Published on

  • Be the first to comment

  • Be the first to like this

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide


  1. 1. Y.Sumith, J.S.V.Siva Kumar / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 5, September- October 2012, pp.1668-1674 Estimation Of parameter For Induction Motor Drive Y.Sumith*, J.S.V.Siva Kumar * PG Scholar, E.E.E Dept., G.M.R Institute of Technology, Rajam , Andhra Pradesh, India ** Assistant Professor, E.E.E Dept., G.M.R Institute of Technology, Rajam , Andhra Pradesh, IndiaABSTRACT Generally speed measurement is done high speed switching devices such as IGBTs werewith sensor, but disadvantage of sensor is introduced and more precise motor controldifficult to measure speed at low speeds with strategies, such as vector control techniques, weresensor. These difficulties are eliminated by using developed. As a result, today IMs can be used in anysensor less Flux Orientation Controlled (FOC) . kind of variable speed applications, even as a This paper proposes a Model Reference servomechanism, where high-speed response andAdaptive System (MRAS) for estimation of rotor extreme accuracy is required.speed in FOC. An Induction motor is developedin stationary reference frame and Space Vector The two names for the same type of motor,Modulation (SVM) is used for inverter induction motor and asynchronous motor, describedesign.PID controllers are designed for this FOC. the two characteristics in which this type of motorIt has good tracking and attains steady state differs from DC motors and synchronous motors.response very quickly which is shown in Induction refers to the fact that the field in the rotorsimulation results. is induced by the stator currents, and asynchronous refers to the fact that the rotor speed is not equal toKeywords – Sensor less field orientation control the stator frequency. No sliding contacts and(FOC), Model Reference Adaptive System permanent magnets are needed to make an IM work,(MRAS), Induction motor drive, Speed which makes it very simple and cheap toestimation. manufacture. As motors, they rugged and require very little maintenance. However, their speeds are1. INTRODUCTION not as easily controlled as with DC motors. They Induction motor (IM) can be considered as draw large starting currents, and operate with a poorthe ‘workhorse’ of the industry because of its lagging factor when lightly loaded.special features such as low cost, high reliability,low inertia, simplicity and ruggedness. Even today 2.DYNAMIC MODELING OFIMs especially the squirrel cage type, are widely INDUCTION MACHINEused for single speed applications rather than Generally, an IM can be described uniquelyvariable speed applications due to the complexity of in arbitrary rotating frame, stationary referencecontrolling algorithm and higher production cost of frame or synchronously rotating frame. For transientIM. studies of adjustable speed drives, it is usually more convenient to simulate an IM and its converter on a Variable speed drives. However, there is a stationary reference frame. Moreover, calculationsgreat interest on variable speed operation of IM with stationary reference frame are less complex duewithin the research community mainly because IMs to zero frame speed. For small signal stabilitycan be considered as a major industrial load of a analysis about some operating condition, apower system. On the other hand the IMs consume a synchronously rotating frame which yields steadyconsiderable amount of electricity generated. The values of steady-state voltages and currents undermajority of IMs are operated at constant speed, balanced conditions is used.determined by the pole pair number and the stator From the below figure the terminal voltages are assupply frequency. follows, Vqs = Rqiqs + p (Lqqiqs) + p (Lqdids) + p (Lq i ) + p It is well known fact that electric energy (Lqi)consumption of the appliances can be reduced by Vds = p (Ldqiqs) + Rdids + p (Lddids) + p (Ldi) + pcontrolling the speed of the motor. The three phasevariable speed IM drives are therefore encouraged to (Ldi) (1)be used in the industry today as an attractive V = p (Lqiqs) + p (Ldids)+ Ri + p (Li) + psolution forever increasing electricity generation (Li)cost. V = p (Lqiqs) + p (Ldids) + p (Li) + R i + p (Li) During the last decade, with theadvancement of power electronics technology, a 1668 | P a g e
