Topology Optimization and AI-based Design of Power Electronic and Electrical Devices

Topology Optimization and AI-based Design of Power Electronic and Electrical Devices: Principles and Methods provides an essential foundation in the emergent design methodology as it moves towards commercial development in such electrical devices as traction motors for electric motors, transformers, inductors, reactors and power electronics circuits. Opening with an introduction to electromagnetism and computational electromagnetics for optimal design, the work outlines principles and foundations in finite element methods and illustrates numerical techniques useful for finite element analysis. It summarizes the foundations of deterministic and stochastic optimization methods, including genetic algorithm, particle swarm optimization and simulated annealing, alongside representative algorithms. The work goes on to discuss parameter optimization and topology optimization of electrical devices alongside current implementations including magnetic shields, 2D and 3D models of electric motors, and wireless power transfer devices. The work concludes with a lengthy exposition of AI-based design methods, including surrogate models for optimization, deep neural networks, and automatic design methods using Monte-Carlo tree searches for electrical devices and circuits. Focuses on helping researchers and design engineers practically apply the emergent topology design optimization to power electronics and electrical device design, supported by step-by-step methods, demonstrator Python algorithms and pseudocodes Proposes unique formulations of AI-based design to electrical devices using Monte-Carlo tree search and other machine learning methods Richly accompanied by detailed numerical examples, and replete with computational support materials in algorithms and explanatory formulae Accompanied by pedagogical videos showing the evolutionary process of topology optimization, the distribution of genetic algorithms, and CMA-ES, among others