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Uncover the cover of an electrified house, factory or mine, and you will find a group of squirrel cage motors running all day. Without these, industrialized countries would not be so industrialized.

This type of three-phase induction motor is rugged and reliable, and is usually the first choice in the industry. They do not produce sparks and are very suitable for hazardous environments such as oil refineries, mines and grain elevators for grinding, pumping and blowing operations.

At home, refrigerators, washing machines, tumble dryers and swimming pool pumps are powered by single-phase squirrel cage motors. These motors are particularly suitable for high-speed applications above 3000 rpm. Even better, the squirrel cage motor is self-starting and does not require much maintenance, even if the rated power is hundreds of horsepower.

However, squirrel cage motors can cause damaging electricity bills to large companies. In South Africa, the National Broadcasting Corporation often advertises at night to encourage people to turn off household appliances and swimming pool pumps.

In short, there is a huge demand for high-performance, value-for-money main motors. However, grid managers also require that the interference caused by these motors is limited.

Dr. Mbika Muteba from the University of Johannesburg trained artificial intelligence to optimize the design of the squirrel cage motor. The research was published in the "Energy" magazine. AI significantly improves the power factor of the motor, ensuring that the optimized design will cause almost no interference to the grid to which it is connected.

In this study, Muteba modeled and designed the rotor and auxiliary capacitor coil for a 5.5kW (7.37 metric horsepower) squirrel cage motor. Then he built the rotor and tested it in the laboratory. The actual performance of the motor is very close to the predicted performance.

The motor in the first test has no auxiliary coils on the stator and has not been optimized by AI. The second one has an auxiliary coil to improve the power factor, and it has not been optimized by AI. The third motor has an auxiliary coil on the stator, which is also optimized by AI algorithm. The genetic algorithm has optimized it to obtain the highest performance (torque per ampere) under various loads. Muteba verified the results of the genetic algorithm with finite element analysis.

The AI-optimized 5.5kW motor has an excellent power factor in laboratory settings, ranging from 0.93 measured at 0% load to 0.99 to 120% load at 60% load. The full load efficiency of the AI ​​optimized motor is 85.87%, which is 1-2% different from the unoptimized motor. Compared with the unoptimized motor, its efficiency under 30% load has also been greatly improved.

Most importantly, even with excellent power factor, the optimized motor can provide more torque while consuming less current. The torque per ampere of the AI ​​optimized design is double digits higher than that of the motor without AI optimization.

Compared with the unoptimized version, the optimized motor torque per ampere is 22% higher at 20% load, 16% higher at 60% load, and 13% higher at 120% load.

Why the squirrel cage motor will make the grid unstable

"The power factor of squirrel cage motors is usually very poor. Especially when they start or run under light loads," Muteba said. "But the power company hopes that all the loads that you connect to their power grid, whether it is the motor of the pool pump or the mine crushing machine, have a good power factor."

The three-phase grid provides two kinds of power. The first is active power, which rotates the motor and does work. Electricity companies charge customers in units of kilowatts or megawatts. The grid also provides reactive power. The squirrel cage motor consumes reactive power on the grid to maintain the magnetic field on the rotor. Without that magnetic field, the squirrel cage motor cannot operate. Among all types of motors, squirrel cage motors require the most reactive power.

Transformers that reduce high-voltage power to household or industrial voltage also consume reactive power on the grid. "Loads with poor power factor consume more reactive power. When hundreds of such loads are connected to the grid, the owner of the grid must spend money to upgrade the grid to provide more reactive power," he said .

If the grid is overwhelmed by loads with poor power factor, all loads on the grid, even those with good power factor, cannot obtain enough reactive power to operate, and the grid may become unstable. This can cause extensive damage to irrigation systems in mines, factories, and farms.

For loads with poor power factor, the power company will severely punish users. Therefore, a national grid may be connected to tens or hundreds of thousands of squirrel cage motors as a reliable main force. But the low power factor of the motor will make the grid unpredictable and even unstable.

Muteba said that AI optimization of the rotor and auxiliary capacitor coils can improve power factor and performance, and there is still a reliable and efficient squirrel motor to cope with challenging applications.

The AI-optimized motor has an air gap between the rotor and the stator, which is larger than the unoptimized motor. Under high load, high temperature and high speed, the optimized motor should have better mechanical performance than the unoptimized motor.

"With these results, we see that it is possible to run a squirrel-cage induction motor without spending millions of dollars to buy a reactive power compensator in order to avoid penalties by the utility company. There is also no need to use a system that reduces efficiency or torque per ampere. Auxiliary coil," he added.

"The AI-optimized rotor and auxiliary capacitor coils have excellent power factor across the entire load range, and are more efficient and perform better."

He said that for microgrids or private grids, building an excellent power factor in each squirrel cage motor also makes the grid easier to manage.

Muteba said that using AI to optimize the rotor and auxiliary capacitor coil design can save time compared to entrenched design practices. The genetic algorithm spent 27 minutes in 8 executions and 60 generations of chromosome processing to optimize the rotor and auxiliary capacitor coil design.

"Design engineers are faced with the challenge of choosing the optimal value of the air gap length and auxiliary capacitor coil. In most cases, they use design software that performs sensitivity and parameter analysis. These processes are usually very long and have limited search capabilities," said Mu Teba.

"Artificial intelligence such as optimal search algorithms can find the optimal value of the air gap length and the auxiliary capacitor coil by searching a large solution space within a few minutes. The population-based technology used in this study, a genetic Algorithm is a good choice to find the best value you need." Further exploration to power the sea to space More information: Mbika Muteba, based on genetic algorithm to optimize the air gap length and capacitor auxiliary winding in a three-phase induction motor , Energy (2021). DOI: 10.3390/en14154407 Citation provided by the University of Johannesburg: How AI can break the power factor of the main industrial motor (2021, October 19), retrieved on November 13, 2021, from https://techxplore.com/news/ 2021-10-ai-power-factor-industrial-workhorse.html This document is protected by copyright. Except for any fair transaction for private learning or research purposes, no part may be copied without written permission. The content is for reference only.

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