  2. 2. Y.Sumith, J.S.V.Siva Kumar / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 5, September- October 2012, pp.1668-1674 frame dynamic model. The dynamic equations of the induction motor in any reference frame can be represented by using flux linkages as variables. This involves the reduction of a number of variables in the dynamic equations. Even when the voltages and currents are discontinuous the flux linkages are continuous. The stator and rotor flux linkages in the stator reference frame are defined as  qs  Ls iqs  Lm iqr  ds  Ls ids  Lm idr -------------- (2) Fig .1 Two-phase equivalent diagram of induction motor  qr  Lr iqr  Lm iqs Where p is the differential operator d/dt,  dr  Lr idr  Lm ids and vqs, vds are the terminal voltages of the stator q axis and d axis. V, V are the voltages of rotor   qm  Lm (iqs  iqr ) and  windings, respectively. is and ids are the stator -------------- (3) q axis and d axis currents. Whereas i and i are the  dm  Lm (ids  idr ) rotor  and  winding currents, respectively and Lqq, Stator and rotor voltage and current equations Ldd, L and L are the stator q and d axis winding are as follows and rotor  and  winding self-inductances, respectively. vds  Rs ids  p ds The following are the assumptions made in vqs  Rs iqs  p qs order to simplify vdr  Rr idr   r qr  p dr -------------- (4) i. Uniform air-gap ii. Balanced rotor and stator vqr  Rr iqr   r dr  p qr windings with sinusoidal distributed mmfs Since the rotor windings are short circuited,iii. Inductance in rotor position is the rotor voltages are zero. Therefore sinusoidal andiv. Saturation and parameter changes Rr idr  r qr  p dr  0 are neglected Rr iqr  r dr  p qr  0 ---------------- (5) The rotor equations are refereed to stator side as in the case of transformer equivalent circuit. From this, From (5), we have the physical isolation between stator and rotor d-q  p dr   r qr axis is eliminated. i dr  Rr  p qr   r dr -------------- (6) i qr  Rr By solving the equations (4)-(6) we get the following equations  ds   (vds  Rs ids )dt ---------------- (7)  qs   (vqs  Rs iqs )dt ----------------- (8)  Lr  r qr  Lm ids Rr  dr  ------------------ (9) Rr  sLr Figure 2 (b) Dynamic de-qe equivalent circuits of Lr  r dr  Lm Rr iqs machine (a) qe-axis circuit, (b) de-axis circuit  qr  ------------------ (10) Rr  sLr Figure 2 shows the de-qe dynamic model equivalent circuit of induction motor under synchronously rotating reference frame, if vqr = vdr = 0 and we=0 then it becomes stationary reference 1669 | P a g e
  3. 3. Y.Sumith, J.S.V.Siva Kumar / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 5, September- October 2012, pp.1668-1674 vds   dr .sLm  output.ids    ------------- (11) Rs  sLs  Lr .(Rs  sLs )  vqs   qr .sLm iqs    ------------- (12) Rs  sLs  Lr .(Rs  sLs )  The electromagnetic torque of the induction motor in stator reference frame is given by 3 p Te  Lm (iqs idr  ids iqr ) -------------- (13) 22 3 p Lm or Te  (iqs dr  ids qr ) --------------(14) 2 2 Lr Fig 4: Schematic diagram of voltage source inverter 3. PRINCIPLE OF VECTOR CONTROL The fundamentals of vector control can be In reality, there are only six nonzero voltage vectors explained with the help of figure 3, where the and two zero voltage vectors as shown in Fig 5(a) & machine model is represented in a synchronously (b). rotating reference frame. Fig 3 Basic block diagram of vector control Vector control implementation principle with machine ds-qs model as shown The controller makes two stages of inverse transformation, as shown, so that the control currents and (a) i * correspond to the machine currents ids and iqs, qs respectively. In addition, the unit vector assures correct alignment of ids current with the flux vector ^ r and iqs perpendicular to it, as shown. It can be noted that the transformation and inverse transformation including the inverter ideally do not incorporate any dynamics, and therefore, the response to ids and iqs is instantaneous (neglecting computational and sampling delays). (b) Fig 5(a) Inverter Switching Stages, (b) Switching – 4. INVERTER voltage space vectors Processing of the torque status output and The machine voltages corresponding to the the flux status output is handled by the optimal switching states can be calculated by using the switching logic. Fig (4) shows the schematic following relations. diagram of voltage source inverter. The function of the optimal switching logic is to select the appropriate stator voltage vector that will satisfy both the torque status output and the flux status 1670 | P a g e
  4. 4. Y.Sumith, J.S.V.Siva Kumar / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 5, September- October 2012, pp.1668-1674v ab  v a  v b  model. The model that has the quantity to be  estimated involved is considered as the adaptivev bc  v b  v c  -------------------------- (15) model (or adjustable model). The output of thev ca  v c  v a   adaptive model is compared with that of the reference model, and the difference is used to drive a suitable adaptive mechanism whose output is the Sensor less vector control induction motor quantity to be estimated (the rotor speed). The drive essentially means vector control without any adaptive mechanism should be designed to assure speed sensor. An incremental shaft mounted speed the stability of the control system. A successful encoder, usually an optical type is required for MRAS design can yield the desired values with less closed loop speed or position control in both vector computational error (especially the rotor flux based control and scalar controlled drives. A speed signal MRAS) than an open loop calculation and often is also required in indirect vector control in the simpler to implement. whole speed range and in direct vector control for the low speed