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1、 题名： 新型双连杆双曲轴内燃机滑块偏转仿真研究作者： 谭理刚;杨靖;龚志辉来源： 《内燃机工程》 ISSN :1000-0925,2005,26(3):57-602、 题名： 直喷式发动机燃油喷射过程的多维模型仿真作者： 刘金武;杨靖;高为国;倪小丹来源： 《系统仿真学报 》ISSN :1004-731X,2004,16(3):525-5293、 题名： 虚拟样机技术在SL1126内燃机设计中的应用研究作者： 易际明;杨靖;张亮峰来源： 《计算机辅助设计与图形学学报》 ISSN :1003-9775,2004,16(7):1016-10194、 题名： 基于案例的SL1126内燃机方案设计作者： 易际明;杨靖;张亮峰来源： 《机械设计》 ISSN :1001-2354,2004,21(12):35-375、题名： 支持Top-Down Design的内燃机参数化建模作者： 易际明;杨靖;张亮峰来源： 《中国制造业信息化》 ISSN :1672-1616,2004,33(3):100-1026、 题名： 直喷式发动机喷雾模型研究进展作者： 刘金武;杨靖;高为国;倪小丹来源： 《内燃机工程》 ISSN :1000-0925,2005,26(1):81-847、 题名： 柴油机的性能改进及缸内工作过程的三维数值模拟作者： 杨靖;肖明伟;崔东晓;邓帮林;周剑来源： 《湖南大学学报. 自然科学版 》ISSN :1000-2472,2006,33(4):50-548、 题名： 内燃机燃烧过程仿真后处理输入文件Ipost的研究作者： 刘金武;杨靖;高为国;倪小丹来源： 《湖南工程学院学报》 自然科学版 ISSN :1671-119X,2003,13(3):34-369、 题名： 关联设计技术及其在内燃机CAD系统中的应用作者： 易际明;朱理;杨靖来源： 《机械设计与研究》 ISSN :1006-2343,2004,20(3):89-90,9510、题名： 基于μC/OS-Ⅱ嵌入式内核的排气分析仪开发研究作者： 谭理刚;杨靖;潘朝辉;龚金科来源：《湖南大学学报》自然科学版 ISSN :1000-2472,2005,32(4):43-4611、题名： CAD系统软件数据交换技术的实现作者： 张亮峰;杨靖;彭浩舸来源：《湖南工程学院学报》自然科学版ISSN :1671-119X,2004,14(4):38-4012、题名： 双连杆内燃机动态仿真作者： 易际明;杨靖来源： 《系统仿真学报》 ISSN :1004-731X,2004,16(12):2780-278213、题名： 提高智能排气分析仪精度的研究作者： 杨靖;潘朝晖;周剑来源： 《内燃机工程》 ISSN :1000-0925,2004,25(2):75-7814、题名： 105系列直喷式柴油机新燃烧系统开发作者： 杨靖;李克;潘朝浑来源： 《内燃机工程》 ISSN :1000-0925,2003,24(6):13-1615、题名： 面向装配的智能变型设计技术及应用研究作者： 易际明;杨靖来源： 《湖南工程学院学报》 自然科学版 ISSN :1671-119X,2005,15(1):25-2916、题名： SL1115单缸双连杆柴油机配气凸轮型线的设计作者： 李蓉;杨靖来源： 《小型内燃机与摩托车》 ISSN :1002-8277,2000,29(2):1917、题名：轻型汽油车改装柴油机后发动机悬置系统和冷却系统的优化作者： 杨靖;肖明伟；崔东晓；邓帮林来源： 《客车技术与研究》 ISSN :1000-2472,2006,28(2):4918、题名： 内燃机燃烧过程仿真计算的双精度系统设计作者： 刘金武;杨靖;倪小丹;黄麓升来源： 《湖南工程学院学报》 自然科学版 ISSN :1671-119X,2004,14(2):40-43
呵呵，从具体的情况来看，好象这类的问题应该有专业方面的人才来帮助你回答啊！很可惜我不会啊！
Robotics education in the university* Rafael M. Inigo and Jose M. Angulo School of Engineering and Applied Science, University of Virginia, Charlottesville, Virginia 22901, USADept. de Informatica, Universidad de Deusto, Bilbao, Spain Available online 28 October 2004. The importance of automation and robotics in modern factories has required the introduction of courses on these subjects at the graduate and undergraduate levels in engineering schools. A comprehensive course on robotics must include the following subjects of fundamental importance: kinematics, dynamics, computer hardware and software, automatic control and machine vision. This paper describes the authors' experience in teaching a graduate robotics course at the University of Virginia and a short summer course at the Universidad de Deusto in Spain. Hands-on experience is a must in courses on robotics, and some simple yet effective systems designed and constructed by students are described. These include a program for transformation matrix manipulation, an operating system for manipulator control, and a simple three degrees of freedom programmable manipulator. The majority of the students who took both courses were electrical engineers, but mechanical engineers and computer scientists were also enrolled. Author Keywords: Robotics Education; Robotics Laboratory; Hardware; Software Development For Robotics Education *Parts of this paper were presented at the Second annual workshop on interactive computing, CAD/CAM: Electrical Engineering Education Washington,
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啊,我才小学
你好，经查证该期刊该刊被CA 化学文摘(美)(2014)数据库收录，属于CA期刊，并不是核心期刊。
根据教育局规定，已经没有明确一本、二本的概念。湖南工学院（Hunan Institute of Technology）位于湖南衡阳，是 2007年经教育部批准由湖南建材高等专科学校和湖南大学衡阳分校合并升格的省属公办普通本科院校。2010年3月湖南工业科技职工大学整体并入，2011年湖南工学院成为全国百所“卓越工程师培养计划”高校，CDIO工程教育联盟成员单位。2018年，成为湖南省省级硕士立项建设单位。
截至2021年12月，学校有三个校区占地1400余亩，校舍建筑面积56万余平方米，图书馆纸质藏书164万余册；设有18个二级教学院（部），开设45个本科专业；拥有省级重点学科4个；教育部特色专业1个，教育部“卓越计划”试点专业3个，省特色专业和重点资助建设专业4个；教职工1320人，其中享受国务院政府特殊津贴专家6人；全日制在校学生19466人。师资力量截至2021年12月，学校有教职工1320人，其中正高职称112人（教授100人），副高职称312人（副教授206人），博、硕士908人。有享受国务院政府特殊津贴专家6人、湖南省新世纪“121人才工程”第一、二、三层次人选6人，有一批获得教育部思想政治教育中青年杰出人才支持计划培养对象、全国优秀教师、湖南省院士专家咨询委员会专家、省级学科带头人、省级骨干教师、省级青年教学能手、湖南省优秀教师、湖南省教学奉献奖、省级海外名师、湖湘英才、湖湘侨界精英等荣誉的高水平教师。省级教学团队（3个）：安全工程本科专业教学团队（张力）、机械设计制造及其自动化专业教学团队（金潇明）、电工电子技术系列课程教学团队（姚胜兴）院系专业截至2021年12月，学校设有18个二级教学院（部）、18个党政管理机构、3个党群组织、9个直属单位，开设45个本科专业。
教学建设截至2018年4月，学校有教育部特色专业1个，教育部“卓越计划”试点专业3个，省特色专业和重点资助建设专业4个，省级综合改革试点专业5个；有省级实践教学示范中心3个，国家级精品课程1门、省级精品课程8门；国家级大学生校外实践教育基地1个，省级优秀实习教学基地11个。 教育部特色专业建设点：安全工程湖南省特色专业建设点：工商管理教育部卓越工程师培养计划专业：自动化、无机非金属材料工程、机械设计制造及其自动化
