AI-Assisted Axial Flux Motor Design and Optimization with MotorXP-AFM, MATLAB and AI Coding Agents

What You Will Learn:

In this webinar, you will learn how MotorXP-AFM combines fast quasi-3D finite-element analysis, multi-objective optimization, MATLAB automation, and AI-assisted script development. A practical axial flux machine example will demonstrate the workflow from simulation and design-space exploration to detailed DC and AC winding-loss analysis.

During the webinar, we will cover:

• Introduction to MotorXP-AFM and its axial flux motor design and simulation workflow
• Quasi-3D FEA methodology and why it is well suited for large-scale axial flux motor optimization
• Multi-objective optimization in MotorXP and MATLAB: surrogate models, variables, objectives, constraints, evaluation functions, penalty strategies, and parallel processing
• A generalized optimization scenario based on normalized design variables for an axial flux machine
• Using an AI coding agent to create and modify MATLAB optimization scenarios, run simulations, process results, and refine optimization strategies
• Lumped and Full winding models and the analysis of DC and AC winding losses using Magnetostatic and Dynamic FEA, including sinusoidal-current and PWM operation

🚀 This webinar is designed for electric machine designers, electromagnetic simulation engineers, R&D professionals, researchers, and advanced engineering students interested in axial flux motors, FEA, MATLAB automation, and design optimization. Previous experience with MotorXP-AFM is not required, but a basic understanding of permanent-magnet machines is recommended.

💬 You will be able to raise all your questions about MotorXP-AFM, axial flux motor simulation, optimization, and winding-loss analysis during a Q&A session at the end!