Leveraging its deep expertise, Alvier Mechatronics developed a proof-of-concept (PoC) design to showcase the unique benefits of Höganäs’ powder metal material in an EDU application. However, taking this PoC to the next level required addressing complex challenges in inverter and transmission design, as well as robust testing and validation.

To meet these demands, the project turned to Drive System Design (DSD), experts in global propulsion system engineering. DSD brought to the table their unmatched capabilities in integrating simulation-driven methodologies to optimise designs. Their solution? A digital twin approach, enabling the team to precisely evaluate and refine the EDU design virtually—significantly reducing the need for time-intensive physical prototyping.

To power these virtual iterations, Alvier Mechatronics utilised ePOP, the state-of-the-art simulation tool from ZeBeyond. ePOP allowed Alvier Mechatronics and DSD to efficiently run simulations across extensive datasets, enabling rapid exploration of multiple powertrain configurations. The development of the gears was made possible by Höganäs' extensive material expertise. The design and production insights were only achieved through collaboration with the metal powder manufacturer's robust network of partners.

This collaborative effort resulted in an EDU design that met Höganäs’ specifications and validated the material's transformative potential.

Delivering results

The final EDU design aims to demonstrate Höganäs’ hypothesis, delivering tangible benefits such as:

• Sustainability: By using materials sourced from recycled steel, and using powder metallurgy processes that minimise waste, the sustainability metrics for gear and stator components are vastly improved! The PM process also reduces energy consumption.
• Reduced weight and size: Through net-shape forming, reductions are made without compromising performance.
• Flexible gear geometry: As powder processes are not bound by the geometric constraints of hobbing or shaper cutter processes, the geometry of the gear root can be optimised for lower stress levels.

Beyond achieving the initial objectives, the project is yielding invaluable insights into the material's capabilities, paving the way for its application in next generation eDrives.

Conclusion: Collaboration fuels innovation

This successful partnership exemplifies the power of collaboration in advancing eMobilitysolutions. Höganäs, Alvier Mechatronics, DSD, and ZeBeyond each brought their unique strengths to the table—proving that by working together, industry leaders can confidently develop innovative technologies that redefine the future of electrified propulsion systems.

Fundamental Concepts and Simplified Models

To comprehend the significance of adding details to electromagnetic models, it is crucial to begin with a basic understanding of fundamental concepts. Electromagnetism, as described by Maxwell's equations, governs the behavior of electric and magnetic fields. Simplified models often serve as the starting point for analysis. These models provide a high-level overview but lack the intricacies required for precise predictions.

Incorporating Material Properties

One of the initial steps in enhancing electromagnetic models is the inclusion of material properties. Real-world materials exhibit varying electrical and magnetic characteristics. To increase fidelity, models must consider parameters such as, permeability, and conductivity. Incorporating these properties allows for a more realistic representation of how electromagnetic fields interact with materials. One aspect that significantly affects model fidelity is the consideration of electromagnetic losses.

Electromagnetic losses in materials occur due to a variety of physical mechanisms, and they can have a substantial impact on the behavior of electromagnetic fields. To increase the fidelity of electromagnetic models, it is imperative to account for these losses in materials.

Materials with magnetic properties, like ferromagnetic or ferrimagnetic substances, experience losses through mechanisms such as hysteresis and eddy currents. Accurate modeling of magnetic losses is crucial for understanding energy losses, as well as predicting the behavior of inductors, transformers, and magnetic shielding materials.

Geometric Complexity

Electromagnetic systems often involve intricate geometries that cannot be adequately represented by simplistic models. Adding geometric details, such as tooth tips, slot radiuses, and insulation material, becomes necessary for accurate simulations. These details ensure that models reflect the physical world with precision.

Meshing and Discretization

To analyze electromagnetic phenomena in complex geometries, numerical methods like the finite element method (FEM) or finite difference time domain (FDTD) are commonly employed. These methods require discretization of space into smaller elements or grids. Fine-tuning the mesh or grid resolution allows for a more detailed analysis, as it captures localized effects and boundary interactions accurately.

Time-Dependent Behavior

Many electromagnetic phenomena exhibit time-dependent behavior, which necessitates modeling changes over time. Including temporal details such as time-varying sources, transient responses, and dynamic material properties further enhances the fidelity of electromagnetic models. Time-domain simulations provide insights into how systems evolve in real-world scenarios.

Frequency-Dependent Effects

Electromagnetic systems often operate at various frequencies. Modeling frequency-dependent effects, such as dispersion and resonances, requires additional details. Frequency-domain analysis, such as the use of complex permittivity and permeability, is crucial for accurately predicting how electromagnetic fields interact with materials and structures across different frequencies.

Coupling and Multiphysics Interactions

In many practical applications, electromagnetic systems interact with other physical phenomena, such as heat transfer, fluid dynamics, or structural mechanics. Including these multiphysics interactions in models increases their fidelity by considering the complex coupling between different physical domains.

Validation and Experimental Data

The final step in enhancing fidelity involves validation against experimental data. Comparing model predictions with real-world measurements is essential to confirm the accuracy of the model and identify any discrepancies. This iterative process may lead to further refinement of details in the model to align predictions with experimental results.

Conclusion

In conclusion, the step-by-step addition of details to electromagnetic models is a fundamental approach to increasing their fidelity. Beginning with fundamental concepts and simplifications, models evolve to incorporate material properties, geometric complexity, meshing, time-dependent behavior, frequency-dependent effects, multiphysics interactions, and validation against experimental data. Each of these steps enhances the model's accuracy, allowing for more precise predictions and applications across various fields, from telecommunications and medical devices to aerospace and beyond. As technology continues to advance, the continual refinement of electromagnetic models through the addition of details will remain essential in our pursuit of understanding and harnessing electromagnetic phenomena.

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Ultimately, the choice between axial and radial flux machines involves a trade-off between various factors, and it highlights the importance of considering the specific needs and goals of the electric drivetrain in question. A good way to perform such an analysis is with a systems optimization toolbox, such as ePOP.

If you’d like to discuss the trade-offs between axial flux and radial flux further, please contact Gerald Römpp, and we’ll set up a meeting with our technical experts to discuss how your problem could be analyzed faster, and with higher quality.

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Your Profile

You are a (or a plurality of) Master Student(s) in Engineering, you have at least basic knowledge of electrical machines, thermodynamics, fluid mechanics, measurement systems, and manufacturing methods. It will help to have some practical skills as the intention is to build and test.

Communication in English or Swedish is a requirement. The thesis shall be written in English.

Interested?

Don’t hesitate to apply! We look forward to your application!

Contact Person

Kristoffer Nilsson, System Architect & Technical Lead, Alvier Mechatronics,

kristoffer.nilsson@alviermechatronics.com

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