Additive manufacturing of polymer-bonded magnets is a recently developed technique, for single-unit production, and for structures that have been impossible to manufacture previously. Also, new possibilities to create a specific stray field around the magnet are triggered. The current work presents a method to 3D print polymer-bonded magnets with a variable magnetic compound fraction distribution. This means the saturation magnetization can be adjusted during the printing process to obtain a required external field of the manufactured magnets. A low-cost, end-user 3D printer with a mixing extruder is used to mix permanent magnetic filaments with pure polyamide (PA12) filaments. The magnetic filaments are compounded, extruded, and characterized for the printing process. To deduce the quality of the manufactured magnets with a variable magnetic compound fraction, an inverse stray field framework is developed. The effectiveness of the printing process and the simulation method is shown. It can also be used to manufacture magnets that produce a predefined stray field in a given region. This opens new possibilities for magnetic sensor applications. This setup and simulation framework allows the design and manufacturing of polymer-bonded permanent magnets, which are impossible to create with conventional methods.

An efficient algorithm for the reconstruction of the magnetization state within magnetic components is presented. The occurring inverse magnetostatic problem is solved by means of an adjoint approach, based on the Fredkin-Koehler method for the solution of the forward problem. Due to the use of hybrid FEM-BEM coupling combined with matrix compression techniques the resulting algorithm is well suited for large-scale problems. Furthermore the reconstruction of the magnetization state within a permanent magnet as well as an optimal design application are demonstrated.

We present a finite-difference method for the topology optimization of permanent magnets that is based on the FFT accelerated computation of the stray-field. The presented method employs the density approach for topology optimization and uses an adjoint method for the gradient computation. Comparsion to various state-of-the-art finite-element implementations shows a superior performance and accuracy. Moreover, the presented method is very flexible and easy to implement due to various preexisting FFT stray-field implementations that can be used.

A method to optimize the topology of hard as well as soft magnetic structures is implemented using the density approach for topology optimization. The stray field computation is performed by a hybrid finite element–boundary element method. Utilizing the adjoint approach the gradients necessary to perform the optimization can be calculated very efficiently. We derive the gradients using a “first optimize then discretize” scheme. Within this scheme, the stray field operator is self-adjoint allowing to solve the adjoint equation by the same means as the stray field calculation. The capabilities of the method are showcased by optimizing the topology of hard as well as soft magnetic thin film structures and the results are verified by comparison with an analytical solution.