e existing electromobility (EM) is still in its edgling stage and multiple challenges have to be overcome to make Electric Vehicles (EVs) as convenient as combustion engine vehicles. Users and Electric Vehicle Fleet Operators (EFOs) want their EVs to be charged and ready for use at all times. is straightforward goal, however, is counteracted from various sides: e range of the EV depends on the status and depletion of the EV ba ery which is in uenced by EV use and charging characteristics. Also, most convenient charging from the user's point of view, might unfortunately lead to problems in the power grid. As in the case of a power peak in the evening when EV users return from work and simultaneously plug in their EVs for charging. Last but not least, the mass of EV ba eries are an untapped potential to store electricity from intermi ent renewable energy sources. In this paper, we propose a novel approach to tackle this multilayered problem from di erent perspectives. Using on-board EV data and grid prediction models, we build up an information model as a foundation for a back end service containing EFO and Charging Station Provider (CSP) logic as well as a central Advanced Drivers Assistant System (ADAS). ese components connect to both battery management and user interfaces suggesting various routing and driving behaviour alternatives customized and incentivized for the current user pro le optimizing above mentioned goals. CCS CONCEPTS •Applied computing →Transportation; •Hardware →Smart grid; Energy distribution; •Social and professional topics →User characteristics; •So ware and its engineering →So ware architectures;

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Prolonging the lifetime of batteries in Electric Vehicles (EVs) becomes a more and more important issue for private users and fleet operators. In addition to the environmental point of view, a better battery health results in less cost, higher battery capacities and higher performance. To achieve this, the EV drivers or the fleet operators need to get proper information, which kind of actions will increase or decrease the batteries health. To this point, various tips and recommendations exist distributed over literature. Unfortunately, those kind of recommendations are hard to follow in the day-today routine. This paper suggests so called dynamic recommendations for battery health that are able to advise the user in specific situations with respect to battery use. Recommendations from literature are broken down into a list, which can be automatically computed. Recommendations will then be dynamically created in the current context of the EV and displayed to the user just in time. CCS CONCEPTS • Human-centered computing → HCI theory, concepts and models; Activity centered design; • Applied computing → Physics; • Information systems → Data analytics;

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In this paper an automated, softwarebased and easy to customize test tool for Hardware in the Loop (HIL) measurements is proposed. This system is originally designed for the test of a thermal power station control system. Due to its modular approach it may also be customized for a wide range of applications. The developed tool is independent of the Operating System (OS) or the used hardware platform. Especially when using embedded systems as host platform limited system resources are available. One demand is, therefore, the development of a lightweight tool. By implementing the tool in Python, which by itself provides various hardware abstraction modules, a suitable and efficient programming language is selected. To enable an easy adoption of this tool for further tests or even future projects, a modular software architecture is proposed. Therefore, the test functionality is divided into its basic core functionalities, which are then implemented in dedicated software components. Decoupled from each other and linked via a central communication system, continued development and improvement of these components is possible. For each test, that shall be performed, a dedicated test script that describes the used interfaces, instruments, as well as the test definitions has to be interpreted and executed at runtime. This approach allows easy modifications of the test script without the need for restarting the entire test tool. By implementing an exemplary test, the functionality of the proposed test tool is illustrated. For this purpose a test measurement, which closely resembles the intended application field in thermal power station control systems is presented.

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