3D Electromagnetic Simulation Methodology for Detailed Characterization of Small Electric Motor for Motorcycle Applications

The electrification of powertrains leads to the development of increasingly accurate computational methodologies to predict electromagnetic behavior early in the design phase, reducing the need for experimental tests and expensive prototypes. In the motorcycle industry, where space constraints and performance drive the design of compact and efficient e-motors, conventional two-dimensional FE (Finite Element) simulations are often inaccurate in terms of performance, fluxes, and inductances, particularly for e-motors with high diameter/length ratios. A detailed review of existing literature revealed that no papers describe how to implement a 3D methodology for e-motor electromagnetic characterization in FEA software. This paper presents a novel 3D electromagnetic simulation methodology, developed using finite-element software combined with an in-house MATLABSimulink tool, to calculate inductances, fluxes, and performance of a three-phase Permanent Magnet Synchronous Motor (PMSM). These factors significantly impact field-weakening performance and MTPV (Maximum Torque per Voltage), leading to the underestimation of the λd and λq fluxes and a lower-than-expected power output results in the experimental validation, different e-motor efficiency, back-electromotive force constant and control strategy. The tool in the MATLABSimulink environment allows for real mapping of the electric motor through a series of point calculations; it also presents the possibility of coupling the motor to the inverter to use the real waveforms and calculate with high accuracy the losses of the electric motor itself. By incorporating full 3D effects, this methodology provides a more accurate estimation of key parameters. An experimental campaign has been organized to evaluate the effectiveness of this approach and validate the accuracy of the electric motor characterization. This paper's contribution improves predictive modelling techniques, enabling more efficient and optimized electric motor designs for next-generation two-wheeled electric vehicles while reducing development time and costs.