研究目的
To develop a novel and reliable direct drive system for high-power grinding mills using synchronous optimal pulsewidth modulation to ensure low harmonic current distortion and reduced switching losses at a very low switching frequency, taking into account the anisotropic magnetic properties of a separately excited synchronous motor.
研究成果
The study demonstrates that synchronous optimal PWM can significantly reduce harmonic current distortion and switching losses in large salient-pole synchronous machines used in high-power grinding mills. The method allows for operation at a very low switching frequency, increasing the efficiency and reliability of the drive system.
研究不足
The study is focused on the specific application of high-power grinding mills in the cement and mining industries. The experimental results are from a downscaled laboratory setup and a 23-MW drive system in the field, which may not cover all possible operational scenarios.
1:Experimental Design and Method Selection:
The methodology involves the use of synchronous optimal pulsewidth modulation (PWM) for controlling large salient-pole synchronous machines. The optimization of the pulse patterns considers the anisotropic magnetic properties of the motor.
2:Sample Selection and Data Sources:
The study focuses on a 23-MW semiautonomous grinding mill installed in a Zambian copper mine.
3:List of Experimental Equipment and Materials:
The equipment includes a voltage source inverter, synchronous motors with a high number of pole pairs, and a three-level topology using pairs of parallel-connected 6.5-kV 600-A insulated-gate bipolar transistors (IGBTs).
4:5-kV 600-A insulated-gate bipolar transistors (IGBTs).
Experimental Procedures and Operational Workflow:
4. Experimental Procedures and Operational Workflow: The procedure involves the optimization of PWM pulse sequences for minimum harmonic distortion of the armature current, considering the internal impedance of the machine.
5:Data Analysis Methods:
The harmonic currents are computed using state equations and inductance operators to simplify the optimization algorithm.
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