值。在實際系統(tǒng)中，這可能造成阻尼以低振幅的速度振蕩（參照圖10）。 平臺速度的設定值和實際值在平臺運行的結束階段會無效。這個合理的方法，保證了所要平臺的位置。一個較低的平臺改變電池的充電水平。在AWP的工作期間SOC的改變示于圖 12。輕微電池放電過程被觀察到在SPP階段。這是由于由電動馬達裝載電池運行液壓泵所造成的。在SPD階段，可觀察到SOC增加是由平臺的勢能轉換和再生的。能量回收比率（在SPD階段熱能源的份額比上SPL階段所使用的能源）以約36％為例被考慮。
圖12 電池SOC改變占空比期間
建議配置電池放電的每一個責任周期是0.017％。連續(xù)循環(huán)的模擬得出結論，SOC達到其最低值0.3在2920循環(huán)周期之后。這是相當于14.6 h工作時間，見圖13。AWP的有效使用時間占整個工作周期時間74％并達到2.5小時[12]。從而可以得出結論，即AWP的驅動電源只有在電池不過度放電時才能夠供給的電動機。如下所述，為整個車輛的工作時間估計平均燃油消耗量可以降低約24％。
圖13 電池SOC下降
5.結束語
一個用于混合動力驅動，由AWP速度控制器，AWP位置控制器和電池充電控制器組成的兩級多輸出控制系統(tǒng)結構，已經研制成功。該系統(tǒng)允許轉移系統(tǒng)的工作點使其運動軌跡能達到最佳的節(jié)能效果區(qū)域。模擬混合動力驅動的調查結果，實驗驗證表明了所開發(fā)的控制系統(tǒng)的正確性。 取得的模擬結果已經制定了一個固定的基礎，發(fā)展用于發(fā)展原型實驗室控系統(tǒng)的調查。本文提出的控制系統(tǒng)結構可以考慮用在混合動力驅動器的應用程序中，其在占空比之后致動元件改變它的潛在能量。例如：叉車，高空作業(yè)平臺，安裝轉盤的拖車，移動式起重機等。MONTRAKS需要增加現(xiàn)有的高空作業(yè)平臺驅動器的投資，估計占車輛總成本的2％。為進一步推廣應用的技術經濟可行性，研究報告應詳細到每個個案。
致謝
作者答謝在波蘭教育部和高等教育部的資金支持下獲得5 TO7C 0192：
為市政工程發(fā)展建設環(huán)保的專用車和機器的電動機械動力傳送單元。
參考文獻
[1] B.V. Arburg, Hybrid technology growing momentum, Hybrid Truck Users Forum,San Antonio, 2003 http://calstart.org.
[2] J.S. Stecki, F. Conrad, P.L. Matheson, A. Rush, Development of a hydraulic drive for a novel hybrid diesel-hydraulic system for large commercial vehicles, 5-th JFPS International Symposium on Fluid Power, Nara, Japan, 2, 2002, pp. 425–430.
[3] B. Baumman, G.Washington, B. Glenn, G. Rizzoni, Mechatronic design and control of hybrid electric vehicles, IEEE transactions on mechatronics, 55(1), 2000, pp.58–72.
[4] http://www.valla.co.
[5] C. Lin, H. Peng, J.W. Grizzle, J. Liu, M. Busdiecker, Control System Development for an Advanced-Technology Medium-Duty Hybrid Electric Truck, SAE International Truck & Bus Meeting & Exhibition, Fort Worth, TX, USA, SAE Paper 2003-01-3369,2003.
[6] R. Nellums, J. Steffen, S. Naito, Class 4 Hybrid Truck for Pick Up and Delivery Applications, SAE International Truck & Bus Meeting & Exhibition, FortWorth, TX,USA, SAE Paper 2003-01-3368, 2003.
[7] C. Chan, The state of the art of electric and hybrid vehicles, Proc. IEEE 90 (2) (2002)247–275.
[8] M. Ehsani, Y. Gao, S.E. Gay, A. Emadi, Modern Electric, Hybrid Electric, and Fuel Cell Vehicles: Fundamentals, Theory, and Design, CRC Press, Washington D.C., 2004.
[9] J.B. Burl, J.E. Beard, Control Strategies for a Series-Parallel Hybrid Electric Vehicle,SAE 2001 World Congress, Detroit, SAE Paper 2001-01-1354, 2001.
