Demand Profile Study of Battery Electric Vehicle under Different Charging Options

Abstract-- An increased research on electric vehicles (EV) andplug-in hybrid electric vehicles (PHEV) deals with their flexibleuse in electric power grids. Several research projects on smartgrids and electric mobility are now looking into realistic modelsrepresenting the behavior of an EV during charging, includingnonlinearities. In this work, modeling, simulation and testing ofthe demand profile of a battery-EV are conducted. Realistic workconditions for a lithium-ion EV battery and battery charger areconsidered as the base for the modeling. Simulation results showthat EV charging generates different demand profiles into thegrid, depending on the applied charging option. Moreover, alinear region for the control of EV chargers is identified in therange of 20-90% state-of-charge (SOC). Experiments validate theproposed model.Index Terms - charging, demand profile, electric vehicles,modeling, validation7 halama

Modeling of a Hybrid-Electric System and Design of Control Laws for Hybrid-Electric Urban Air Mobility Power Plants

Advanced Air Mobility (AAM) is an emerging market and technology in the aerospace industry. These systems are being developed to overcome traffic congestion. The current designs make use of Distributed Electric Propulsion (DEP): either fully electric or hybrid electric. The hybrid engine system consists of two power sources: prime movers, such as turbine engines, and batteries. The hybrid systems offer higher range and endurance compared with the existing fully electric systems. Hybrid-electric power generation systems for AAM have different mission requirements when compared to systems used in automobiles. Therefore, there is a particular need to model hybrid-electric systems and the development of control logic specifically for AAM aircraft. This thesis focusses on the modeling and design of control logic for hybrid-electric power plants for Advanced Air Mobility (AAM) applications. The developed model can assist in designing and optimizing the system as well as supporting the system architecture. These models can also help the testing and integration of hardware and software of systems and sub-systems, also known as software-in-the-loop and hardware-in-the-loop simulations. A state-space representation of the hybrid-electric system is created and validated with experimental results to facilitate the use of modern controls methods. A control law for the hybrid-electric system was also developed to meet the AAM aircraft mission requirement of generating the required electrical power and maintaining the State of Charge (SOC) of the batteries

Robotic Wireless Sensor Networks

In this chapter, we present a literature survey of an emerging, cutting-edge, and multi-disciplinary field of research at the intersection of Robotics and Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system that aims to achieve certain sensing goals while meeting and maintaining certain communication performance requirements, through cooperative control, learning and adaptation. While both of the component areas, i.e., Robotics and WSN, are very well-known and well-explored, there exist a whole set of new opportunities and research directions at the intersection of these two fields which are relatively or even completely unexplored. One such example would be the use of a set of robotic routers to set up a temporary communication path between a sender and a receiver that uses the controlled mobility to the advantage of packet routing. We find that there exist only a limited number of articles to be directly categorized as RWSN related works whereas there exist a range of articles in the robotics and the WSN literature that are also relevant to this new field of research. To connect the dots, we first identify the core problems and research trends related to RWSN such as connectivity, localization, routing, and robust flow of information. Next, we classify the existing research on RWSN as well as the relevant state-of-the-arts from robotics and WSN community according to the problems and trends identified in the first step. Lastly, we analyze what is missing in the existing literature, and identify topics that require more research attention in the future

Towards Data-driven Simulation of End-to-end Network Performance Indicators

Novel vehicular communication methods are mostly analyzed simulatively or analytically as real world performance tests are highly time-consuming and cost-intense. Moreover, the high number of uncontrollable effects makes it practically impossible to reevaluate different approaches under the exact same conditions. However, as these methods massively simplify the effects of the radio environment and various cross-layer interdependencies, the results of end-to-end indicators (e.g., the resulting data rate) often differ significantly from real world measurements. In this paper, we present a data-driven approach that exploits a combination of multiple machine learning methods for modeling the end-to-end behavior of network performance indicators within vehicular networks. The proposed approach can be exploited for fast and close to reality evaluation and optimization of new methods in a controllable environment as it implicitly considers cross-layer dependencies between measurable features. Within an example case study for opportunistic vehicular data transfer, the proposed approach is validated against real world measurements and a classical system-level network simulation setup. Although the proposed method does only require a fraction of the computation time of the latter, it achieves a significantly better match with the real world evaluations