range, including the zero speed start The model reference adaptive system up operation. Speed encoders undesirable in a drive (MRAS) is one of the major approaches for adaptive because it adds cost and reliability problems, control [6]. The model reference adaptive system besides the need for a shaft extension and mounting (MRAS) is one of many promising techniques arrangement. employed in adaptive control. Among various types of adaptive system configuration, MRAS is important since it leads to relatively easy- to- implement systems with high speed of adaptation for a wide range of applications. Fig 6:Block Diagram of Sensor less Control of Induction Motor The schematic diagram of control strategy of induction motor with sensor less control is shown in Fig 4.. Sensor less control induction motor drive Fig 7: basic identification structures and their essentially means vector control without any speed correspondence with MRAS sensor [5]. The inherent coupling of motor is eliminated by controlling the motor by vector The basic scheme of the MRAS given in control, like in the case of as a separately excited Fig. 7 is called a parallel (output error method) motor. The inverter provides switching pulses for MRAS in order to differentiate it from other MRAS the control of the motor. The flux and speed configurations where the relative placement of the estimators are used to estimate the flux and speed reference model and of a adjustable system is not respectively. These signals then compared with the same. The MRAS scheme presented above are reference values and controlled by using the PI characterized by the fact that the reference model controller. was disposed in parallel with the adjustable system. In this scheme the reference and adjustable models 5. MODEL REFERENCING ADAPTIVE are located in series [6]. The use of parallel MRAS SYSTEM (MRAS) is determined by its excellent noise-rejection proper- Tamai [5] has proposed one speed ties that allow obtaining unbiased parameter estimation technique based on the Model Reference estimates. By contrast, ‘‘series–parallel’’ MRAS Adaptive System (MRAS) in 1987. Two years later, configurations always lead to biased parameter Schauder [6] presented an alternative MRAS estimations in presence of measurement noise [8]. scheme which is less complex and more effective. Reference model equations: Lr L2 The MRAS approach uses two models. The model r  ( (U s  Rs is )dt  ( Ls  m )is ) ------ (16) that does not involve the quantity to be estimated Lm Lr (the rotor speed, ωr) is considered as the reference 1671 | P a g e
  5. 5. Y.Sumith, J.S.V.Siva Kumar / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 5, September- October 2012, pp.1668-1674 Lr L2 axes voltages and load torque. The outputs are directr  ( (U s  Rs is )dt  ( Ls  m )is ) ---- (17) and quadrate axis rotor fluxes, direct and quadrature Lm Lr axes stator currents, electrical torque developed andAdjustable model equations rotor speed.d r L m   is   r r  r ------------ (18) dt Tr Trd r Lm  r  is   r r  ------------ (19) dt Tr TrError between reference and adjustable models:    r r  r r --------------------- (20)Estimated speed from PI controller is r  K p w  Ki   wdt --------------------- (21)6. VECTOR CONTROL OF INDUCTIONMOTOR DRIVE: The Vector Control or Field orientationcontrol of induction motor is simulated onMATLAB/SIMULINK - platform to study thevarious aspects of the controller. The actual system Fig.9: Simulink block diagram for induction motorcan be modeled with a high degree of accuracy in modelthis package. It provides a user interactive platformand a wide variety of numerical algorithms. This 6.2 INVERTERchapter discusses the realization of vector control of Fig 4 shows the Voltage Source Inverterinduction motor using Simulink blocks. (VSI), it consists of an Optimal Switching Logic Fig.8 shows the Vector controlled which is shown in Fig 10. The function of theInduction Motor block simulink diagram for optimal switching logic is to select the appropriatesimulation. This system consisting of Induction stator voltage vector that will satisfy both the torqueMotor Model, Three Phase to Two phase status output and the flux status output. Processingtransformation block, Two phase to Three phase of the torque status output and the flux status outputblock, Flux estimator block and Inverter block. is handled by the optimal switching logic. Fig 10 Voltage Source InverterFig 8: Simulink Model of Vector Controlled 6.3 Model Refernce Adaptive System (MRAS)Induction motor Fig 11 shows the simulink block diagram Model Referencing Adaptive System (MRAS).6.1 Induction Motor Model: Which is consists Two blocks one is called The motor is modeled in stator reference Reference Model and other is Adaptive Model. Theframe. The dynamic equations are given by (1) to voltage model’s stator-side equations, (16) & (17)(14). By using these equations we can develop the are defined as a Reference Model and the simulinkinduction motor model in stator reference frame. block diagram of Reference Model is shown inFig.9 shows the simulink block diagram for motor Fig11. The Adaptive Model receives the machinemodel. Inputs to this block are direct and quadrature stator voltage and current signals and calculates the 1672 | P a g e