[10] D. Choi, M. Im, H. Kim, An operation algorithm with state of charge recovery for a parallel-type hybrid vehicle, Proc. of the Institution of Mechanical Engineers, PartD, J. Automob. Eng. 217 (9) (2003) 801–807.
[11] J. Krasucki, A. Rostkowski, Idea of application of electric drives in hydraulic power systems on example of actuating units of automotive crane MONTRAKS, (in Polish),Prz. Mech. 9 (2005) 15–19.
[12] A. Rostkowski, J. Krasucki, M. Barty?, The analysis of hydraulic driving system of special vehicle MONTRAKS in operating conditions, XX Conference on Problems of Heavy Duty Machines Development. Zakopane, Poland, 2007, pp. 269–271, (in Polish).
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[14] J.M. Mendel, Fuzzy logic systems for engineering, Proc. IEEE 83 (1995) 345–377.
15
英文原文
Control strategy of the hybrid drive for vehicle mounted aerial work platform
Janusz Krasucki a, Andrzej Rostkowski a, ?ukasz Gozdek b, Micha? Barty? b,
a Construction Equipment Research Institute, Napoleona 2, 05-230 Koby?ka, Poland
b Warsaw University of Technology, Institute of Automatic Control and Robotics, Boboli 8, 02-525 Warsaw, Poland
The development process i.e. assumptions, construction, simulations and analysis of a control strategy for thehybrid drive of the vehicle mounted aerial work platform is presented in the paper. Particular attention ispaid to the development of the control system strategy ensuring appropriate energy recuperation by makinguse of energy stored in the electrochemical form. The control strategy is built up around the concept of bilevelhierarchic control system. The elevation control of the aerial work platform is assumed as the primarygoal of the control system. The secondary goal of the control system is formulated in terms of tracking andkeeping the charging level of the rechargeable electrochemical accumulator in predefined limits. A control system simulation model is developed in Matlab-Simulink environment. Exemplary results of control system simulations are shown on the example of a hydraulic power unit driving aerial work platform mounted on
special vehicle MONTRAKS.
1. Introduction
The reduction of vehicle emission has been an objective of research for many years; partly it is forced by increasingly stringent environmental legislation. The Kyoto protocol, whichwas adopted at the COP3in December 1997, is aimed to decrease the green house gas emissions(GHG) by an average of 5% referring to 1990 levels. It came into force on February 16, 2005 following its ratification by Russia.
Hybrid systems are now gaining attention as a means for reducing GHG emissions by improving fuel economy and energy eficiency.
Market for hybrid driven vehicles is growing up dynamically sincemany years. Contemporary, eleven large car manufacturers use to deliver or to intensively develop hybrid driven vehicles. Even that is mainly focusing on passenger cars segment, it should be stressed that the remarkable effort is undertaken to implement hybrid drives in the trucks, delivery vans and buses [1,2].
WestStart-CALSTART [3], an advanced transportation technologies consortium, supported by U.S. Army National Automotive Center(NAC), organized the pilot program as part of its Hybrid Truck Users Forum (HTUF?) program, to speed up and to assist hybrid commercialization. According to the forecasts elaborated by CALSTART,the hybrid driven trucks market share will grow reaching ca 9% in 2010 and near 18.5% in 2020.
Still heavy duty machines and special purpose vehicles are the object of possible implementation for hybrid drive solution. However there are some doubts, if that application is economically feasible.Considering passenger cars,in respect of environmental regulations,important role plays the “effect of the scale”. In case of heavy duty machines, aerial work platforms, pick and carry mobile cranes or special vehicles with lift equipment, the application of hybrid solution is driven with operating constrains and application.
For many cases, working conditions for that class of machinerystrongly limits or even eliminates the application of combustion engines. In particular that is case of closed space areas such as factory shops, warehouses, intrinsically safe zones, etc. Here the implementation of diesel-electric drives could considerably extend possible use of that kind of equipment. Very unique and on the other side common area of services is municipal services and works used to be processed during night in the highly populated zones (street sprayer-sweepers,garbage trucks, tramway traction networks service vehicles, etc.). It is often reported by municipalities, that the issue to be solved for that services is the level of noise generated by diesel engine.
An example on how to meet the ever-increasing regulations controlling environmental conditions during indoor lifting operations is the battery powered cranes line designed by Valla Corporation [4],which recently extended the offer for hybrid solution. Another example is a hybrid system investigated by Eaton Corporation [5,6]for medium trucks with optional aerial work platform equipment.Eaton began commercializing its medium-duty hybrid system in August 2007 in a wide variety of applications such a: telecommunications and municipality, city delivery, refuse, city transit bus, pick andcarry and so on.
