T.Lehtla, Ph.D
Tallinn Technical University, Estonia
Abstract. The paper describes a method of parameter identification of an equivalent circuit of an induction motor using fuzzy logic controller. The method is based on the stepbystep approach in which the parameters are calculated from an equivalent circuit and real measured speedtorque characteristic. The displacement of two characteristics as a complex input variable for a fuzzy logic controller is used. In order to demonstrate the reliability of the proposed methods, an example of speedtorque characteristic of induction motors and parameter determination of an equivalent circuit is discussed.
Keywords. AC induction motor, speedtorque characteristic,
equivalent circuit parameters, fuzzy logic controller
INTRODUCTION
During the last years, the significance of the squirrel
cage induction motors in speed and position controlled drives have grown
drastically. The reason is the largescale exploitation of the AC induction
motors in the technolgies which traditionally used DC motors. Futhermore,
to achieve high efficiency of the technology, many noncontrolled AC drives
are reconstructed by adding frequency converters, and they are used now
as speed controlled drives. To attach perfect static and dynamic qualities
of these drives, control engineers need more information about the control
object. Therefore, the importance of the characteristics and parameter
determination of the squirrel cage induction motor has markedly grown.
The most important means of the drive design and control is a perfect model
of a motor. Moreover the modelbased control methods of the induction motor
drives are most effective and usable.
MODELS
Many different models available for squirrel cage induction motors are sucessfully used for drive design and control. Generally, these models can be classified as static or dynamic, linear or nonlinear, partial or integral (Fig. 1). In addition, models with lumped or distributed parameters exist. A singlephase equivalent circuit with lumped parameters is the most traditional model of an AC induction motor. Several modifications of the Kloss formula are derived from this circuit for the calculation of speedtorque characteristics. However, for a squirrel cage induction motor, this model does not satisfy the conditions of exact calculations.
Parameter determination of an equivalent circuit for a squirrel cage induction motor is a complex problem, because no reliable theory exists and no methods of direct measurements in a rotor circuit are available. The skin effect in the rotor winding and the iron core saturation effect lead to complications in the modelling process of a squirrel cage motor. Therefore indirect measurement methods and calculations must be used for the parameter determination from the data given by reference or by experimentally measured speedtorque characteristics.
It is relatively simple to calculate speedtorque characteristics from the data of an equivalent circuit, but it is much more complicated to solve the inverse problem  to calculate parameters from a referred characteristic, because an equivalent circuit can be varied and many different parameters can be chosen.
There are many kinds of equivalent circuits, used to calculate the speedtorque characteristics (Fig. 2). The equivalent circuits a and b could be sucessfully used for wound rotor induction machine, but due to skin effect in the case of a squirrel cage motor, the calculated speedtorque characteristic differs markedly from the real characteristic.
The scheme c could be used for induction motors with large airgap, such as the magnetohydrodynamical (MHD) pumps and some types of linear motors. In special cases, also the schemes d and e could be used. The scheme e is useful for the analysis of vector controlled AC induction motor drive, where the electromotive force is observed and the AC motor like a DC motor can be accepted. There are many ways to calculate speedtorque characteristic of the squirrel cage induction motor.
Figure 1. The classification of models
The method, offered by E. Risthein [1], allows us to calculate the torque in a large range of slip variation s = 0...2. The torque can be calculated as a sum of two or three components, each of which is similar to the Kloss formula. The basic advantage of the given method is the possibility to calculate the speedtorque characteristic in a large range of rotor slip variation and the fact, that the calculations take into consideration the real physical effects. Due to the skin effect and variation of the rotor resistance during the starting process there are two torque maximums. The drawback is that it does not enable the calculation of the speedtorque characteristic as a function of equivalent circuit parameters.
The second way to calculate the speedtorque characteristic for the equivalent circuits given in Fig. 2, is most traditional, but it is possible only for the small slip s < smax condition. Due to the skin effect, the calculated torque on the slip range 2 > s > smax differs considerably from the real torque.
