United States
               Environmental Protection
               Agency
National Risk Management
Research Laboratory
Research Triangle Park, NC 27711
               Research and Development
EPA/600/SR-96/008
May 1996
EPA      Project Summary
               Efficiency Optimization  Control  of
               AC  Induction  Motors:  Initial
               Laboratory  Results
               M.W. Turner, V.E. McCormick, and J.G. Cleland
                 A fuzzy logic, energy optimizing con-
               troller has been developed to improve
               the  efficiency of motor/drive combina-
               tions which operate at  varying loads
               and speeds. This  energy optimizer is
               complemented by a sensorless speed
               controller which maintains motor shaft
               revolutions per minute  (rpm) to pro-
               duce constant output power. Efficiency
               gains of from 1 to 20% are obtained
               from laboratory demonstration  with
               commercial motors and drives. Motor
               shaft rpm is controlled to within 0.5%.
               The energy optimizing controller used
               for  "vector control" adjustable speed
               drives is complemented by a torque
               pulsation control  scheme  to  rapidly
               damp vibrations.
                 This Project Summary  was developed
               by  EPA's National Risk Management
               Research Laboratory's  Pollution Pre-
               vention and Control Division, Research
               Triangle Park, NC, to announce key
               findings of the research project that is
               fully documented  in a separate report
               of the same  title  (see Project Report
               ordering information at back).

               Introduction
                 Electric motors  use  over 60% of the
               electrical power generated in the U.S. The
               U.S. population of approximately 1 billion
               (109) motors consume over 1700 billion
               kWh per year.  Each year,  140 million new
               motors are sold. More than 80% of the
               electricity used by motors  is consumed by
               less than 1% of the  motor  population [mo-
               tors greater than 20 hp (142  kW)]. Each
               1% improvement in  motor  efficiency could
               result  in  savings of over $1  billion per
               year in energy costs,  6-10 million tons
               (5.4-9.1 million tonnes) less per year of
               combusted coal and approximately 15-20
 million tons (13.6-18.1 million tonnes) less
 carbon dioxide  released into the atmo-
 sphere.
  Adjustable speed  drives (ASDs) are
 power electric devices which allow control
 of the speed of rotation of electric motors.
 ASDs can provide a significant savings in
 energy for motors which spend a portion
 of their duty cycle operating at less than
 their rated speed and torque. Prior to the
 introduction  of ASDs, control of motor-
 driven devices such as fans and pumps
 were always controlled by valves, vanes,
 dampers, and other mechanical devices,
 which are inherently inefficient.
  Conventional  ASDs do not optimally
 minimize motor input power at any given
 motor speed and load torque.  The objec-
 tive of the research described in  this re-
 port has been to improve ASDs by adding
 controls which optimize  the ASD on the
 basis of energy efficiency. The research
 and development program was defined by
 the  following precepts:
  •  New controls must  work with com-
    mercial ASDs. Controllers should be
    able to  be  added to existing ASDs
    and/or integrated into new ASD de-
    signs.
  •  Motors of interest are those rated from
    5 to 5000 hp (3.7 to  3730 kW).
  •  Steady-state operation of large  mo-
    tors is emphasized.
  •  Simple, low-cost design is emphasized.
  •  The controllers  must reduce  energy
    consumption "significantly." A reduc-
    tion in overall energy use of 2%  is
    targeted for motors with rated  effi-
    ciencies above 85%  (large motors).

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  Controls are physically  integrated  into
the motor/ASD configuration as shown in
Figure 1. The qualitative interactive perfor-
mance of these components is the same
at essentially any scale. Energy optimiz-
ing controllers interface with the ASD to
minimize line power consumption.  In ac-
tual  applications,  the  direct-current (dc)
brake is replaced  by an actual load such
as a pump or conveyor belt. The dyna-
mometer is a research tool used to mea-
sure and  maintain a  specific simulated
load.
  Controllers that have  been  developed
under this project for two  kinds of adjust-
         able speed drives used with ac induction
         motors are
           1)   ASD Type 1: These ASDs  control
               the  frequency and voltage supplied
               to a motor by maintaining a  ratio of
               voltage to frequency that is the same
               as the ratio at the motor's rated con-
               ditions (e.g., 208V at 60 Hz, 104V at
               30  Hz). These drives are best for
               steady-state  operation (where load
               or speed fluctuations are only occa-
               sional or the dynamics are slow—on
               the  order of minutes rather than mil-
               liseconds or seconds).
                               2)  ASD Type 2:  These ASDs control
                                   frequency and current by  indirect
                                   vector control.  These drives are bet-
                                   ter for  dynamic operation and con-
                                   trolling  speed  under rapidly chang-
                                   ing load conditions, such as control
                                   of smaller motors in manufacturing,
                                   positioning, and computer-aided de-
                                   sign/manufacturing machining.