A hybrid vehicle is defined as one that has more than one source of power. Several different types of hybrid solutions have beenconsidered in the past and are still undergoing extensive research,
Fig. 1. Special purpose vehicle MONTRAKS 3PS.
such as Hybrid Electric Vehicles (HEVs) [1], which use a motor/generator and battery packs (or other electrical storage devices) and mechanical hybrids which use flywheels to store energy. Hybrid Hydraulic Vehicles (HHVs) [2], which store kinetic energy captured during braking events and store it in hydro-pneumatic accumulators and return energy to driveline during vehicle acceleration. Various different structures of hybrid drives (serial and parallel) have been developed. [7,8]
The hybrid electric system maintains conventional drive train architecture while adding the ability to enhance engine power withelectrical one.
One feature of this system is its ability to recover energy normally lost during braking and store the energy in batteries. The stored energy is used to improve fuel economy and vehicle performance for a given speed or used to operate the vehicle with electric power only.
The control of hybrid power trains is more complicated than the control of ICE only power train. First, one needs to determine the optimal operating mode among five possible modes (motor only,engine only, power assist, recharge, and regenerative). Furthermore,when the power assist mode or the recharge mode is selected, the enginepower and motor power needs to be selected to achieve optimal fuel economy, battery charge balance, and operability. With the increased power train complexity and the need to achieve multiple objectives, most often a two-level control architecture is adopted [5].
Fig. 2. Structure of the hybrid drive unit. Notion: x — piston stem displacement, v — piston stem velocity, p1 — under piston pressure, R1 — switching signal of valve (8), p2 — supply pressure, R2 — switching signal of valve (7), n1 — EM rotational speed, U — battery voltage, I — battery current, n2 — ICE rotational speed, OUT — setpoint of electric motor controller.
Fig. 3. Structure of the control system. Notion: SP_xp — Setpoint of the AWP position. PV_xp — Actual value of the AWP position. e_xp — AWP position control error. SP_vp — Setpoint of the lifting or lower velocity of the AWP. PV_vp — Actual value of the AWP velocity. SP_SOC — Setpoint of the battery SOC. PV_SOC — Actual value of battery SOC. PV_P1 — Actual value of the pressure p1. PV_P2 — Actual value of the pressure p2. OUT1, OUT2 — Outputs of PID controllers.
The analysis of power control systems optimizing: power efficiency factors, fuel consumption and emissions has been given in[3,9,10]. Investigations have been mainly focused on the possibility of kinetic energy recuperation in the phase of vehicle braking.
In this paper, the design of a power management control system isdescribed for a hybrid drive system of special purpose vehicle with hydraulic aerial work platform (AWP) equipment. For that type of vehicles (stop-and-go duty cycles) the potential energy of the load being handled with AWP should be seriously considered as recyclable [11,12].
The major advantage of the proposed hybrid drive over othersolutions is a simple drive architecture. It differs from known solutions, thosewidely used in personal cars. The classic approach (personal cars) needs full redesign of power transmission system. The innovative approach for the special purpose vehicles requires only extension of classic ICE drive with extension unit. Extension unit is composed of electricmotor coupledwith hydraulic pump/motor. That solution allows to differentiate the power flowbetween the thermal and electrical path with help of hydraulic subsystem. However, even that solution is not straightforward from the point of view of power flow, it demands for advanced control system strategies.
Two-layer hierarchical control system architecture is considered in this paper. A lower control level is built by application of local classic proportional-integral-derivative (PID) controllers. A higher control level is developed around a fuzzy logic controller (FLC) with the intention of dynamically setting out control rules for lower level local controllers
2. Characteristics of the target system
A specialized automotive vehicle MONTRAKS (Fig. 1) is intended for repairing and maintenance of tram and trolley-bus overhead wire system, assembling and disassembling of rail track sections and is exploited by the municipal communication services.