湖南省“十二五”专业综合改革试点项目：安全工程、无机非金属材料省级实践教学示范中心：模具设计与制造实践教学中心、电气与控制工程实践教学中心、安全工程实践教学中心国家级精品课程：安全人机工程学省级精品课程：Pro/ENGINEER三维设计、电路分析、安全人机工程学、工程制图、工商企业经营与管理、高等数学、材料物理化学、会计学、机械制造工程训练—金工实习等国家级大学生校外实践教育基地：湖南工学院-湖南韶峰南方水泥有限公司工程实践教育中心学科建设截至2018年4月，学校有1个省级重点学科材料学。合作交流学校以校友会、基金会为平台，以“校企合作、产教融合”为重点，分别与大亚湾核电站、三一重工、中联重科、南方水泥、皇朝家私、泛华集团、千山药机、华兴工程、共创实业等企业进行合作共建实践实训基地，搭建实践实训课程平台。截至2018年4月，学校与美国、英国、澳大利亚、日本、韩国、马来西亚等10多个国家的30多所高校建立了合作关系。
科研机构截至2018年4月，学校拥有国家地方联合工程实验室1个，省级科研平台5个，省级教育科学研究基地1个。学术资源馆藏资源截至2018年4月，图书馆纸质藏书135万余册。截至2015年11月，学校馆藏纸质书刊文献124万余册，电子图书310万余册，中外文期刊990种，中外文报纸120余种。藏书种类以工为主。学术期刊《湖南工学院学报》是由湖南工学院主办的综合性学术期刊，创刊于2002年，季刊，大16开本，季末出刊。主要内容是刊登安全、化工、建筑、材料、机械、自动化、电子、信息、经济、管理、基础理论、社会科学及高等教育教学类的反映本院学科特色和地域特色的新理论、新技术、新成果、新方法。主要栏目设有 “ 安全与化工 ” “ 建筑与材料 ” “ 机械与自动化 ” “ 电子与信息 ” “ 经济与管理 ” “ 基础理论 ” “社会科学”“ 教育教学 ” 8个栏目。
英语写作网上可能会有
Sensorless torque control scheme ofinduction motor for hybrid electric vehicleYan LIU 1,2, Cheng SHAO1( Institute of Advanced Control Technology, Dalian University of Technology, Dalian Liaoning 116024, China; of Information Engineering of Dalian University, Dalian Liaoning 116622, China)Abstract: In this paper, the sensorless torque robust tracking problem of the induction motor for hybrid electric vehicle(HEV) applications is addressed. Because motor parameter variations in HEV applications are larger than in industrialdrive system, the conventional field-oriented control (FOC) provides poor performance. Therefore, a new robust PI-basedextension of the FOC controller and a speed-flux observer based on sliding mode and Lyapunov theory are developed inorder to improve the overall performance. Simulation results show that the proposed sensorless torque control scheme isrobust with respect to motor parameter variations and loading disturbances. In addition, the operating flux of the motor ischosen optimally to minimize the consumption of electric energy, which results in a significant reduction in energy lossesshown by : Hybrid electric vehicle; Induction motor; Torque tracking; Sliding mode1 IntroductionBeing confronted by the lack of energy and the increasinglyserious pollution, the automobile industry is seekingcleaner and more energy-efficient Hybrid ElectricVehicle (HEV) is one of the solutions. A HEV comprisesboth a Combustion Engine (CE) and an Electric Motor(EM). The coupling of these two components can be inparallel or in series. The most common type of HEV is theparallel type, in which both CE and EM contribute to thetraction force that moves the vehicle. Fig1 presents a diagramof the propulsion system of a parallel HEV [1].Fig. 1 Parallel HEV automobile propulsion order to have lower energy consumption and lower pollutantemissions, in a parallel HEV the CE is commonlyemployed at the state (n > 40 km/h or an emergency speedup), while the electric motor is operated at various operatingconditions and transient to supply the difference in torquebetween the torque command and the torque supplied bythe CE. Therefore fast and precise torque tracking of an EMover a wide range of speed is crucial for the overall performanceof a induction motor is well suited for the HEV applicationbecause of its robustness, low maintenance and lowprice. However, the development of a drive system basedon the induction motor is not straightforward because of thecomplexity of the control problem involved in the IM. Furthermore,motor parameter variations in HEV applicationsare larger than in industrial drive system during operation[2]. The conventional control technique ranging from theinexpensive constant voltage/frequency ratio strategy to thesophisticated sensorless control schemes are mostly ineffectivewhere accurate torque tracking is required due to theirdrawbacks, which are sensitive to change of the parametersof the general, a HEV operation can be continuing smoothlyfor the case of sensor failure, it is of significant to developsensorless control algorithms. In this paper, the developmentof a sensorless robust torque control system for HEVapplications is proposed. The field oriented control of the inductionmotor is commonly employed in HEV applicationsdue to its relative good dynamic response. However the classical(PI-based) field oriented control (CFOC) is sensitive toparameter variations and needs tuning of at least six controlparameters (a minimum of 3 PI controller gains). An improvedrobust PI-based controller is designed in this paper,Received 5 January 2005; revised 20 September work was supported in part by State Science and Technology Pursuing Project of China (No. 2001BA204B01).Y. LIU et al. / Journal of Control Theory and Applications 