Auswirkungen der Reifendimension auf den Energieaufwand im Umfeld verschiedener Fahrzyklen und Fahrzeugkonzepte

The efficiency of a vehicle has a direct impact on its consumption as well as on its range and is essential for both the achievement of customer-specific and legal requirements. The reduction of driving resistors is therefore one of the greatest priorities within the automotive development process. Due to the considerable impact on aerodynamics, mass inertia and rolling resistance, the selection of the dimensions of the rims and tyres in the early development phase is an important basis for the subsequent achievement of the efficiency targets of the entire vehicle. In the context of changing mobility and new vehicle concepts, the current design limits are changing, which creates new design spaces in the dimensioning of the vehicle. Within the scope of this study the significance of the efficiency-relevant tyre parameters aerodynamics, mass inertia and rolling resistance within the individual cycle components of the WLTP are analysed in simulations. The variation of the vehicle parameters mass, aerodynamic end face and recuperation efficiency makes it possible to evaluate the individual tyre parameters with regard to different vehicle concepts. Using measured data, physical relationships and literature research, the efficiency-relevant parameters of the tyre are set in relation to the rim and tyre dimension and dimensional recommendations for exemplary scenarios are presented.     

Evaluating system architectures for driving range estimation and charge planning for electric vehicles

Due to sparse charging infrastructure and short driving ranges, drivers of battery electric vehicles (BEVs) can experience range anxiety, which is the fear of stranding with an empty battery. To help eliminate range anxiety and make BEVs more attractive for customers, accurate range estimation methods need to be developed. In recent years, many publications have suggested machine learning algorithms as a fitting method to achieve accurate range estimations. However, these algorithms use a large amount of data and have high computational requirements. A traditional placement of the software within a vehicle's electronic control unit could lead to high latencies and thus detrimental to user experience. But since modern vehicles are connected to a backend, where software modules can be implemented, high latencies can be prevented with intelligent distribution of the algorithm parts. On the other hand, communication between vehicle and backend can be slow or expensive. In this article, an intelligent deployment of a range estimation software based on ML is analyzed. We model hardware and software to enable performance evaluation in early stages of the development process. Based on simulations, different system architectures and module placements are then analyzed in terms of latency, network usage, energy usage, and cost. We show that a distributed system with cloud‐based module placement reduces the end‐to‐end latency significantly, when compared with a traditional vehicle‐based placement. Furthermore, we show that network usage is significantly reduced. This intelligent system enables the application of complex, but accurate range estimation with low latencies, resulting in an improved user experience, which enhances the practicality and acceptance of BEVs.     

Physical Model of Tire-Road Contact Under Wet Conditions

Four non-halogenated ionic liquids (ILs) with trihexyl(tetradecyl)phosphonium cation are tested as lubricant additives to polypropylene (PP) and lithium-complex (LiX) greases. In pin-on-disk tests at elevated temperatures, the addition of an IL with bis(oxalato)borate ([BOB]) anion reduces wear by up to 50% when compared to the neat LiX base grease; an IL with bis(mandelato)borate ([BMB]) anion reduces friction by up to 60% for both PP and LiX. Elemental analysis reveals that oxygen-rich tribofilms help to reduce wear in case of [BOB], while the friction reduction observed for [BMB] is likely caused by adsorption processes. We find that temperature has a pronounced effect on additive expression, yet additive concentration is of minor importance under continuous sliding conditions. In contrast, rolling-sliding experiments at 90 °C show that the traction performance of LiX grease is dependent on additive concentration, revealing a reduction in traction by up to 30 and 40% for [BMB]- and [BOB]-containing ILs at concentrations of 10 wt%. Finally, an IL with dicyanamide anion reduces friction and increases wear in pin-on-disk tests at room temperature, while an IL with bis-2,4,4-(trimethylpentyl)phosphinate anion increases wear, showing only limited potential as grease additives. Overall, this work demonstrates the ability of non-halogenated ILs to significantly extend grease performance limits.

     

Load mitigation and power tracking capability for wind turbines using linear matrix inequality‐based control design

This article deals with nonlinear model‐based control design for wind turbines. By systematically integrating several mechanical degrees of freedom in the control design model, the load mitigation potential from the proposed multivariable control framework is demonstrated. The application of the linear matrix inequality (LMI)‐based control design is discussed in detail. Apart from the commonly considered power production mode, an extended operating range to provide stabilization of the electrical grid through power tracking is considered. This control functionality allows for an evaluation of the resulting fatigue and ultimate loads for power tracking at different dynamic requirements. The results indicate that under the impact of a dedicated control scheme, this functionality is feasible with respect to the occurring loads and operational behavior of the wind turbine.