Advanced eMotor Design Conference 2025 | Detroit

We are in the midst of a remarkable flourishing in electric motor design, as electrification spreads rapidly across mobility and transport – from scooters, cars, trucks, ships, and aircraft. At the heart of this revolution are electric propulsion systems, which offer several advantages over their distant combustion-engine cousins: higher specific torque and power density, smoother and quieter operation, lower maintenance, and dramatically improved efficiency and reliability.

Electric machines sit at the critical interface of power and motion. As prime movers, they enable propulsion systems that are not only more environmentally responsible but also more cost-effective over their lifecycle. While short-term fluctuations in EV adoption may make headlines, the long-term trajectory of electrified mobility is clear and it is inevitable.

The business case for battery-electric propulsion is improving year over year—not just for cars, but across virtually all modes of transport. The transition away from combustion for most use cases is no longer a question of if, but when? And from a motor design perspective, the most exciting opportunities lie ahead.

This keynote will explore advanced motor technologies can come to life enabled by new design tools and methods. With them we can now bring to life new machine topologies, with new design features and details, made of new materials and guided by new controls to create cleaner, less costly, and more capable mobility solutions across land, air, and sea.

Innovation speed is critical to gaining a competitive edge in any emerging field. During this discussion, will explore the keys for an eMotor designer to efficiently use detailed 3D models to compute critical metrics. This enables rapid iteration through new technology and detailed innovative design ideas without requiring physical prototype iteration thereby greatly speeding up the innovation loop.

JMAG is being developed with a focus on data-driven design (DDD).
DDD is only possible with massive, reliable datasets, making the accuracy and speed of simulations more critical than ever before.

It is said that the introduction of machine learning-based surrogate models can significantly enhance the power of DDD. However, these surrogate models require extensive training using simulation results, which makes the speed of generating FEA results increasingly important—even for 2D analyses.

We have been continuously improving JMAG’s performance to meet the growing demands of DDD.

Additionally, the question of how surrogate models should be used in DDD remains an important topic of investigation in our JMAG development efforts.

The latest advancements will be presented in the upcoming presentation.

Several factors and considerations affect the design of electric machines for traction applications. In the case of axial flux machines, this exercise is even more challenging given the need for 3D FEA simulations and that torque/power scaling is not as straightforward as industry-standard radial flux topologies. Data-driven design processes coupled with detailed analyses & representative models can effectively reduce the engineering time needed to arrive at optimal designs for electric machines. In this presentation, a case study for the accelerated multi-criteria design optimization of axial flux machines with 3D FEA simulations will be showcased using the Python/MATLAB scripting capabilities of JMAG-Designer.

The Electric Drive Module (EDM), typically comprising an electric motor, inverter, and reducer, plays a critical role in determining the performance, driving range, and cost of hybrid and electric vehicles (HEVs/EVs). While original equipment manufacturers (OEMs) and motor suppliers adopt varying EDM strategies, several global trends are emerging that shape EDM development. This presentation will explore these trends and define the key performance indicators (KPIs) used to evaluate EDM effectiveness. Furthermore, it will highlight the core technical enablers and design methodologies necessary to meet these KPIs and ensure competitive, high-efficiency EDM solutions in the evolving EV market.