Three-dimensional printing is a promising technology that offers increased freedom to create topologically optimised electrical machine designs with a much smaller layer thickness achievable with the current, laminated steel-sheet-based technology. These composite materials have promising magnetic behaviour, which can be competitive with the current magnetic materials. Accurately calculating the iron losses is challenging due to magnetic steels’ highly nonlinear hysteretic behaviour. Many numerical methodologies have been developed and applied in FEM-based simulations from the first introduced Steinmetz formulae. However, these old curve-fitting-based iron loss models are still actively used in modern finite-element solvers due to their simplicity and high computational demand for more-accurate mathematical methods, such as Preisach- or Jiles–Atherton-model-based calculations. In the case of 3D-printed electrical machines, where the printed material can have a strongly anisotropic behaviour and it is hard to define a standardised measurement, the applicability of the curve-fitting-based iron loss methodologies is limited. The following paper proposes an overview of the current problems and solutions for iron loss calculation and measurement methodologies and discusses their applicability in designing and optimising 3D-printed electrical machines.

Today, numerous advanced options exist for analyzing and measuring magnetic hysteresis loops and core loss across a broad spectrum of applications. Most of these systems are compact and ready to use, fulfilling the measurement and data processing requirements for laminated iron cores according to the standards. However, modeling newly developed materials with complex structures or the high-frequency behavior of iron cores, and the computation of dynamic hysteresis properties’ temperature dependence, are still challenging problems in the field. Moreover, these standardized measurement tools are relatively expensive, and most of them represent a black box that impedes research and further development. This paper presents the development of a cheap and accessible measurement system that is explicitly designed for recording the hysteresis properties of 3D-printed iron cores. The paper presents a comprehensive overview of the design process, components, circuitry, and simulations integral to this project. The paper presents a completed circuit simulation conducted using LTspice and validation of the prototype’s measurement performance. The measurements obtained with the proposed system show good agreement with those of the reference setup, demonstrating its accuracy and practical applicability.

Li-ion batteries, known for high energy and power density, are widely used in electromobility and stationary applications. In these applications a Battery Management System (BMS) ensures safety and longevity by performing functions like cell balancing and protecting against overcharge and over-discharge. Advanced BMSs estimate the battery’s State of Charge (SOC), crucial for determining remaining operating time and safe range. This study compares three Kalman Filter (KF)-based SOC estimation techniques: the general Sigma Point KF (SPKF), the joint SPKF, and the dual SPKF, for state and parameter estimation of a Samsung 18650INR13L Li-ion battery.