Many cities have announced ambitious plans to introduce zero-emission electric bus systems. The transformation process to electric bus systems opens up a vast design space as different charging strategies, charging technologies and battery types are available. Therefore, a profound assessment strategy is necessary to find a “most suitable system solution” under given strategic and operational requirements.In this study, we present a new methodology for conceptual design of urban electric bus systems. First, the available e-bus technologies are analysed with a special focus on charging systems, battery technology and aging. Relational functional analysis is used to derive a suitable simulation model. Based on the operational requirements, an energetic simulation of the e-bus is carried out, and the required battery capacity is obtained. Subsequently, the design space is reduced by applying a qualitative cost- technology compatibility matrix taking cost and battery aging into account. The applicability of the model is shown for an exemplary realistic operational scenario to identify three most expedient concepts, which are finally validated with an in-depth analysis.

Light electric vehicles (LEV) are seen as an effective solution for reducing the carbon emissions in the transportation sector thanks to their light weight and low energy requirement. Integrated photovoltaic (PV) panels on LEVs have great potential because a higher portion of the energy demands can be covered by PV panels compared to heavier vehicles. Integrated PV panels on LEVs are constrained by the surface shape and available area, which results in panels facing different angles. In this work, we assess the effectiveness of such integrated PV panels based on simulations with meteorological data and measurements from a real prototype on an electric scooter. It is shown that the measured PV power correlates well with the simulated data. A number of design options such as the number of PV panels and the angle of the panels are evaluated through simulations and we compare seasonal and regional differences. Based on the assessment, we make design suggestions for cost-effective and energy-efficient integrated PV panels on LEVs. Results indicate that with the right design and favorable circumstances, the integrated PV panels can generate more energy over a day than is consumed by the LEV in a day.

Creating an appropriate energy consumption prediction model is becoming an important topic for drone-related research in the literature. However, a general consensus on the energy consumption model is yet to be reached at present. As a result, there are many variations that attempt to create models that range in complexity with a focus on different aspects. In this paper, we benchmark the five most popular energy consumption models for drones derived from their physical behaviours and point to the difficulties in matching with a realistic energy dataset collected from a delivery drone in flight under different testing conditions. Moreover, we propose a novel data-driven energy model using the Long Short-Term Memory (LSTM) based deep learning architecture and the accuracy is compared based on the dataset. Our experimental results have shown that the LSTM based approach can easily outperform other mathematical models for the dataset under study. Finally, sensitivity analysis has been carried out in order to interpret the model.

Electric road systems (ERSs) are a promising solution for electrifying heavy-duty freight transport by providing traction and charging power from the power lines installed along the road. Development of ERSs has been accelerated in the last decade, and several pilot projects have been successfully implemented, proving the high level of maturity that the technology has achieved. One crucial step that could be initiated before a rollout is the standardization and certification of ERS infrastructure and system components. For instance, pantographs for overhead ERSs face unique challenges, in that the power transfer should be safe and reliable in the presence of dynamic longitudinal and lateral movements of the vehicle. To tackle this problem, we outline the requirements for overhead ERSs and ERS pantograph testing. Among the key requirements are the rising and lowering times, response to lateral maneuvers, such as lane changes, and high electrical current during stillstand. We introduce our developed test stands capable of testing various aspects of an ERS pantograph. The lateral test stand was developed to test basic functionalities and simulate lateral movements. A second test stand was implemented, to test high currents and the subsequent temperature development. Furthermore, a digital test stand used for planning, design, and modeling is introduced.

Thermal efficient resource mapping and scheduling techniques are particularly important for mobile processors because of limited opportunities for external cooling. In mobile processors such as the ones using ARM’s big.LITTLE architectures, the cores of either the big or the LITTLE processor cannot be individually voltage/frequency scaled. However, we show that by forcing all the application threads to a single core, and not having any workload on the other cores of a processor, there is still considerable thermal benefit. This is counter intuitive since all the cores run at the same frequency. We show real measurements and discuss what impact this has on thermal-aware scheduling for such multicore processors.