Such types of vehicles are usually designed on the bases of regular trucks undercarriage equipped with appropriate working accessories. The equipment is built up around the aerial work platform (AWP) (1) embedded at the end of the boom (2) driven by the set of two hydraulic cylinders and hydraulic swing motor (3).Besides a standard road running on the tires, the major feature of these vehicles is the possibility to move on rail run. That is achieved with additional set of rail wheels (4) which are driven with low speed hydraulic motors.As often as not, maintenance and repairing of the traction networks take place throughout the night, and these are time consuming operations. For the period of the time that repair work is carried out, the vehicle is parked; instead of the engine is continuously running and driving the hydraulic pump which is used to supply oil to the hydraulic equipment. In this phase of duty cycle, a power demand from the working equipment is low — does not exceed 3% value of engine rated power [2], due to that the diesel operation point approaches the regions of its low efficiency and significant emissions. Simultaneously, the diesel generates particularly bothersome noise.
Disadvantages mentioned above may be eliminated for instance by introducing an additional electric motor (EM) powered by an electrochemical battery pack. In this case, the ICE will deliver
mechanical power when the vehicle moves from/to its operation area. While parking the vehicle's power demand from the working equipment will be balanced from the EM and optionally from the ICE.
The structure of discussed hybrid drive is shown in Fig. 2
Energy for the motor is supplied from a set of electrochemicalaccumulators (5). The primary power source of the equipment drive unit is the EM. Motor traction parameters are controlled by the pulse width modulator (6). It is possible to reverse the motor's operation into generator mode. The EM runs the hydraulic pump (3) supplying the hydraulic actuation system. The ICE, running in the appropriate chosen operating point, drives the second hydraulic pump (2).Hydraulic oil flows frompumps (2) and (3) are added together in the common supply line. Hydraulic switching valves (7) and (8) redirect the oil flow in the main supply line either to the tank via overflow valve or to the under piston chamber of the hydraulic cylinder (9).The piston stemof the cylinder (9) controls the elevation angle of the boom (10) and indirectly the position of AWP (11). It is obvious that the control of the cylinder (9) influences the potential energy of load Q while the platform is lifting or lowering.
The following phases are to be distinguished in the duty cycle of the
hybrid drive unit:
? SPL phase — lifting of the AWP,
? SPD phase — lower of the AWP,
? SPP phase — parking of the AWP.
In SPL phase, as a result of movements of the cylinder's (9) piston and appropriate boom lifting movements, the addition or differentiation of oil flows from pumps (2) and (3) takes place. In case of subtraction of flows, one part of the pump flow (2) is directed to the main supply line and the reminder part of flow drives the pump (3) switched into motor mode. In SPD phase, the direction of oil flow in the main hydraulic supply line changes, oil runs the pump (3), and the mechanically coupled electric motor (4). In both phases it is possible to supply cylinder (9) by the oil delivered by the pump (3) driven by electric motor (4). Charging a battery (5) occurs in the SPP phase. In this phase, the AWP is fixed, and the pump (3) is driven by oil provided by the pump (2).
Fig. 4. Membership functions of the AWP position control error.
3. Control strategy
In general, the main objective of the power control strategy is to operate the hybrid drive with possible high energy efficiency and low emissions while maintaining specified vehicle performance [13].Maximal use of electric power is the main task of the hybrid drive control system. This corresponds with specific requirements for noise level and economic operation of MONTRAKS vehicle.This can be achieved by applying of the proposed power control strategy. This strategy is based on operation of AWP velocity closed to required trajectory and effectively capturing of the regenerative energy by controlling the state of charge (SOC) of a battery. As it is only possible,the electric drive should be used in SPL and SPD phases of duty cycle.SOC is the ratio of present charge of a battery to the maximum charge that can be possibly stored in the battery and in time instantt=T may be expressed as:
;
where:Q(t0)=Qmax maximal capacity of the battery, SOC(t0)=1,i(t) battery charging or recharging current.Meanwhile, the SOC of a battery should be controlled between a minimum SOC and a maximum SOC to obtain regenerative braking energy effectively with the least amount lost and stress on the battery.The minimum and maximum SOC levels are determined according to
the ability of a battery to absorb regenerative energy and to restart vehicle systems. In general, the larger the difference between the minimum SOC level and the maximum SOC level, the more regenerative energy a battery can effectively absorb. However, the larger span of operating SOC levels may reduce the battery's life, which is affected by the depth of discharge. Hence, the SOC levels should be appropriately determined between optimal minimum and maximum levels [SOCmin, SOCmax]. Considering the battery charging and discharging efficiency, the SOC range is set to [0.3, 0.8] in this paper. The power flow distribution between engine and electric motor may be defined through degree of hybridization (DOH) of the drive:
where: PICE — engine power, Pmot — motor power.
