Advanced Magnet Modelling in Ansys Maxwell: From Static Fields to Magnetostriction

Vidyabharati Ippili
4:00 MINS
August 8, 2025

Permanent magnets lie at the heart of modern electromechanical systems—from electric vehicles and wind turbines to MRI machines and high-speed actuators. The accuracy of electromagnetic simulation, particularly Magnet modelling, is key to predicting performance, minimizing losses, and ensuring long-term reliability. Boost accuracy in electromagnetic design with Ansys Maxwell magnet modeling, from static fields to demagnetization and magnetostriction.

Ansys Maxwell, a flagship low-frequency electromagnetic solver, offers a comprehensive platform for modelling magnets in both isolated and system-level contexts. This blog explores these techniques with a focus on:

Defining Magnet Material Behaviour

At the foundation of Maxwell’s capabilities lies its strength in simulating static magnetic fields. This allows engineers to evaluate how permanent magnets behave under steady-state conditions — from flux distributions and field strengths to force interactions in static assemblies. The tool supports both linear and nonlinear BH characteristics, enabling designers to account for magnetic saturation and material-specific responses with high fidelity. But static analysis is just the beginning.

Modern magnetic systems rarely operate in a truly static regime. Motors switch, actuators move, and field conditions fluctuate continuously. Maxwell’s transient solver captures these dynamic behaviours by solving Maxwell’s equations in the time domain. This becomes essential when simulating the start-up of a motor, analysing back-EMF generation, calculating eddy current losses in magnets, or evaluating time-dependent torque profiles. For devices involving motion, Maxwell allows full electromechanical coupling, simulating both linear and rotational movements with real-time force extraction and position-dependent field updates.

Fig. Typical BH Curve showing Magnetic Hysteresis Loop

Magnet modelling starts with material definition. While linear permanent magnet (LPM) models are useful for early-stage concepts, real-world systems demand nonlinear BH curves to capture effects like saturation. These curves, sourced from manufacturers or measurement data, provide a realistic representation of magnets such as NdFeB, SmCo, or ferrite. In cases where the magnet may undergo stress or faults, recoil line modelling helps simulate irreversible changes in magnet performance.

Demagnetization prediction

One of the most critical yet often overlooked aspects of magnet modelling is Demagnetization. Demagnetization is a key failure mode, especially in permanent magnet machines exposed to fault conditions like short circuits or overloads. Ansys Maxwell allows demagnetization studies through transient or magnetostatic solvers by applying extreme operating scenarios. This helps visualize critical areas where the magnet operating point approaches or drops below the knee of the BH curve, supporting informed design decisions on slot geometry, magnet grade, and thermal insulation.

Fig. BH Curve definition interface in Ansys Maxwell

Ansys Maxwell supports temperature dependent BH curves and allows users to track local operating points on the recoil curve, identify potential zones of irreversible demagnetization and evaluate magnet geometry and grade selection under worst-case scenarios.

Magnetostriction and Inverse Magnetostriction effects

Magnetostriction—deformation due to magnetic domain alignment—can lead to noise, vibration, or stress in magnetic systems. This is especially relevant for applications like transformers and high-speed motors. Maxwell enables modelling of magnetostriction effects by coupling electromagnetic simulations with structural solvers like Ansys Mechanical. The inverse effect, where mechanical stress influences magnetic properties, is also supported and is valuable in the design of sensors, actuators, and energy harvesters.

Fig. Inverse Magnetostriction setup using Multi-curve models in Ansys Maxwell

Fig. Magnetostriction setup using Multi-curve models in Ansys Maxwell

What truly sets Maxwell apart is its ability to bridge electromagnetics with mechanical and thermal domains. Magnetostrictive effects — where materials physically deform in response to magnetic fields — can be extracted from electromagnetic simulations and passed into Ansys Mechanical. This enables users to study structural deformation, stress, and even vibration caused by magnetic excitation. When further coupled with CFD tools like Ansys Fluent or Icepak, one can model how thermal gradients influence magnet behavior, including reductions in remanent flux density and susceptibility to demagnetization.

Temperature dependent Demagnetization

Permanent magnets, widely used in electric machines, actuators, and sensors, are highly sensitive to temperature variations. Their magnetic properties—such as remanence (Br) and intrinsic coercivity (Hci)—deteriorate with increasing temperature, which can lead to performance degradation or irreversible demagnetization if not properly accounted for during the design phase.

Demagnetization due to temperature can be classified into three categories:

Reversible losses – Temporary reduction in magnetic strength, recovered once the magnet cools down.
Irreversible but recoverable losses – Partial demagnetization that requires remagnetization to restore original properties.
Irreversible and unrecoverable losses – Occur when the magnet exceeds its Curie temperature, leading to permanent material degradation.

Fig. Temperature dependent BH curves for Ferrite Y30

Conclusion

Magnet modelling is no longer about static Br values. Ansys Maxwell allows you to simulate magnets the way they behave in reality—nonlinear, temperature-dependent, and mechanically coupled.

Whether you’re building high-speed motors, compact actuators, or efficient magnetic circuits, accurate magnet modelling is your foundation for success.

Want to explore these techniques in your own application? CADFEM India can help you simulate it right the first time.