The third method can be characterized as an exact, but a very complex one. Therefore any simplest method of calculation of the speedtorque characteristic, based on the physical model of the induction motor and giving satisfactory results, is useful.
We can combine the second and the third method, and the skin effect in rotor winding can be considered if we use a special class of equivalent circuits. The Figure 3 shows the three versions of equivalent circuits, which allow the calculation of the speedtorque characteristics for a largerange of slip variation.
The rotor winding equivalent circuit consists of a chain
of RL links with lumped parameters. The most suitable equivalent circuits
are shown in Fig. 3a and 3b. The number of rotor circuit
resistance and inductance components may be varied. Furthermore, the rotor
inductance can be segregated into frequency dependent and saturation dependent
components [3]. The three link (four impedants) equivalent circuit (ladder
network) is shown in Fig. 3c and is described in [3].
Figure 2. The equivalent circuits of AC induction motor
Figure 3. The equivalent circuits for considering the skin effect of the AC induction motor
EQUIVALENT CIRCUIT PARAMETER DETERMINATION
The usual approach is to divide the deep bars of rotor winding into selections and form two or more separate notional "cages". The parameters of partial cages are then calculated from the proposed dimensions of these selections. The multilink (ladder network) equivalent circuit parameters can be computed by using single slot finite element method and by approximative choosing of parameter values, which give best agreement between the impedance of the bar and the input impedance of the lader network, over the desired frequency range [3].
An alternative rotor impedance approximation by choosing
of component values can be realised, if we use the method, based on the
stepbystep approach of the calculated from equivalent circuit and real
measured speedtorque characteristics. The displacement of two characteristics
as a complex input variable for the fuzzy logic controller is used.
Calculation of initial reference parameters
Commonly, the AC induction motor is defined by the output
parameters, given in the catalogues:
Nominal output power, Pnom
Nominal frequency, fnom
Nominal voltage, Unom
Nominal speed or slip, snom
Efficiency, hnom
Nominal power factor cosjnom
Relative maximum torque Tmax / Tnom
Relative starting torque Tst / Tnom
Relative minimum torque Tmin / Tnom
Relative starting current Ist /Inom
These output values can be used for the calculations, to determine the parameters of any proposed equivalent circuits. First, the rated parameters for initial reference must be calculated.
The nominal speed
, (4)
.
. (5)
, (9)
.
Determination of the speedtorque characteristics
The methods of the determination of the speedtorque characteristics can be divided into three groups.
The second method, providing the direct measurement of torque, is most accurate. However, torque sensors are usually relatively expensive. Therefore this method may be used mainly in large stationary laboratories.
The third method is the simplest and the cheapest one. Futhermore, it allows us to determine the characteristic in dynamic conditions. Thus, this method was realised in the laboratory.
The squirrel cage induction motor was loaded dynamically by inertial mass to slow down the starting process. The signal of the speed sensor (in this case DC tachogenerator) was registered by digital oscilloscope. Next, the PC data processing was realized. Data processing included: 1) the numerical filtering of the measured signal; 2) the approximation of the transients with polynomial functions; 3) the function differentiation and calculation of the acceleration transient process, and 4) the calculation of the speedtorque characteristic. The results of this data processing are shown in Fig. 4.
[missing figure]
Figure 4. The determination of the speedtorque characteristic of the AC induction motor by the calculation of the derivation of the measured speed curve
The first curve (a) illustrates the real starting
process of an induction motor, which is registered as the sugnal of a DC
tachogenerator, connected to a motor shaft. The next curve (b) is
the numerically filtered signal. The third curve (c) presents the
eighth order polynomial function, which is the best approximate function
to describe the starting transient process of a motor. The fourth curve
(d) is the derivation of the polynomial function. It is proportional
to the torque of the unloaded motor. The last curve (e) is the dynamic
speedtorque characteristic of the induction motor. If a large moment of
inertia occurs, for example, when the high inertia wheel is connected to
the motor shaft, the found curve is very close to a real static speedtorque
characteristic. To calculate the equivalent circuit parameters, the speedtorque
characteristic may be determined experimentally, as we described it or
given by reference (by motor vendors). For the parameter determination,
a special algorithm of stepbystep approach and a fuzzy logic controller
were developed and used.