The combined power management/design optimization problem can be written as follows:
where:
XSP(t) 2 desired AWP trajectory
XPV(t) 2 actual AWP trajectory.
A structure of the proposed control system for this purpose is given in Fig. 3.
Fig. 3 shows the structure of the control system. The control system consists of two loops:
— control of the AWP position and velocity,
— control of the SOC of battery pack.
Each loop may control electric motor controller. Control signals are governed by the logic unit. It is aimed to provide smooth switching of control signal for appropriate time instants. Control system for AWP positioning and velocity control has a cascade structure. Fuzzy controller processes the velocity of the AWP. It is calculated from the real and desired platform displacement. Velocity signal from the auxiliary controller SP_vp is fed as the reference to the classic PID controller and it is compared with actual velocity of the platform PV_sp. The second control loop keeps the SOC of battery in predefined limits. This loop consists of PID controller and logic unit. PID unit controls the level of charge of the battery through continuous adjustment the hydraulic valves positioning.
Fig. 5. Membership functions of the AWP velocity.
3.1. AWP position controller
A controller of the AWP has been developed based on the cascade of classic PID controller and FLC. The FLC has been chosen because of its suitability for control of nonlinear, multiple-domain, and timevarying plant with multiple uncertainties [3]. This controller has two inputs: a control error of the AWP postion (SP_xp?PV_xp), and acurrent velocity of the AWP (PV_vp). The FLC calculates setpoint value of the AWP velocity SP_vp for the PID controller of the electric motor.
The FLC [14] consists of three basic blocks: fuzzyfication, inference and defuzzyfication. Inputs of the controller are fuzzyfied in the fuzzyfication block. In fact, fuzzification maps the space of crisp values onto the space of fuzzy ones. In this process, each crisp sample of each input signal is transformed into the set of numbers interpreted as the membership degrees of this samples to the appropriate fuzzy values (fuzzy sets). Fuzzyfied inputs are fed to an inference machine. The inference machine makes fuzzy outputs based on: fuzzy inputs, fuzzy logic rules and knowledge embedded in the rule base (Fig. 6). The rule base is created based on the appropriate knowledge or by means of learning from data or is acquired from real or simulation experiments. Fuzzy output from the inference machine is transformed into the crisp value by means of defuzzyfication procedure. Exclusively the triangle and trapezoidal membership functions have been used in the process of fuzzyfication. In fuzzy AWP velocity controller each input was fuzzyfied by means of seven membership functions (see Figs. 4 and 5).
The rule base applied for the inference process is depicted in Fig. 6. Rule base is assumed as the set of quantitative knowledge. A total of 49 rules have been formulated for the FLC. For the clarity, the rule base is displayed in the form of colored matrix. Every entry to the matrix corresponds with the appropriate fuzzy output (SP_vp); that is presented in the form of vertical bar in the right side of Fig. 6. Conventional, center of gravity [14] method has been applied for the defuzzyfication of fuzzy output. A control surface of developed FLC has been presented in Fig. 7. As mentioned above, the output from the FLC is fed to the AWP velocity PID controller. Velocity of the AWP is controlled in the follow-up control system by controlling rotational speed of the hydraulic pump (Fig. 2). Settings of the velocity controller have been carefully tuned to ensure aperiodic transition (without overshoots) even in case of stepwise excitation (see Figs. 10 and 11).
3.2. SOC controller
The linear PID controller has been applied for the control of the battery's SOC (Fig. 3). The actual value of SOC is continuously estimated fromEq. (1) making use of the measurements of the battery current. An additional control unit allows for driving the coils of electro-hydraulic valves R1 and R2. Control signals for the electro-hydraulic valves are obtained from the measurements of supply pressure p2, under piston pressure p1, and current and voltage (I, U) of the battery.
Fig. 6. The rule base of the AWP velocity FLC. Notion used is given in Table 1.
Fig. 7. Control surface of the FLC.
In the lifting phase of the AWP, the control unit delivers an appropriate excitation for the electro-hydraulic valves (7) and (8). In outcome, the under piston chamber of the cylinder is connected with the main hydraulic supply line. After a demanded position of the AWP is reached, the valve (8) will be driven towards its neutral position, which will finish the movement of the platform.
Here, the energy of the combustion motor may be used for battery charging. In the battery charging phase, the charging controller controls also the pressure in the under piston chamber of the hydraulic cyli