湖南工程学院学报审稿周期

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.

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就是一个学校的校报，不是核心期刊

啊,我才小学

在当今能源越来越缺少的社会上，能源与节能技术是不可缺少的。下面我给大家分享一些能源与节能技术论文，大家快来跟我一起欣赏吧。

新能源汽车节能技术的应用

摘 要 伴随着第二次工业革命发展，汽车行业如雨后春笋迅速的成长，但汽车在给人们出行带来方便的同时资源和环境也付出了巨大的代价。汽车的生产和使用需要大量的钢材和石油，而制成钢材的原材料和石油是不可再生资源，因此面对汽车的大量生产这些不可再生的能源将会逐步的枯竭。所以对新能源汽车的开发与节能技术的研究对减少使用不可再生资源有重大的意义。

关键词 新能源车;节能技术;应用

中图分类号TU5 文献标识码A 文章 编号 1674-6708(2013)95-0191-02

0引言

当今社会经济和科技在不断的快速发展的同时能源消耗太大造成能源不断的枯竭与环境污染严重等问题日益明显。如今全世界各个地方都在提倡节能、减排。绿色环保则成了当今社会上的主体。如今汽车行业已经成为世界上最大的能源消耗和污染行业之一。而要解决能源消耗与环境污染问题就应该先从汽车行业抓起，减少能源消耗和污染。

1汽车的节能技术

混合动力技术

混合动力一般指由汽油、柴油与电能混合在仪器所形成的动力。这项技术的关键是混合动力系统。混合动力系统关系着整个车的性能。再经过多年混合动力研究的基础上，将原来的点火装置转变为由电动马达作为发动机的辅助动力来驱动汽车。由原来的离散结构向着一体化结构发展。也就是将发动机和电机与变速箱结合在一起。在启动的时候辅助发动机的电动马达可以产生很强的动力，也可以在汽车高速平稳的行驶时间段内减少发动机的出力减少油耗。而且混合动力技术能够对能量进行回收。在制动的时候，能够对热量进行转变吸收。

混合动力技术的分类可分为两类一是联结方式二是混合度;联结式分类是根据混合动力的驱动方式进行分的，其中联结式分类又分为了3种：1)串联式混合动力系统是由电能转化为动能从而驱动车轮转动，其中的电力是由内燃机带动发电机来引起的;2)并联式的混合动力系统区中的驱动系统内有两套，并且两套的驱动系统能够可以相互协调来共同完成驱动车辆，当然也可以使用单独的驱动系统来驱动车辆。这样的并联式混合驱动系统能够使车辆适用于更为复杂的路况;3)混联式混合驱动系统可以根据不同的路况来临时调节内部机器的输出功率的原因是因为它的内部中的内燃机和电机有自己的一套机械变速箱而且混合动力系统还可以分为以下4类：1)微混合动力系统该系统可以有效的防止电动机的不运转从而增加油耗和对环境的污染。对发动机的启动和停止进行控制;2)轻混合动力系统，而这种系统的主要代表是皮卡车;3)中混合动力系统动力系统采用的是高压机比低混合动力系统更加的灵敏;4)完全混合动力系统的混合度达到50%是未来逐步发展的方向。

高效汽油机、柴油机技术

汽车节能的关键是内燃机的技术。在内燃机节能技术方面，应该从这几个方面讨论， 第一是汽油机直喷技术，稀薄和分层燃烧技术;第二是柴油机的高压喷射技术;第三是柴油机的多次喷射技术;第四是可变气门技术;第五是废气涡轮增压技术。

高效载重汽车的发动机技术

目前我国载重汽车品种少，技术还很落后。发展高效的载重汽车，是在现代物欲横流的形势下，提高运输的效率，降低汽车用能源消耗的重要一步。因此，国家应重点支持这种高效载重汽车的开发和产业化发展。

轿车、轻型车的柴油化技术

实现节能的重要途径是柴油化，随着汽车以很快的速度进入家庭，我们应该十分注重这项技术。不断的开发而且要有质量的保证。这样的话就减少了对能源的开发。实现了节能减排。

2新能源汽车节能技术的应用

混合动力汽车

混合动力一般指由汽油、柴油与电能混合在仪器所形成的动力车型。这样能有效的改善燃油和功率输出低的车型。根据其不同，主要又可以分为汽油混合动力和柴油混合动力两种。他的优点是：1)采用混合动力后可以增加汽车内部机器功率的输出和减少耗油量。当大功率内燃机功率不足时，可由电池来补充，同时电池也可以得到充电，所以其行程和普通汽车是一样的;2)因为使用电池，可以方便地回收以便循环使用;3)在市中心人流量大的地方，完全用电池单独驱动，实现“零”排放;4)可以在现有的加油站加油，不必再投资建设新的加油站;5)用户可以让电池在延长寿命和降低成本的基础上保持良好的工作状态。

纯电动汽车

纯电动汽车是直接采用电机作为驱动器，是全部以电力作为汽车的驱动力这种车的难点在于电力的储存技术。传统汽车消耗石油等不可再生能源造成能源消耗和环境污染，而电能可以从核能、水力和风力等可再生能源中获得且无污染。电动汽车还可以利用在其空余的时间进行充电，使发电设备日夜都能充分使用，大大提高它的行驶效率。由于这些优点，电动汽车的应用成为汽车工业的一个非常关心的问题。对于电动车而言由于建设成本高且基础设施不是一个独立的企业就能够完成的，需要各个企业联合起来与当地政府部门一起努力，才可能大规模的推广。这使得电动汽车的价格非常的高昂，但是与混合动力汽车相比较来说电动汽车的技术简单而且成熟且操作方便，且只要有足够的电力就能驱动汽车且充电方便。但是不足就是电动车所使用的蓄电池的蓄电能力不足存储的电量少，且构建电池的原材料成本高还没有形成一定的经济规模，所以购买价格高。

燃料电池汽车

燃料电池汽车是以液化石油气(LPG)和压缩天然气为燃料，采用先进的电子控制技术和高性能的污染净化装置来减少污染。而且经过有机材料的化学反应产生的电流作为汽车的驱动力。

近年来燃料电池技术已经取得了重大的突破。燃料电池汽车，零排放，而且减少了机油泄漏带来的水污染和温室气体的排放等问题，还提高了燃油经济和发动机燃烧效率，运行平稳，没有噪声。

氢动力汽车

氢动力汽车是真正实现零排放的，排放出来的是纯净水，没有任何污染。

但是氢燃料电池成本高，而且发展氢燃料的存储和运输按照技术条件很难实现，还有就是氢气的提取需要通过电解水，否则就不能从根本上降低二氧化碳排放。

这项技术虽然实施起来困难，但是随着新能源技术的不断发展，一定会得以解决实现。

3发展前景

随着国家政府部门的不断指引，各项政策的不断支持，新能源汽车的应用有很大的发展前景，新能源汽车节能技术的应用也会越来越广泛，并且应用在人们的日常生活中，给人们的生活带来很大的便利。通过不断的发展新的技术，以最低的成

本换取最大的经济效益，也将会引领新能源汽车走上一个更新，更广阔的台阶。

4结论

科学技术永远是第一生产力。汽车的迅猛发展，人们素养的不断提高，在大力提倡生态文明建设，打造美丽中国的时代背景下，人们对环境的要求会越来越高。

更加环保的的汽车会越来越受到人们的欢迎。而新能源的开发会越来越重要，那么新能源汽车节能技术的应用会越来越广阔，越来越受到人们的重视。

时代总是在不断的发展，科技也不断在进步。新能源汽车节能技术的应用将会备受重视。

参考文献

[1]史永基，高雅利，王宇炎.新能源节能技术研究进展，2011(7).

[2]__达，望义熙，周世权.汽车电器的研究，2010(11).

[3]李大胜，吕明，石怀荣.湖南工程学院学报，2011(2).

[4]邵毅明.汽车新能源与节能技术，2008-3-1.

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