A cost model for the estimation of production costs of permanent magnet synchronous machines (PMSM) is presented, which allows to alter design choices such as wire technology, winding layout, cooling system, materials and more. With the goal to make results reproducible by others, the methods are explained in detail and used data and assumptions are given. The developed model helps to understand the interaction between the design of PMSM, manufacturing methods and the resulting costs. With it, different PMSM technologies and materials can be evaluated regarding its influence on the production costs, which is a perquisite to find the best compromise between performance and costs. Production volume is shown to be the most decisive factor for the resulting production costs. Between minimum and maximum assumed volumes, an average cost per unit reduction of 67% could be observed. Furthermore, the results imply that the winding production is responsible for the greatest part of the overall costs, followed by the rotor assembly (including rare earth magnets). When using the model to compare different wire types, it can be stated that up to a production volume of roughly 150,000 units/year, hairpin wires are more expensive to produce. Above this volume, hairpin windings will get cheaper than round wire windings due to its higher grade of automation of the production process. Through the conducted investigations and the presented results, it is demonstrated that the cost model can serve to evaluate technologies with regards to costs in the early development stage. This way a more holistic assessment of technologies for PMSM is possible, helping to find the ideal compromises between costs and performance and to increase the attractiveness of sustainable mobility.

A highly integrated electric drivetrain module with 157 kW peak power is presented, which incorporates novel technologies in the field of electric machines, power electronics and transmissions: 1. High-speed electric machine with six phases and injection mould polymer-bonded magnets; 2. High-ratio dual-speed transmission with double planetary gear set (Ravigneaux gear set); 3. Gallium nitride (GaN) power electronics with winding reconfiguration feature.The combination of these components in one single housing makes the drive module flexible to integrate and to combine with conventional or alternative propulsion technologies, thus allowing various hybrid and electric drivetrain topologies. All technologies are selected in accordance with mass production potential and can therefore have a high impact on the automotive market in the future. Currently, the drive module is under development; the first models will be assembled in winter 2019. The integration into a demonstrator vehicle in 2020 will prove the potential of many new technologies and the suitability for the automotive market.

The imperative for electrification of road transport, driven by global climate targets, underscores the need for innovative powertrain systems in heavy-duty vehicles. When developing new electric drive modules, individual operational requirements need to be considered instead of generalized usage profiles, as heavy-duty vehicles experience significantly differing loads depending on their field of operation. Real driving data, representing the demands of different application scenarios, offers great potential for digital replication of driving conditions at different stages of simulation and physical validation. Application- and vehicle-specific longitudinal requirements during operation are particularly relevant for the dimensioning of powertrain components. Road gradient and mass estimation assist in the description of these operating conditions, allowing for detailed modeling of the real load conditions. An incorporation of real driving data instead of solely relying on standardized cycles has the potential of tailoring components to the target lead users and applications. While some operating conditions can be recorded by vehicle manufacturers, these are usually not accessible by third parties. In this paper, the authors present an innovative methodology of estimating vehicle parameters for the generation of representative driving profiles for implementation into a consecutive powertrain design process. The approach combines the measurement of real driving data with state estimation. The authors show that the presented methodology enables the generation of driving profiles with less than 25% deviation from the original data set.

Autonomous shuttles can address the lack of reliability and service quality of public transport, but people are still skeptical about fully automated driving. This research aims to identify implications for future HMI design by investigating relationships between quality of experience, amount of information and willingness to use autonomous shuttles. An online survey with N = 175 participants indicated that a positive experience increases the propensity to trust in autonomous systems, and preference to use autonomous shuttles over conventional buses. Consequently, HMI should utilize user feedback to create positive experiences, for instance by explaining the behavior of automated driving systems. Additionally, passengers with a higher affinity for technology expressed interest in a greater amount of technical information. To enhance positive experiences here, the HMI and information presentation may be personalized and adapted to each individual user. Encouraging the use of public transportation can help to achieve goals of sustainable mobility.

Recently, there has been a growing interest in understanding how respiratory particles spread within passenger cars, especially in light of ongoing challenges posed by infectious diseases. This study experimentally investigates dispersion patterns of respiratory airborne particles (<1 µm) within these confined spaces. The main objective is to introduce a manikin-based method for studying particle dispersion and assessing in-cabin air quality. To achieve this, a respiratory manikin as a particle source has been developed and tested under various use-cases, including variations in source emission (breathing vs. speaking), the HVAC ventilation mode (fresh and recirculation), and the blower level of the HVAC system (low and high). The findings reveal that for an infection source on the first row of the vehicle when cabin airflow originates from the front panel, the seat directly behind the particle source is associated with the highest particle exposure, while the seat adjacent to the source offers the lowest exposure. Among the tested configurations, the recirculation mode with an active HEPA filter and high blower level shows the lowest particle concentration at recipients’ breath levels during both breathing and speaking. These findings can be used to enhance the design of passenger cars to reduce the transmission of potentially pathogen-laden particles.