The present paper shows the capabilities of a distributed real-time co-simulation environment merging simulation models and testing facilities for developing and verifying electric vehicles. This environment has been developed in the framework of the XILforEV project and the presented case is focused on a ride control with a real suspension installed on a test bench in Spain, which uses real-time information from a complete vehicle model in Germany. Given the long distance between both sites, it has been necessary to develop a specific delay compensation algorithm. This algorithm is general enough to be used in other real-time co-simulation frameworks. In the present work, the system architecture including the communication compensation is described and successfully experimentally validated.
The UAV industry is developing rapidly and drones are increasingly used for monitoring industrial facilities. When designing such systems, operating companies have to find a system configuration of multiple drones that is near-optimal in terms of cost while achieving the required monitoring quality. Stochastic influences such as failures and maintenance have to be taken into account. Model-based systems engineering supplies tools and methods to solve such problems. This paper presents a method to model and evaluate such UAV systems with coloured Petri nets. It supports a modular view on typical setup elements and different types of UAVs and is based on UAV application standards. The model can be easily adapted to the most popular flight tasks and allows for estimating the monitoring frequency and determining the most appropriate grouping and configuration of UAVs, monitoring schemes, air time and maintenance periods. An important advantage is the ability to consider drone maintenance processes. Thus, the methodology will be useful in the conceptual design phase of UAVs, in monitoring planning, and in the selection of UAVs for specific monitoring tasks.
<div class="section abstract"><div class="htmlview paragraph">The presented study is dedicated to the technology supporting vehicle state estimation and motion control with a concept drone, which helps the vehicle in sensing the surroundings and driving conditions. This concept allows also extending the functionality of the sensors mounted on the vehicle by replacing or including additional parameter observation channels.</div><div class="htmlview paragraph">The paper discusses the feasibility of such a drone-vehicle interaction as well as demonstrates several design configurations. In this regard, the paper presents a general description of the proposed drone system that assists the vehicle and describes an experiment in measuring the profile of the road with a range sensor. The results obtained in the experiment are described in terms of the accuracy to be achieved using the drone and are compared with other studies, which use the methods of estimation from the sensors mounted on the vehicle.</div><div class="htmlview paragraph">The proposed measurement concept can be applied to a large number of vehicle systems such as adaptive cruise control, active or semi-active suspension, and wheel slip control. The road profile is captured in real-time by a drone, and the telemetry data is processed by the host computer.</div></div>
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