一种风电电磁制动器的高效能磁场优化方法
By establishing a hysteresis characteristic prediction model and a fast multipole expansion algorithm based on the magnetic charge equivalent source method, combined with the Preisach inverse model and Kriging surrogate model of the hysteresis operator, efficient calculation and accurate magnetic field distribution in the magnetic field optimization process of wind power electromagnetic brakes are achieved. This solves the problems of low calculation efficiency and difficulty in considering hysteresis nonlinear characteristics, and improves the dynamic response and control accuracy of the brake.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- CHINA UNIV OF PETROLEUM (EAST CHINA)
- Filing Date
- 2026-01-09
- Publication Date
- 2026-07-17
AI Technical Summary
The magnetic field optimization process of wind power electromagnetic brakes is computationally inefficient and it is difficult to accurately consider the nonlinear characteristics of hysteresis and the coupling effect of multiple physics fields, which leads to deviations between the magnetic field distribution and the theoretical design.
A three-dimensional geometric model is established and meshed. A set of magnetic field strength-magnetic flux density data pairs is established through hysteresis test experiments. A hysteresis characteristic prediction model is trained. The air gap magnetic field distribution is calculated using a fast multipole expansion algorithm based on the magnetic charge equivalent source method. The Preisach inverse model adaptive identification algorithm and Kriging surrogate model of the hysteresis operator are combined for optimization to achieve magnetic-thermal coupling iterative solution.
It improves the computational efficiency and accuracy of magnetic field optimization, can consider hysteresis nonlinearity and multi-physics coupling effects in real time, improves the uniformity and dynamic response characteristics of air gap magnetic field, and reduces computational complexity and data acquisition costs.
Smart Images
Figure CN121902608B_ABST