Fuzzy parameter determination system
The block diagram of the equivalent circuit parameter determination is shown in Fig. 5. The first operations of this algorithm, as the speedtorque characteristic determination was described in the preceding section of this paper. The following operation is the stepbystep approximation of the speedtorque curve, to estimate the equivalent circuit parameters.
The input values for a fuzzy logic controller are obtained by comparing the speedtorque characteristics calculated from an equivalent circuit and the reference. The displacements between two characteristics are evaluated in four points. These are: the rated slip point, the maximum torque point, the minimum torque point and the starting torque point (Fig. 6). These data may be used as referent inputs for calculations. These data, compared with the results of the calculations, yielded 24 = 16 error functions. After the linguistic evaluation of the error functions, the decision making logic of the fuzzy controller is used to approach the characteristics.
To evaluate of the linguistic values, terms less and more were used. The minimal rule base with 16 rules is shown in Table 1. A more exact solution can be achieved, if there are three linguistic terms (less, normal and more) for every variable used (Table 2).
Table 1



























Table 2
LL  LN  LM  NL  NN  NM  ML  MN  MM  
LL  R1  R2  R3  R4  R5  R6  R7  R8  R9 
LN  
LM  
NL  
NN  
NM  R i  
ML  
MN  
MM  R81 
The dimension of the rule base grows markedly with the number of used terms, because 34 = 81. The approximation process will befinished, when the value of the error functions becomes smaller, than the allowed reference value, and the determined parameters of an equivalent circuit will be printed out.
Figure 5. The algorithm of computer controlled determination
of induction motor characteristics and parameters
Figure 6. Fourpoint error functions of the characteristic
The rule base consists of IF x AND y THEN z kind of sentences. For example, in the case of the state MLML (Table 1) and an equivalent circuit in Fig. 3a, the rule R11 can be realized as:
IF Tmin > T'min AND Tst < T'st AND Tn < T'n AND Tmax < T'max THEN values (Rs, Ls, Lr1, Lr2, Rr1, Rr2, Rr) = new values (kiRs, kiLs, kiLr1, kiLr2, kiRr1, kiRr2, kiRr),
where the coefficient ki is a variable, which considers the value of error (displacement between two characteristics) and the effect of different parameters to the speedtorque curve. The initial reference values of ki are relatively large, but during the calculation process, if the approximate curve becomes closer to the referred curve, the values of ki will also diminish.
The result of the computer controlled stepbystep approach of the speedtorque characteristics and the parameters of an equivalent circuit for a VOLTA motor in comparision with BALDOR motors are shown in Table 3 and Fig. 7.
Table 3
Parameter  Type0735M
BALDOR 
Type 0940M
BALDOR 
Type 4A132
VOLTA 
Power, W  5 516  11 030  11 000 
Nom. speed  1 800  1 800  1 500 
Rs, W  0.793  0.350  0.332 
Rr, W  0.155  0.086  0.089 
Rr1, W  2.24  0.931  1.249 
Rr2, W  0.533  0.261  0.178 
Lm  0.164  0.117  0.121 
Ls  0.00639  0.00393  0.0033 
Lr1  0.00393  0.00190  0.0009 
Lr2  0.00655  0.00455  0.0041 
Figure 7. The computer controlled process of the stepbystep approach of the parameter determination
FURTHER APPLICATIONS
The further applications in the field of electrical drives are characterized with: 1) more complex control systems; 2) indefinite conditions of function environment; 3) multidimensionality (MIMO  multiinput, multioutput systems) and 4) knowledgebased approach to the control and identification problems.
Consequently, it may be concluded that the computeraided
fuzzy logic controller is a most suitable means for several tasks of parameter
determination in an electrical equipment diagnostics system (in industrial
automation).
REFERENCES: