Design and optimization of permanent-magnet synchronous motors for a cargo e-bike

Abstract

The widespread adoption of electric vehicles (EVs) is driven by consumer preferences, ad-vancements in battery technology, and environmental regulations. Within this shift, electric micro-mobility has emerged as a key sector, offering sustainable urban transportation solu- tions. This study addresses critical gaps in performance evaluation and motor design for micro-mobility applications, focusing on hybrid cargo bikes and e-bikes.The first part evaluates the energetic performance of the STEP2 Prototype, a P3 hybrid cargo e-bike, under experimental and simulated urban conditions. Experimental tests assess real-world performance on fixed slopes, while simulations incorporate variable slopes, dy- namic motor assistance, and adaptive gear ratios to optimize efficiency and reduce cyclist fa- tigue. Results highlight the benefits of regenerative braking and adaptive assistance strategies in balancing battery consumption and rider effort, demonstrating the importance of variable power management in hybrid micro-mobility systems. The second part focuses on the design and optimization of a 12-slot/10-pole flat mag- net motor for e-bikes, tailored to a custom driving cycle derived from real-world urban con- ditions. A multi-objective genetic algorithm, integrated with MATLAB and Ansys Motor- CAD, optimizes the motor while considering constraints such as demagnetization, torque ripple, mechanical stress, and weight. A multiphysics analysis validates the design, and a comparative study evaluates different inner-rotor magnet topologies—V-shape, spoke, and surface-mounted—to minimize losses, material costs, and enhance torque production. This systematic approach identifies the most efficient motor configuration for urban micro-mobility while ensuring broader applicability in permanent-magnet synchronous motor systems.Together, this research provides a comprehensive framework for optimizing both hy- brid electric systems and motor design in micro-mobility, bridging real-world performance assessment with advanced engineering solutions. The findings support the development of more efficient, adaptive, and sustainable urban transportation technologies, contributing to the rapid evolution of the electric micro-mobility sector.