2007 5 (1) 42–46 43which has less controller parameters to be tuned, and is robustto parameter variable parameters modelof the motor is considered and its parameters are continuouslyupdated while the motor is operating. Speed andflux observers are needed for the schemes. In this paper,the speed-flux observer is based on the sliding mode techniquedue to its superior robustness properties. The slidingmode observer structure allows for the simultaneous observationof rotor fluxes and rotor speed. Minimization of theconsumed energy is also considered by optimizing operatingflux of the The control problem in a HEV caseThe performance of electric drive system is one of thekey problems in a HEV application. Although the requirementsof various HEV drive system are different, all thesedrive systems are kinds of torque control systems. For anideal HEV, the torque requested by the supervisor controllermust be accurate and efficient. Another requirement is tomake the rotor flux track a certain reference λref . The referenceis commonly set to a value that generates maximumtorque and avoids magnetic saturation, and is weakened tolimit stator currents and voltages as rotor speed HEV applications, however, the flux reference is selectedto minimize the consumption of electrical energy as it is oneof the primary objectives in HEV applications. The controlproblem can therefore be stated as the following torque andflux tracking problems:minids,iqs,we Te(t) − Teref (t), (1)minids,iqs,we λdr(t) − λref (t), (2)minids,iqs,we λqr(t), (3)where λref is selected to minimize the consumption of electricalenergy. Teref is the torque command issued by thesupervisory controller while Te is the actual motor (3) reflects the constraint of field orientation commonlyencountered in the literature. In addition, for a HEVapplication the operating conditions will vary changes of parameters of the IM model need to be accountedfor in control due to they will considerably changeas the motor changes operating A variable parameters model of inductionmotor for HEV applicationsTo reduce the elements of storage (inductances), the inductionmotor model used in this research in stationary referenceframe is the Γ-model. Fig. 2 shows its q-axis (d-axisare similar). As noted in [3], the model is identical (withoutany loss of information) to the more common T-model inwhich the leakage inductance is separated in stator and rotorleakage [3]. With respect to the classical model, the newparameters are:Lm = L2mLr= γLm, Ll = Lls + γLlr,Rr = γ. 2 Induction motor model in stationary reference frame (q-axis).The following basic w−λr−is equations in synchronouslyrotating reference frame (d - q) can be derived from theabove model.⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩dλdrdt= −ηλdr + (we − wr)λqr + ηLmids,dλqrdt= −(we − wr)λdr − ηλqr + ηLmiqs,didsdt= ηβλdr+βwrλqr−γids+weiqs+1σLsVds,diqsdt=−βwrλdr+ηβλqr−weids−γiqs+1σLsVqs,dwrdt= μ(λdriqs − λqrids) −TLJ,dθdt= wr + ηLmiqsλdr= we,Te = μ(λdriqs − λqrids)(4)with constants defined as follows:μ = npJ, η = RrLm, σ = 1−LmLs, β =1Ll,γ = Rs + RrLl, Ls = Ll + Lm,where np is the number of poles pairs, J is the inertia of therotor. The motor parameters Lm, Ll, Rs, Rr were estimatedoffline [4]. Equation (5) shows the mappings between theparameters of the motor and the operating conditions (ids,iqs).Lm = a1i2ds + a2ids + a3, Ll = b1Is + b2,Rr = c1iqs + c2.(5)4 Sensorless torque control system designA simplified block diagram of the control diagram isshown in Fig. Y. LIU et al. / Journal of Control Theory and Applications 2007 5 (1) 42–46Fig. 3 Control PI controller based FOC designThe PI controller is based on the Field Oriented Controller(FOC) scheme. When Te = Teref, λdr = λref , andλqr = 0 in synchronously rotating reference frame (d − q),the following FOC equations can be derived from the equations(4).⎧⎪⎪⎪⎪⎪⎪⎨⎪⎪⎪⎪⎪⎪⎩ids = λrefLm+ λrefRr,iqs = Terefnpλref,we = wr + ηLmiqsλref.(6)From the Equation (6), the FOC controller has lower performancein the presence of parameter uncertainties, especiallyin a HEV application due to its inherent open loopdesign. Since the rotor flux dynamics in synchronous referenceframe (λq = 0) are linear and only dependent on thed-current input, the controller can be improved by addingtwo PI regulators on error signals λref − λdr and λqr − 0 asfollowids = λrefLm+ λrefRr+ KPd(λref − λdr)+KId (λref − λdr)dt, (7)iqs = Terefnpλref, (8)we = wr + ηLmiqsλref+ KPqλqr + KIq λqrdt. (9)The Equation (7) and (9) show that current (ids) can controlthe rotor flux magnitude and the speed of the d − q rotatingreference frame (we) can control its orientation correctlywith less sensitivity to motor parameter variations becauseof the two PI Stator voltage decoupling designBased on scalar decoupling theory [5], the stator voltagescommands are given in the form:⎧⎪⎪⎪⎨⎪⎪⎪⎩Uds = Rsids − weσLsiqs = Rsids − weLliqs,Uqs = Rsiqs + weσLsids + LmLrweλref= Rsiqs + weσLsids + weλref .