This paper demonstrates multi-objective optimization of an axial flux permanent magnet motor for scraper conveyors, indicating enhanced efficiency.
Aiming at the urgent need for miniaturization and high efficiency of the driving mechanism of scraper conveyors, this paper proposes an axial flux permanent magnet motor, which is different from the current asynchronous motors or radial flux permanent magnet motors. Aiming at the problems of many parameters and strong coupling in the multi-objective optimization process of the motor, a multi-objective optimization method based on a genetic algorithm is proposed. Through OptiSLang software and Maxwell joint simulation, multi-objective optimization analysis is carried out to achieve the goals of cogging torque and output torque fluctuation. Through parameter sensitivity analysis, strong correlation variables are selected to improve optimization efficiency. The response surface between the optimization objectives and variables is established, and the multi-objective optimization is carried out by a genetic algorithm. Finally, the correctness and tangibility of the algorithm and the results are verified by finite element simulation. It provides a new idea for miniaturization and high efficiency of the drive motor of the scraper conveyor.
No takes yet. Share an insight, caveat, or question.
Shi et al. (2025) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: