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). ------- 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 slowon 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. ------- 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. ------- 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. ------- 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. ------- 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 ------- 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. ------- 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. ------- 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 ------- |