  6. 6. Y.Sumith, J.S.V.Siva Kumar / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 5, September- October 2012, pp.1668-1674rotor flux vector signals, as indicated by equations, MATLAB/SIMULINK. The results for different(18) and (19) which is shown in Fig 11. By using cases are given below.suitable adaptive mechanism the speed r, can be (a)Reference speed = 100 rad/sec and on no-loadestimated and taken as feedback.Fig 11: Simulink block diagram for ModelReferencing Adaptive System6.4 Sensor less control of induction motor The Sensor less control of induction motorusing Model Reference Adaptive System (MRAS) issimulated on MATLAB/SIMULINK - platform tostudy the various aspects of the controller. Theactual system can be modeled with a high degree of Fig 13: 3- currents, Speed, and Torque for no-loadaccuracy in this package. It provides a user reference speed of 100 rad/secinteractive platform and a wide variety of numericalalgorithms. Here we are going to discuss therealization of Sensor less control of induction motorusing MRAS for simulink blocks. Fig. 12 shows theroot-block simulink diagram for simulation. Mainsubsystems are the 3-phase to 2-phasetransformation, 2-phase to 3-phase transformation,induction motor model, Model Reference AdaptiveSystem (MRAS) and optimal switching logic &inverter. Fig 14: Reference speed, Rotor Speed, Slip Speed RespectivelyFig 12: Simulink root block diagram of Sensorlesscontrol of induction motor using MRAS (b)Reference speed = 100 rad/sec; Load torque of 15 N-m is applied at t = 1.5 sec7. SIMULATION RESULTS The simulation of Vector Control ofInduction Motor is done by using 1673 | P a g e
  7. 7. Y.Sumith, J.S.V.Siva Kumar / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 5, September- October 2012, pp.1668-1674 torque wave and also the starting current is high. The main results obtained from the Simulation, the following observations are made. i) The transient response of the drive is fast, i.e. we are attaining steady state very quickly. ii) The speed response is same for both vector control and Sensor less control. iii) By using MRAS we are estimating the speed, which is same as that of actual speed of induction motor. Thus by using sensor less control we can get the same results as that of vector control without shaft encoder. Hence by using this proposed technique, we can reduce the cost of drive i.e. shaft encoder’s cost, we can also increase the ruggedness of the motor as well as fast dynamic response can be achieved.Fig 15: 3- currents, Speed, and Torque for no-loadreference speed of 100 rad/sec REFERENCES 1. Abbondanti, A. and Brennen, M.B. (1975). Variable speed induction motor drives use electronic slip calculator based on motor voltages and currents. IEEE Transactions on Industrial Applications, vol. IA-11, no. 5: pp. 483-488. 2. Nabae, A. (1982). Inverter fed induction motor drive system with and instantaneous slip estimation circuit. Int. Power Electronics Conf., pp. 322-327. 3. Jotten, R. and Maeder, G. (1983). Control methods for good dynamic performance induction motor drives based on current and voltages as measured quantities. IEEE Transactions on Industrial Applications, vol. IA-19, no. 3: pp. 356-363. 4. Baader, U., Depenbrock, M. and Gierse, G. (1989). Direct self control of inverter-fed induction machine, a 5. Tamai, S. (1987). Speed sensorless vectorFig 16: Reference speed, Rotor Speed, Slip Speed control of induction motor with modelRespectively reference adaptive system. Int. Industry Applications Society. pp. 189-195.7.1. Conclusion 6. Griva, G., Profumo, F., Illas, C.,In this thesis, Sensorless control of induction motor Magueranu, R. and Vranka, P. (1996). Ausing Model Reference Adaptive System (MRAS) unitary approach to speed sensorlesstechnique has been proposed. Sensorless control induction motor field oriented drives basedgives the benefits of Vector control without using on various model reference schemes.any shaft encoder. In this thesis the principle of IEEE/IAS Annual Meeting, pp. 1594-1599.vector control and Sensorless control of induction 7. Viorel, I. A. and Hedesiu, H. (1999). Onmotor is given elaborately. The mathematical model the induction motors speed estimator’sof the drive system has been developed and results robustness against their parameters. IEEEhave been simulated. Simulation results of Vector Journal. pp. 931-934.Control and Sensorless Control of induction motor 8. Amstrong, G. J., Atkinson, D. J. andusing MRAS technique were carried out by using Acarnley, P. P. (1997). A comparison ofMatlab/Simulink and from the analysis of the estimation techniques for sensorless vectorsimulation results, the transient and steady state controller induction motor drives. Proc. Ofperformance of the drive have been presented and IEEE-PEDS.analyzed. From the simulation results, it can beobserved that, in steady state there are ripples in 1674 | P a g e