Improving Efficiency of Rolling Mill Stand Electric Drives Through Load Alignment
The problem of reducing electric power consumption is critical to ferrous metallurgy as it is a very energy-intensive industry. Significant energy savings can be achieved by increasing the efficiency of high-power electric drives of rolling mills. Experiments with the 5000 plate mill showed that the...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
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| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/18/12/3175 |
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| Summary: | The problem of reducing electric power consumption is critical to ferrous metallurgy as it is a very energy-intensive industry. Significant energy savings can be achieved by increasing the efficiency of high-power electric drives of rolling mills. Experiments with the 5000 plate mill showed that the deterioration of energy efficiency can be caused by the misalignment of loads between the upper and lower roller main electric drive motors (upper main drive/UMD and lower main drive/LMD, respectively) caused by the misalignment of roller motor speeds. Experiments showed that when the speed misalignment reaches 5%, the motor torques differ by two times. Various UMD and LMD speeds can be set to bend the front end of the workpiece (form a “ski”). The installed load division controller (LDC) option fails to provide load alignment due to a low response rate and late startup. This article’s contribution consists of the development of a forced UMD and LMD speed and torque alignment method. To implement this method, a load-division controller with a switching structure has been developed. The authors also developed an efficiency and electric loss monitor and provided an experimental assessment of electric losses per one-pass and per sheet batch rolling cycle. The prospects of this research include the optimization of high-speed and high-load electric drive modes to reduce the energy costs of rolling and the development of an LDC based on fuzzy logic algorithms. |
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| ISSN: | 1996-1073 |