                               All  efficiency  optimization under  this
                             project  is based on a  fundamental  ap-
                             proach-the voltage  (for ASD Type 1) or
                  Fuzzy Logic
                  Energy Optimizer
          Feedback

          * Voltage
          * Current
          * Frequency
          * Power
                                                                                              Developed Torque
                                  Motor Load Signal
Control Signals

* Voltage/ Current
* Frequency
                                                     Stator
                                                     Temperature
                      Line
                 1   Power I  (230 VAC)
                                                                                         Dynamometer
                                                                                         Controller
                    Adjustable
                    Speed Drive
     Adjust AC
     Voltage,
                                      Current,
                                      Frequen.
                                                  T
AC
Induction
Motor
                                                                       Optical Shaft
                                                                       Encoder
                                          Flexible
                                          Coupling
                                        DC Power
Dynamometer/
DC Brake
 Figure 1. Motor research laboratory main component layout.

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the current (for ASD Type 2) is perturbed in
a manner that decreases the motor's input
power while the motor output power is main-
tained constant. By these means, the core
losses of the machine decrease while the
copper losses increase until the combined
core and copper losses  reach a minimum
value, as shown in Figure 2.

Fuzzy  Logic and  Control Designs
  The mathematical technique called fuzzy
logic offers a new approach to improving
ASD voltage/frequency/current control.
Fuzzy logic  has evolved from an esoteric
branch of mathematics into a useful engi-
neering  tool. By virtue of its adaptability, it
can be  applied to problems whose non-
linearity and dynamic nature makes them
intractable to solution via classical control
methods. Motor control  has  all  of the at-
tributes of this class of problems.  Fuzzy
logic has been implemented  in this devel-
opment of improved motor control because:
  1)   Fuzzy logic overcomes the math-
       ematical difficulties of modeling highly
       non-linear systems;
  2)   Fuzzy logic  responds in a  more
       stable fashion to imprecise readings
       of feedback control parameters, such
       as the dc link current and voltage;
       and
  3)   Fuzzy logic control mathematics and
       software are simple to develop and
       flexible for each modification.
  Three interactive efficiency-optimizing (in-
put power minimizing) controllers have been
developed for Type 1 ASDs. These control-
lers are  1) voltage  perturbation  for input
power  minimization, 2) speed correction,
and 3)  slip compensation.
  The  voltage perturbation controller  is
based  on changes in input power and sta-
tor voltage. Fuzzy logic control  has been
emphasized for voltage perturbation.  The
fuzzy logic  membership functions for  both
inputs and the output are partitioned using
five fuzzy sets.  The input variables are
AVsold  and  APin;  the  output variable  is
AVS  .  Triangular fuzzy sets are used for
                                     (using speed corrector control)
                                                                                Torque
                                                                                Speed
                                                                             DC Link Power
                                                                             Stator Voltage
                                                                                Total Machine
                                                                                Loss
                                                                                 Copper
                                                                                    Loss
                                                                                Converter
                                                                                    Loss
                                                                                 Iron Loss
                                          Efficiency Optimized     Time
                                            Operating Point
 Figure 2. Changes in core and copper losses with changing flux.

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both inputs and outputs, with a restriction
that the output fuzzy sets must be isosce-
les to simplify defuzzification.
  Membership functions  and the associ-
ated rule set are shown in Figure 3, where
input  and output  values  are represented
linguistically (i.e.,  NM=negative  medium,
NS=negative small,  ZE=zero, PS=positive
small, and PM=positive medium). The rule
base  table  can be  read according to the
following example: If the last voltage change
(AVSo|d ) is a "positive small" value and the
    measured input power change (APin) is a
    "negative small" value, then AVsnew is "posi-
    tive small."
       Speed correction control is needed  be-
    cause the perturbation approach alters mo-
    tor speed and output power.  The motor's
    output  rotor speed  should be maintained
    as constant as possible. For Type 1 ASDs,
    a fuzzy logic speed corrector controller was
    designed to correct for the speed change
    with voltage perturbation. The fuzzy speed
    controller uses voltage, commanded speed,
                     measured  frequency, and measured volt-
                     age to estimate  the  best new frequency
                     setting.
                       Slip compensation,  has also been devel-
                     oped to further reduce  motor power con-
                     sumption.  For  many  motor  ASD applica-
                     tions,  whenever  the  frequency  is  set,  a
                     higher  than  desired  rotor  speed  results,
                     using more power.  For example: If an op-
                     erator wishes to  reduce speed to 50% of
                     the rated value, the operator sets the fre-
                     quency from 60 to 30 Hz.  However, with
            -0.16-0.12-0.08-0.04  0
                               AV,.
0.04 0.08 0.12 0.16
-0.06  -0.04   -0.02
0.02   0.04   0.06
                                   'old
                                               A P.
                                                                                        in
                                                                                     AV,.
                                                                                         'old
                                                            A P.
                                                               in
            0
            -0.4  -0.3  -0.2  -0.1    0
                                AV,,
 0.1   0.2   0.3   0.4
                                     new
NM
NS
ZE
PS
PM
NM NS ZE PS PM
NM
NS
ZE
PS
PM
NS
NS
ZE
PS
PS
ZE
ZE
ZE
ZE
ZE
PS
PS
ZE
NS
NS
PM
PM
ZE
NS
NM
Figure 3. Membership functions and rule set for fuzzy voltage perturber.

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the frequency change, the slip, s,  of the
motor also changes.  Slip  is defined  as
Rotor speed/Frequency = 1-s. In this  re-
search,  the  slip compensation  control
mathematically estimates the slip  which
will result from  a given change in  fre-
quency, and adjusts  frequency to give
the desired percent speed.
  An  indirect vector controlled induction
motor drive  with an efficiency optimiza-
tion controller is shown  in Figure 4.  All
the control  functions  indicated  by  the
dashed  outline are implemented in real
time by  a  single digital signal processor.
The feedback speed control  loop gener-
ates the active  or torque current com-
mand iqs*.  The vector rotator receives the
torque and excitation  current commands
iqs* and ids* from one of the two positions
of a switch: the  transient position (1) or
the steady-state position  (2).  The fuzzy
controller  becomes  effective  at steady-
state condition; i.e., when the speed loop
error Acor approaches zero.
  A feed-forward pulsating torque com-
pensator has been  developed to prevent
speed  ripple  and mechanical  resonance
during  transient operation. As  the excita-
tion current is reduced in  adaptive steps
by the  fuzzy  controller, the rotor flux de-
creases exponentially. The decrease of
flux causes  loss of torque,  which nor-
mally is compensated for  slowly by the
speed  control loop.
  Efficiency optimization control is effec-
tive only at steady-state conditions. A dis-
advantage of this control mode is that the
transient response  becomes sluggish. For
any change  in load torque or speed com-
mand,  fast transient response capability
of the drive can be restored by establish-
ing  the  rated flux. Therefore,  for ASD
Type  2,  the system starts in efficiency
optimization and then  switches  to tran-
sient response optimization in the event
of a load disturbance or a  change in set
speed.  During non-steady-state  condi-
tions,  the system  establishes the rated
magnetizing current (Figure 4 switch  in
Position  1).
         230 V. 3<|>
           60 Hz
                                                                                               IM
 Figure 4. An indirect vector controlled induction motor drive incorporating the proposed efficiency
          optimization controller.

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  Results and Recommendations
    Figure  5 is a  captured screen from a
  real-time  demonstration of the  optimizing
  and speed controllers for  a Type 1  ASD.
  The motor load being measured and con-
  trolled simulates a pump or fan  running at
  90% of rated speed and 81% of  rated
  torque. At each step, a speed  correcting
         controller  compensates  for  changes  in
         speed with changes in input frequency. Ul-
         timately, the input power is reduced from
         about 81 to about 78% of rated input power.
           The speed controller has been shown to
         hold speed during efficiency optimization to
         within 0.5%. Figure 6 illustrates controller
                                         behavior over several pump-fan load con-
                                         ditions tested in the laboratory. Slip com-
                                         pensation was not active in these tests.
                    0.825
                    0.765
                        0.00
1.50
3.00     4.50

  Time (Mins)
6.00
7.50
 Figure 5. Efficiency optimization results for 90% speed and 81% torque.
                               40:16      50:25       60:36      70:49      80:64

                                              % Rated Speed : % Rated Torque


Figure 6. Percent change in motor speed from initial motor speed, without slip compensation.


                                                             6
                                                     90:81

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  Typical power savings due to slip com-
pensation for a 10 hp motor are shown in
Figure 7. A total of 1-2% of rated power is
saved.
  The  operation  of the pulsating torque
compensation scheme for the indirect vec-
tor control drive system is illustrated in Fig-
ure 8. An ASD initially operating in a steady-
state mode  has  its command  speed
changed from 450-900 rpm. At 3 seconds,
the system has  already reached  a new
steady-state mode with rated current  rees-
tablished. A new search for the optimum
efficiency point is initiated. The drive speed
response demonstrates  the adequacy of
the method for fast transient applications.
                               40:16     50:25     60:36     70:49    80:64
                                                        Speed : Torque
                                       90:81
       95.90
Figure 7. Power reduction in watts due to slip compensation (rated input power = 8477W).
                                                    OA
                                                    0 rpm
                                                              OA
                                                                                                      •OA
                             (a)
                                        (b)
Figure 8. Drive performance in time domain with sudden changes in command speed.
                        a) Top: current (3.33 A/div.); Bottom: speed (3.5 rpm/div.).
                        b) Top: ids* (3.33 A/div.); Bottom iqs* (3.33 A/div.).
                                        Time scale: 5 sec./div.

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  Figure 9  contains  efficiency  curves for
the Type 2 ASD, where the dotted curves
are results obtained by optimal control with
the fuzzy controller and  the solid curves
represent standard drive control. At  light
load torque, efficiency gains on the order of
15% may be obtained.
  For ASD Type 1, Figures  10 and 11, it is
seen that Motor A exhibits  less gain from
efficiency optimization  in the  50 to 60%
speed  range than at the highest and lowest
output powers.  The  test data also show
that, in this operating  range, voltage pertur-
bation  for optimization reverses its direc-
tion; i.e., at the higher speed/torque combi-
nations, voltage  perturbation results in volt-
age increases  until  Fj>n  is  minimized.  At
                  lower speed/torque combinations,  voltage
                  decreases to optimize. Motor B results are
                  more common  during  efficiency optimiza-
                  tion,  with almost no improvement at rated
                  conditions (100:100). Motor A behavior sug-
                  gests that the optimum slip of a motor does
                  not necessarily occur at rated  conditions.
                  The finding is significant because it implies
                  that,  for some motors,  input power can be
                  reduced  significantly  near rated  output
                  power operation.
                    Recommendations for continuing efforts
                  related to the efficiency  optimization con-
                  trollers include:
                    • Final  hardware  implementation of a
                      microprocessor integrating  all  control-
lers into ASD circuitry, and testing
of the hardware configuration.
Further investigation of the influ-
ence of motor design and fabrica-
tion on the operating  conditions
where  maximum efficiency gains
are found during application of the
new controllers.
Demonstration of the  hardware-
implemented controllers in an  in-
dustrial setting.
                               90
                               80-
s-
0
'o
e  eo-
LU
E
to  ._
>• 5
CO


   40-
                               30
                                                                             U>r = 0.75 pu
                                                                           Rated Flux

                                                                           Optimum Flux
                                        0.1      0.2     0.3     0.4     0.5     0.6     0.7     0.8
                                                       Load Torque (pu)
Figure 9. Experimental system efficiency curves.
     92

     90


   g88
   & 86
   0)
   o 84
   Si
     82

     80

     78
           40:16   50:25  60:36   70:49  80:64   90:81  100:100
                     % Rated Speed : % Rated Torque
                                       40:16   50:25  60:36   70:49   80:64  90:81  100:100
                                                  % Rated Speed : % Rated Torque
Figure 10. V/Hz and optimum efficiencies-Motor A.
                                Figure 11. V/Hz and optimum efficiencies-Motor B.

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   M.W.  Turner, V.E.  McCormick, and J.G.  Cleland are with  Research Triangle
     Institute, Research Triangle Park, NC 27709.
   Ronald J. Spiegel is the EPA Project Officer (see below).
   The complete report, entitled "Efficiency Optimization Control of AC Induction
     Motors: Initial Laboratory Results," (Order No. PB96-153  424; Cost: $21.50,
     subject to change) will be available only from:
           National Technical Information Service
           5285 Port Royal Road
           Springfield, VA 22161
           Telephone: 703-487-4650
   The EPA Project Officer can be contacted at:
           Air Pollution Prevention and Control Division
           National Risk Management Research Laboratory
           U. S. Environmental Protection Agency
           Research Triangle Park, NC 27711
United States
Environmental Protection Agency
National Risk Management Research Laboratory (G-72)
Cincinnati, OH 45268

Official Business
Penalty for Private Use $300
     BULK RATE
POSTAGE & FEES PAID
         EPA
   PERMIT NO. G-35
EPA/600/SR-96/008

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