(10)Because of fast and good flux tracking, poor dynamics decouplingperformance exerts less effect on the control Speed-flux observer designBased on the theory of negative feedback, the design ofspeed-flux observer must be robust to motor parameter speed-flux observer here is based on the slidingmode technique described in [6∼8]. The observer equationsare based on the induction motor current and flux equationsin stationary reference frame.⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩d˜idsdt= ηβ˜λdr + β ˜ wr˜λqr − γ˜ids +1LlVds,d˜iqsdt= −β ˜ wr˜λdr + ηβ˜λqr − γ˜iqs +1LlVqs,d˜λdrdt= −η˜λdr − ˜ wr˜λqr + ηLm˜ids,d˜λqrdt= ˜wr˜λ dr − η˜λqr + ηLm˜iqs.(11)Define a sliding surface as:s = (˜iqs − iqs)˜λdr − (˜ids − ids)˜λqr. (12)Let a Lyapunov function beV = . (13)After some algebraic derivation, it can be found that when˜ wr = w0sgn(s) with w0 chosen large enough at all time,then ˙V = ˙s · s 0. This shows that s will converge tozero in a finite time, implying the stator current estimatesand rotor flux estimates will converge to their real valuesin a finite time [8]. To find the equivalent value of estimatewr (the smoothed estimate of speed, since estimate wr is aswitching function), the equation must be solved [8]. Thisyields:˜ weq = wr˜λqrλqr + λdr˜λdr˜λ2qr +˜λ2dr −ηnp˜λqrλdr − λqr˜λdr˜λ2qr +˜λ2dr. (14)The equation implies that if the flux estimates converge totheir real values, the equivalent speed will be equal to thereal speed. But the Equation (14) for equivalent speed cannotbe used as given in the observer since it contains unknownterms. A low pass filter is used instead,˜ weq =11 + s · τ˜ wr. (15)Y. LIU et al. / Journal of Control Theory and Applications 2007 5 (1) 42–46 45The same low pass filter is also introduced to the systeminput,which guarantees that the input matches the feedbackin selection of the speed gain w0 has two major constraints:1) The gain has to be large enough to insure that slidingmode can be ) A very large gain can yield to instability of the simulations, an adaptive gain of the slidingmode observer to the equivalent speed is = k1 ˜ weq + k2. (16)From Equation (11), the sliding mode observer structureallows for the simultaneous observation of rotor Flux reference optimal designThe flux reference can either be left constant or modifiedto accomplish certain requirements (minimum current,maximum efficiency, field weakening) [9,10]. In this paper,the flux reference is chosen to maximum efficiency at steadystate and is weaken for speeds above rated. The optimal efficiencyflux can be calculated as a function of the torquereference [9].λdr−opt = |Teref| · 4Rs · L2r/L2m + Rr. (17)Equation (17) states that if the torque request Teref iszero, Equation (8) presents a singularity. Moreover, theanalysis of Equation (17) does not consider the flux fact, for speeds above rated, it is necessary toweaken the flux so that the supply voltage limits are not improved optimum flux reference is then calculatedas:⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩λref = λdr-opt,if λmin λdr-opt λdr-rated ·wratedwr-actual,λref = λmin, if λdr-opt λmin,λref = λdr-rated ·wratedwr-actual,if λdr-opt λdr-rated ·wratedwr-actual.(18)where λmin is a minimum value to avoid the division SimulationsThe rated parameters of the motor used in the simulationsare given byRs = Ω, Rr = Ω, Lls = 75 H,Llr = 105 H, Lm = mH, Ls = Lls + Lm,Lr = Llr + Lm, P = 4, Jmot = kgm2,J = Jmot +MR2tire/Rf, ρair = , Cd = = m2, Rf = , Cr = = m, M = 3000 kg, wbase = 5400 rpm,λdr−rated = shows the torque reference curve that representstypical operating behaviors in a hybrid electric . 