Electrification of non-road mobile machinery holds immense potential for reducing the high emissions and fuel consumption of such industrial machinery. Detailed real-time physics-based simulation models capable of comparing energy efficiencies of hybrid powertrains in realistic working conditions can aid the development of efficient mobile machinery. In this study, four system-level hybrid electric powertrain models have been developed and coupled with a detailed multibody dynamics-based tractor model in a co-simulation environment. The four models, differentiated by their topology and transmission design, are simulated in a virtual environment under the dynamic load conditions of a ploughing work cycle of the Deutsche Landwirtschafts-Gesellschaft powermix. The simulation results show that improvements of 9.7% and 9.2% in total energy consumption can be achieved by the two studied power-split configurations in the simulated work cycle compared to an automated manual transmission-based series powertrain. The double planetary gear-based power-split model achieved the highest energy recovery and lowest energy loss compared to the other models. The developed models are real-time capable, allowing a human operator to simulate customizable work cycles.

In electric vehicle (EV) traction, energy conversion by electric motors must be material and energy efficient to reduce environmental burden caused by the manufacture and operation of the systems and to help in efficient transition towards net zero future. The scarcity of key materials like rare earths and to some extent copper must be addressed in the design. Novel traction motors need a different approach compared to traditional industrial motor designs. Here, we focus on innovative design and optimization strategies to enhance material and energy efficiency and meet the escalating demand for sustainable transportation solutions. We are developing a prototype motor that achieves a continuous specific power of 7 kW/kg, significantly exceeding current automotive standards. This will be achieved by elevated operational speed of the traction motor, integrating advanced materials, and innovative cooling techniques such as direct liquid cooling (DLC) using hollow hairpin conductors, and insulating them with polyether-ether-ketone (PEEK) extrusion and expandable mainwall insulation material. The approach reduces reliance on rare earth permanent magnet (PM) materials by 60% compared to existing motors, aligning with global sustainability objectives. Through simulation, modeling, and practical case studies, the research demonstrates the feasibility of these innovations in real-world applications, highlighting potential advancements in EV propulsion systems. The article not only represents the insights into the latest developments in the design of electric motors for EV but also delineates the journey towards the creation of such a motor with considering accompanying electromagnetic and mechanical challenges.

Computer simulations are important tools for evaluating hybrid electric powertrain concepts. In heavy mobile machinery, the powertrain undergoes traction and often hydraulic loads. The dynamic loads on hydraulic actuators of heavy mobile machinery can be studied using detailed physics-based simulation models. The effect of coupling hydraulic actuators to various configurations of hybrid electric powertrains is studied using a co-simulation approach in this study. The case example of a tractor modeled using multibody dynamic approach combined with four powertrain configurations with different topology and hydraulic actuator coupling is investigated. A farm tractor was simulated in a virtual environment with deformable terrain in a soil digging and dumping work cycle. The coupling of hydraulics to the electric energy source in a series-parallel topology achieved fuel savings of 10.5% and total energy savings of 12.3%. The presented modeling method can be used to simulate various heavy mobile machinery to evaluate hybrid electric powertrains using work cycles created by human operators.