Powertrain electrification continues to be a growing trend in vehicular applications. Electric powertrains have numerous advantages over traditional mechanical and hydraulic powertrains but there are still important challenges to overcome for long-term commercial success. This research presents a technological assessment of present and future developments of powertrain electrification in non-road mobile machinery (NRMM). The challenges and opportunities of NRMM electrification are described in detail. The trends and drivers related to technological development such as regulations, policies and market development are analyzed, and technology enablers are highlighted. Future scenarios are formulated based on the prevailing trends and drivers, development of key components, scientific literature and status of the non-road mobile machinery industry. Some recommendations are also given in relation to the development of hybrid and electric powertrains for NRMM. The key findings of this research indicate that the electrification of NRMM is slowly started and the progress is demonstrated by hybridization of some specific, successful mobile machines. In short-term, high component and technology development costs remain the main barrier for higher adoption of electric and hybrid powertrains. In the long-term scenario, many NRMM can operate autonomously and powertrain electrification has become mainstream technology.

Purpose: The purpose of this paper is to report on the developments in manufacturing soft magnetic materials using laser powder bed fusion (L-PBF). Design/methodology/approach: Ternary soft magnetic Fe-49Co-2V powder was produced by gas atomization and used in an L-PBF machine to produce samples for material characterization. The L-PBF process parameters were optimized for the material, using a design of experiments approach. The printed samples were exposed to different heat treatment cycles to improve the magnetic properties. The magnetic properties were measured with quasi-static direct current and alternating current measurements at different frequencies and magnetic flux densities. The mechanical properties were characterized with tensile tests. Electrical resistivity of the material was measured. Findings: The optimized L-PBF process parameters resulted in very low porosity. The magnetic properties improved greatly after the heat treatments because of changes in microstructure. Based on the quasi-static DC measurement results, one of the heat treatment cycles led to magnetic saturation, permeability and coercivity values comparable to a commercial Fe-Co-V alloy. The other heat treatments resulted in abnormal grain growth and poor magnetic performance. The AC measurement results showed that the magnetic losses were relatively high in the samples owing to formation of eddy currents. Research limitations/implications: The influence of L-PBF process parameters on the microstructure was not investigated; hence, understanding the relationship between process parameters, heat treatments and magnetic properties would require more research. Originality/value: The relationship between microstructure, chemical composition, heat treatments, resistivity and magnetic/mechanical properties of L-PBF processed Fe-Co-V alloy has not been reported previously.

An iron-loss model for laminated ferromagnetic cores of electrical machines is presented and applied to estimate the core losses of an induction machine with finite-element analysis. Skin effect in the cross section of the core lamination is modelled using a set of sinusoidal basis functions while locally considering both the hysteretic material properties and the excess field caused by domain wall motion. After spatial and time discretisation, a single non-linear equation system is obtained. An accurate vector Preisach model, the differential reluctivity tensor and the Newton–Raphson method guarantee excellent convergence of the iteration procedure. Results from the model correspond well to iron-loss data obtained by measurements.

We consider an analytical model of a permanent magnet synchronous generator (PMSG) and formulate a mixed-integer constrained multiobjective optimization problem with six objective functions. We demonstrate the usefulness of solving such a problem by applying an interactive multiobjective optimization method called NIMBUS. In the NIMBUS method, a decision is iteratively involved in the optimization process and directs the solution process in order to find the most preferred Pareto optimal solution for the problem. We also employ a commonly used noninteractive evolutionary multiobjective optimization method called NSGA-II to generate a set of solutions that approximate the Pareto set and demonstrate the advantages of using an interactive method. This study is the first one to consider an interactive approach for the design of a PMSG. Thus, we promote the further usage of interactive multiobjective optimization methods in the design. Further, we see that these methods could also be very useful in the teaching of electrical machines.

Torque density of radial, axial and transverse flux machine topologies is investigated. A 10-kW, 200-rpm motor is chosen as a test case. Radial and axial flux motors that fulfill the key specifications of the selected test case are designed employing in-house analytical dimensioning tools and MATLAB genetic multi-objective optimization. Rather simple numerical approach is taken to study the transverse flux motor. A 20-pole-pair radial flux motor is found to outperform its axial and transverse flux counterparts in terms of torque density.

After its recent improvements described here, open source finite element software Elmer is shown to be a highly efficient option for electrical machine modeling. The parallelization of computational burden is shown to be a necessity. The methods implemented enable applying fully parallel computation to electrical machine models, including rotation and electrical circuits. Computational experiments performed demonstrate that Elmer can effectively utilize several hundreds of computational cores in parallel, making it an attractive alternative when computational speed is of high importance.