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E-mobility is a game changer for the automotive domain. It promises significant reduction in terms of complexity and in terms of local emissions. With falling prices and recent technological advances, the second generation of electric vehicles (EVs) that is now in production makes electromobility an affordable and viable option for more and more transport mission (people, freight). Still, major challenges for large scale deployment remain. They include higher maturity with respect to performance (e.g., range, interaction with the grid), development efficiency (e.g., time-to-market), or production costs. Additionally, an important market transformation currently occurs with the co-development of automated driving functions, connectivity, mobility-as-a-service. New opportunities arise to customize road transportation systems toward application-driven, user-centric smart mobility solutions.

Automotive embedded systems have become very complex, are strongly integrated, and the safety-criticality and real-time constraints of these systems raise new challenges. The OSEK/VDX standard provides an open-ended architecture for distributed real-time capable units in vehicles. This is supported by the OSEK Implementation Language (OIL), a language aiming at specifying the configuration of these real-time operating systems. The challenge, however, is to ensure consistency of the concept constraints and configurations along the entire product development. The contribution of this paper is to bridge the existing gap between model-driven systems engineering and software engineering for automotive real-time operating systems (RTOS). For this purpose a bidirectional tool bridge has been established based on OSEK OIL exchange format files.

Automotive electronics are complex distributed embedded systems. The tight interconnection of the different functionalities (e.g. ABS, ESP) makes the network resource the backbone of the system. Time-triggered architectures and time-triggered communication systems such as FlexRay have been introduced in this context to support the development and integration of safety-relevant systems. An important enhancement to this approach is online monitoring and transparent diagnosis to ensure better assessment of the system status (faster fault detection) during operation. This is required for preventive maintenance in order to improve system availability. We propose a non-intrusive two steps method for the analysis of the communication architecture. In the first step, the system behavior is monitored at different abstraction levels by a dedicated tester node. The traces are analyzed online and the current system behavior is compared to the specification (e.g.

Efficient integration of mechanics and microelectronics components is nowadays a must within the automotive industry in order to minimize integration risks and support optimization of the entire system. We propose in this work a cross domain co-simulation platform for the efficient analysis of mechatronic systems. The interfacing of two state-of-the-art simulation platforms provides a direct link between the two domains at an early development stage, thus enabling the validation and optimization of the system already during modeling phase. The proposed cross-domain co-simulation is used within our TEODACS project for the analysis of the FlexRay technology. We illustrate using a drive-by-wire use case how the different architecture choices may influence the system.

One main challenge during the validation of automotive communication architectures is to consider the assembled system and more especially the interactions between the different components. We propose in this work a test and validation infrastructure based on tightly coupled co-simulation and prototype platforms. The co-simulation framework, on one hand, enables the efficient simulation of the entire network and the accurate analysis of the communication at different abstraction layers. On the other hand, the prototype framework is required for the model calibration and for the system validation on a realistic environment. We discuss further how the interconnection of these two platforms supports the analysis of both single components and entire communication networks. Experimental results illustrate our approach.