Multi‐objective optimization design of the large‐scale high‐intensity homogeneous magnetic field coil system based on non‐dominated sorting genetic algorithm (NSGA‐II) - Zhu, Boliang; Lu, Yiwei; Yang, Yong; Zhang, Ming; Jiang, Li; Wang, Shusheng (IET electric power applications, 2022)
With the development of modern tokamak devices, the magnetic interference problem has become increasingly serious. On considering the International Thermonuclear Experimental Reactor (ITER), for example, the stray magnetic field around the tokamak device will be over 200 mT. To ensure the reliable operation of the electrical and electronic equipment installed around the tokamak, the magnetic immunity test becomes a mandatory requirement. Generally, a set of coils is employed to realize the required test field. Since the coil power loss and conductor mass are proportional to the dimension and intensity of the test field, optimization design is of great significance. This paper presents the multi‐objective optimization design of a large‐scale high‐intensity homogeneous magnetic field coil system. The analytical model of the multi‐coil system is proposed, and the constrained multi‐objective optimization model is established based on the non‐dominated sorting genetic algorithm. Taking the ITER test coil as an example, the optimization design is performed and the Pareto‐front is figured out. The designed four‐coil system enables the magnetic field immunity tests for equipment within 1 m side‐length at a highest test level of 275 mT with a magnetic field inhomogeneity of 1.05. The validity of the proposed model is verified by the finite element analysis and experimental tests.