4 The torque reference torque is modeled by considering the aerodynamic,rolling resistance and road grade forces. Its expression isgiven byTL = RtireRf(12ρairCdAfv2 +MCr cos αg +M sin αg).Figures in [5∼8] show the simulation results of thesystem of (considering variable motor parameters).Though a small estimation error can be noticed on the observedfluxes and speed, the torque tracking is still achievedat an acceptable level as shown in Figs. [5, 6, 8]. The torquecontrol over a wide range of speed presents less sensitivityto motor parameters presents the d and q components of the rotor flux λr is precisely orientated to d-axis because of theimproved PI shows clearly the real and observed speed in thedifferent phases of acceleration, constant and decelerationspeed with the motor control torque of . The variablemodel parameters exert less influence on speed shows the power loss when the rotor flux keeps constantor optimal state. A significant improvement in powerlosses is noticed due to reducing the flux reference duringthe periods of low torque . 5 Motor rotor flux λ Y. LIU et al. / Journal of Control Theory and Applications 2007 5 (1) 42–46Fig. 6 Motor . 7 Power . 8 Motor ConclusionsThis paper has described a sensorless torque control systemfor a high-performance induction motor drive for aHEV case. The system allows for fast and good torquetracking over a wide range of speed even in the presence ofmotor parameters uncertainty. In this paper, the improvedPI-based FOC controllers show a good performance in therotor flux λdr magnitude and its orientation tracking. Thespeed-flux observer described here is based on the slidingmode technique, making it independent of the motor adaptation of the speed -flux observer is used tostabilize the observer when integration errors are present.
英语写作网上可能会有
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Sensorless torque control scheme ofinduction motor for hybrid electric vehicleYan LIU 1,2, Cheng SHAO1( Institute of Advanced Control Technology, Dalian University of Technology, Dalian Liaoning 116024, China; of Information Engineering of Dalian University, Dalian Liaoning 116622, China)Abstract: In this paper, the sensorless torque robust tracking problem of the induction motor for hybrid electric vehicle(HEV) applications is addressed. Because motor parameter variations in HEV applications are larger than in industrialdrive system, the conventional field-oriented control (FOC) provides poor performance. Therefore, a new robust PI-basedextension of the FOC controller and a speed-flux observer based on sliding mode and Lyapunov theory are developed inorder to improve the overall performance. Simulation results show that the proposed sensorless torque control scheme isrobust with respect to motor parameter variations and loading disturbances. In addition, the operating flux of the motor ischosen optimally to minimize the consumption of electric energy, which results in a significant reduction in energy lossesshown by : Hybrid electric vehicle; Induction motor; Torque tracking; Sliding mode1 IntroductionBeing confronted by the lack of energy and the increasinglyserious pollution, the automobile industry is seekingcleaner and more energy-efficient Hybrid ElectricVehicle (HEV) is one of the solutions. A HEV comprisesboth a Combustion Engine (CE) and an Electric Motor(EM). The coupling of these two components can be inparallel or in series. The most common type of HEV is theparallel type, in which both CE and EM contribute to thetraction force that moves the vehicle. Fig1 presents a diagramof the propulsion system of a parallel HEV [1].Fig. 1 Parallel HEV automobile propulsion order to have lower energy consumption and lower pollutantemissions, in a parallel HEV the CE is commonlyemployed at the state (n > 40 km/h or an emergency speedup), while the electric motor is operated at various operatingconditions and transient to supply the difference in torquebetween the torque command and the torque supplied bythe CE. Therefore fast and precise torque tracking of an EMover a wide range of speed is crucial for the overall performanceof a induction motor is well suited for the HEV applicationbecause of its robustness, low maintenance and lowprice. However, the development of a drive system basedon the induction motor is not straightforward because of thecomplexity of the control problem involved in the IM. Furthermore,motor parameter variations in HEV applicationsare larger than in industrial drive system during operation[2]. The conventional control technique ranging from theinexpensive constant voltage/frequency ratio strategy to thesophisticated sensorless control schemes are mostly ineffectivewhere accurate torque tracking is required due to theirdrawbacks, which are sensitive to change of the parametersof the general, a HEV operation can be continuing smoothlyfor the case of sensor failure, it is of significant to developsensorless control algorithms. In this paper, the developmentof a sensorless robust torque control system for HEVapplications is proposed. The field oriented control of the inductionmotor is commonly employed in HEV applicationsdue to its relative good dynamic response. However the classical(PI-based) field oriented control (CFOC) is sensitive toparameter variations and needs tuning of at least six controlparameters (a minimum of 3 PI controller gains). An improvedrobust PI-based controller is designed in this paper,Received 5 January 2005; revised 20 September work was supported in part by State Science and Technology Pursuing Project of China (No. 2001BA204B01).Y. LIU et al. / Journal of Control Theory and Applications 2007 5 (1) 42–46 43which has less controller parameters to be tuned, and is robustto parameter variable parameters modelof the motor is considered and its parameters are continuouslyupdated while the motor is operating. Speed andflux observers are needed for the schemes. In this paper,the speed-flux observer is based on the sliding mode techniquedue to its superior robustness properties. The slidingmode observer structure allows for the simultaneous observationof rotor fluxes and rotor speed. Minimization of theconsumed energy is also considered by optimizing operatingflux of the The control problem in a HEV caseThe performance of electric drive system is one of thekey problems in a HEV application. Although the requirementsof various HEV drive system are different, all thesedrive systems are kinds of torque control systems. For anideal HEV, the torque requested by the supervisor controllermust be accurate and efficient. Another requirement is tomake the rotor flux track a certain reference λref . The referenceis commonly set to a value that generates maximumtorque and avoids magnetic saturation, and is weakened tolimit stator currents and voltages as rotor speed HEV applications, however, the flux reference is selectedto minimize the consumption of electrical energy as it is oneof the primary objectives in HEV applications. The controlproblem can therefore be stated as the following torque andflux tracking problems:minids,iqs,we Te(t) − Teref (t), (1)minids,iqs,we λdr(t) − λref (t), (2)minids,iqs,we λqr(t), (3)where λref is selected to minimize the consumption of electricalenergy. Teref is the torque command issued by thesupervisory controller while Te is the actual motor (3) reflects the constraint of field orientation commonlyencountered in the literature. In addition, for a HEVapplication the operating conditions will vary changes of parameters of the IM model need to be accountedfor in control due to they will considerably changeas the motor changes operating A variable parameters model of inductionmotor for HEV applicationsTo reduce the elements of storage (inductances), the inductionmotor model used in this research in stationary referenceframe is the Γ-model. Fig. 2 shows its q-axis (d-axisare similar). As noted in [3], the model is identical (withoutany loss of information) to the more common T-model inwhich the leakage inductance is separated in stator and rotorleakage [3]. With respect to the classical model, the newparameters are:Lm = L2mLr= γLm, Ll = Lls + γLlr,Rr = γ. 2 Induction motor model in stationary reference frame (q-axis).The following basic w−λr−is equations in synchronouslyrotating reference frame (d - q) can be derived from theabove model.⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩dλdrdt= −ηλdr + (we − wr)λqr + ηLmids,dλqrdt= −(we − wr)λdr − ηλqr + ηLmiqs,didsdt= ηβλdr+βwrλqr−γids+weiqs+1σLsVds,diqsdt=−βwrλdr+ηβλqr−weids−γiqs+1σLsVqs,dwrdt= μ(λdriqs − λqrids) −TLJ,dθdt= wr + ηLmiqsλdr= we,Te = μ(λdriqs − λqrids)(4)with constants defined as follows:μ = npJ, η = RrLm, σ = 1−LmLs, β =1Ll,γ = Rs + RrLl, Ls = Ll + Lm,where np is the number of poles pairs, J is the inertia of therotor. The motor parameters Lm, Ll, Rs, Rr were estimatedoffline [4]. Equation (5) shows the mappings between theparameters of the motor and the operating conditions (ids,iqs).Lm = a1i2ds + a2ids + a3, Ll = b1Is + b2,Rr = c1iqs + c2.(5)4 Sensorless torque control system designA simplified block diagram of the control diagram isshown in Fig. Y. LIU et al. / Journal of Control Theory and Applications 2007 5 (1) 42–46Fig. 3 Control PI controller based FOC designThe PI controller is based on the Field Oriented Controller(FOC) scheme. When Te = Teref, λdr = λref , andλqr = 0 in synchronously rotating reference frame (d − q),the following FOC equations can be derived from the equations(4).⎧⎪⎪⎪⎪⎪⎪⎨⎪⎪⎪⎪⎪⎪⎩ids = λrefLm+ λrefRr,iqs = Terefnpλref,we = wr + ηLmiqsλref.(6)From the Equation (6), the FOC controller has lower performancein the presence of parameter uncertainties, especiallyin a HEV application due to its inherent open loopdesign. Since the rotor flux dynamics in synchronous referenceframe (λq = 0) are linear and only dependent on thed-current input, the controller can be improved by addingtwo PI regulators on error signals λref − λdr and λqr − 0 asfollowids = λrefLm+ λrefRr+ KPd(λref − λdr)+KId (λref − λdr)dt, (7)iqs = Terefnpλref, (8)we = wr + ηLmiqsλref+ KPqλqr + KIq λqrdt. (9)The Equation (7) and (9) show that current (ids) can controlthe rotor flux magnitude and the speed of the d − q rotatingreference frame (we) can control its orientation correctlywith less sensitivity to motor parameter variations becauseof the two PI Stator voltage decoupling designBased on scalar decoupling theory [5], the stator voltagescommands are given in the form:⎧⎪⎪⎪⎨⎪⎪⎪⎩Uds = Rsids − weσLsiqs = Rsids − weLliqs,Uqs = Rsiqs + weσLsids + LmLrweλref= Rsiqs + weσLsids + weλref .(10)Because of fast and good flux tracking, poor dynamics decouplingperformance exerts less effect on the control Speed-flux observer designBased on the theory of negative feedback, the design ofspeed-flux observer must be robust to motor parameter speed-flux observer here is based on the slidingmode technique described in [6∼8]. The observer equationsare based on the induction motor current and flux equationsin stationary reference frame.⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩d˜idsdt= ηβ˜λdr + β ˜ wr˜λqr − γ˜ids +1LlVds,d˜iqsdt= −β ˜ wr˜λdr + ηβ˜λqr − γ˜iqs +1LlVqs,d˜λdrdt= −η˜λdr − ˜ wr˜λqr + ηLm˜ids,d˜λqrdt= ˜wr˜λ dr − η˜λqr + ηLm˜iqs.(11)Define a sliding surface as:s = (˜iqs − iqs)˜λdr − (˜ids − ids)˜λqr. (12)Let a Lyapunov function beV = . (13)After some algebraic derivation, it can be found that when˜ wr = w0sgn(s) with w0 chosen large enough at all time,then ˙V = ˙s · s 0. This shows that s will converge tozero in a finite time, implying the stator current estimatesand rotor flux estimates will converge to their real valuesin a finite time [8]. To find the equivalent value of estimatewr (the smoothed estimate of speed, since estimate wr is aswitching function), the equation must be solved [8]. Thisyields:˜ weq = wr˜λqrλqr + λdr˜λdr˜λ2qr +˜λ2dr −ηnp˜λqrλdr − λqr˜λdr˜λ2qr +˜λ2dr. (14)The equation implies that if the flux estimates converge totheir real values, the equivalent speed will be equal to thereal speed. But the Equation (14) for equivalent speed cannotbe used as given in the observer since it contains unknownterms. A low pass filter is used instead,˜ weq =11 + s · τ˜ wr. (15)Y. LIU et al. / Journal of Control Theory and Applications 2007 5 (1) 42–46 45The same low pass filter is also introduced to the systeminput,which guarantees that the input matches the feedbackin selection of the speed gain w0 has two major constraints:1) The gain has to be large enough to insure that slidingmode can be ) A very large gain can yield to instability of the simulations, an adaptive gain of the slidingmode observer to the equivalent speed is = k1 ˜ weq + k2. (16)From Equation (11), the sliding mode observer structureallows for the simultaneous observation of rotor Flux reference optimal designThe flux reference can either be left constant or modifiedto accomplish certain requirements (minimum current,maximum efficiency, field weakening) [9,10]. In this paper,the flux reference is chosen to maximum efficiency at steadystate and is weaken for speeds above rated. The optimal efficiencyflux can be calculated as a function of the torquereference [9].λdr−opt = |Teref| · 4Rs · L2r/L2m + Rr. (17)Equation (17) states that if the torque request Teref iszero, Equation (8) presents a singularity. Moreover, theanalysis of Equation (17) does not consider the flux fact, for speeds above rated, it is necessary toweaken the flux so that the supply voltage limits are not improved optimum flux reference is then calculatedas:⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩λref = λdr-opt,if λmin λdr-opt λdr-rated ·wratedwr-actual,λref = λmin, if λdr-opt λmin,λref = λdr-rated ·wratedwr-actual,if λdr-opt λdr-rated ·wratedwr-actual.(18)where λmin is a minimum value to avoid the division SimulationsThe rated parameters of the motor used in the simulationsare given byRs = Ω, Rr = Ω, Lls = 75 H,Llr = 105 H, Lm = mH, Ls = Lls + Lm,Lr = Llr + Lm, P = 4, Jmot = kgm2,J = Jmot +MR2tire/Rf, ρair = , Cd = = m2, Rf = , Cr = = m, M = 3000 kg, wbase = 5400 rpm,λdr−rated = shows the torque reference curve that representstypical operating behaviors in a hybrid electric . 4 The torque reference torque is modeled by considering the aerodynamic,rolling resistance and road grade forces. Its expression isgiven byTL = RtireRf(12ρairCdAfv2 +MCr cos αg +M sin αg).Figures in [5∼8] show the simulation results of thesystem of (considering variable motor parameters).Though a small estimation error can be noticed on the observedfluxes and speed, the torque tracking is still achievedat an acceptable level as shown in Figs. [5, 6, 8]. The torquecontrol over a wide range of speed presents less sensitivityto motor parameters presents the d and q components of the rotor flux λr is precisely orientated to d-axis because of theimproved PI shows clearly the real and observed speed in thedifferent phases of acceleration, constant and decelerationspeed with the motor control torque of . The variablemodel parameters exert less influence on speed shows the power loss when the rotor flux keeps constantor optimal state. A significant improvement in powerlosses is noticed due to reducing the flux reference duringthe periods of low torque . 5 Motor rotor flux λ Y. LIU et al. / Journal of Control Theory and Applications 2007 5 (1) 42–46Fig. 6 Motor . 7 Power . 8 Motor ConclusionsThis paper has described a sensorless torque control systemfor a high-performance induction motor drive for aHEV case. The system allows for fast and good torquetracking over a wide range of speed even in the presence ofmotor parameters uncertainty. In this paper, the improvedPI-based FOC controllers show a good performance in therotor flux λdr magnitude and its orientation tracking. Thespeed-flux observer described here is based on the slidingmode technique, making it independent of the motor adaptation of the speed -flux observer is used tostabilize the observer when integration errors are present.
Robotics education in the university* Rafael M. Inigo and Jose M. Angulo School of Engineering and Applied Science, University of Virginia, Charlottesville, Virginia 22901, USADept. de Informatica, Universidad de Deusto, Bilbao, Spain Available online 28 October 2004. The importance of automation and robotics in modern factories has required the introduction of courses on these subjects at the graduate and undergraduate levels in engineering schools. A comprehensive course on robotics must include the following subjects of fundamental importance: kinematics, dynamics, computer hardware and software, automatic control and machine vision. This paper describes the authors' experience in teaching a graduate robotics course at the University of Virginia and a short summer course at the Universidad de Deusto in Spain. Hands-on experience is a must in courses on robotics, and some simple yet effective systems designed and constructed by students are described. These include a program for transformation matrix manipulation, an operating system for manipulator control, and a simple three degrees of freedom programmable manipulator. The majority of the students who took both courses were electrical engineers, but mechanical engineers and computer scientists were also enrolled. Author Keywords: Robotics Education; Robotics Laboratory; Hardware; Software Development For Robotics Education *Parts of this paper were presented at the Second annual workshop on interactive computing, CAD/CAM: Electrical Engineering Education Washington,
我也，用彭坤，胡健，张姣，彭利等名字，冒充湖南工程学院学报，湖南科技学院学报，湖南城市学院学报等到处钱
性 别： 男出生年月： 1965年8月民 族： 汉职称职务： 教授最后学历学位： 博士研究方向学科专业领域： 机械设计制造主要研究方向： 磨削技术及其数控装备；汽车设计制造，摩擦学。主要工作经历1980年至1984年， 在湖南大学机械与汽车工程学院学习；1985年至1988年，在东南大学研究生院学习；1989年至1992年，在西安交通大学研究生院获博士学位；1993年至1994年，在清华大学研究生院做博士后；2007年1月至2008年3月， 在英国Nottingham 大学工作；2002年9月至2004年9月 在英国 London大学作高级访问学者。主要社会兼职有： 湖南大学学术骨干，湖南省后备学术带头人，中国机械工程学会高级会员，国家科技部863项目评委, 国家自然科学基金评审专家, 科技部中国科技信息所中国科技期刊评审专家，国家教育部科技项目、科技奖励评审专家，湖南省科技奖励评审专家，湖南省自然科学基金评审专家，国家高效磨削工程技术研究中心研究员，硕士研究生导师，国家985高技术研究（汽车先进设计与制造创新团队）学术骨干。中国科技论文在线评审专家，全国中文科技核心期刊《精密制造与自动化》杂志编委。国际著名科技期刊[特约审稿人,全国一级科技期刊《振动工程学报》、《湖南大学学报》审稿人。湖南省一级科技期刊《湖南文理学院学报》特约审稿人。英国国际制造科学研究会理事，英国Sheffield大学兼职教授等。