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An Integrated Approach Enabling Cross-Domain Simulation of Model-Based E/E-Architectures
Technical Paper
2017-01-0006
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
The increasing complexity of electric/electronic architectures (EEA) in the automotive domain raised the necessity of model-based development processes for the design of such heterogeneous systems, which combine different engineering principles with different viewpoints. High-level simulation is a great means to evaluate the EEA in the concept phase of the design, since it reduces costly real-world experiments. However, model-based EEA design and analysis as well as its simulation are often separate processes in the development lifecycle. In this paper, we present a novel approach that extends state-of-the-art model-based systems engineering principles of EEA by a behavior specification reusing library components. The specification is seamlessly integrated in the development process of a single source EEA model. Therewith, the starting point is the abstract logical function architecture of the EEA. Based on this single source EEA model we synthesize a unified high-level simulation model, which is capable of linking the behavioral model with lower level implementation details of other domains, e.g. the network communication of the underlying hardware topology. This cross-layer simulation enables an early but holistic system’s behavior analysis of the dynamic changes which typically depend on the scenarios applied. Moreover, the integrated approach enables the potential to feedback the simulation results into suitable EEA metrics and benchmarks for further analysis and optimization as well as the seamless traceability of the behavioral specification to requirements and other abstraction layers. A driver assistance system use case demonstrates the proof-of-concept and the benefits of our methodology.
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Bucher, H., Reichmann, C., and Becker, J., "An Integrated Approach Enabling Cross-Domain Simulation of Model-Based E/E-Architectures," SAE Technical Paper 2017-01-0006, 2017, https://doi.org/10.4271/2017-01-0006.Data Sets - Support Documents
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