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E Architecture
  • Hadi Askaripoor ,
  • Thilo Mueller ,
  • Alois Knoll
Hadi Askaripoor
Technical University of Munich

Corresponding Author:[email protected]

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Thilo Mueller
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Alois Knoll
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Over the last few years, the electrical and/or electronic (E/E) architecture of vehicles has significantly developed. The new generation of road vehicles demands considerable computational power due to many safety-critical applications and advanced driver assistance systems (ADAS) functionalities.
A centralized architecture with the adoption of a high-performance computing unit establishes a proper way in empowering vehicles to process the demanding applications.
In addition, high-bandwidth protocols are required due to the significant number of sensors and actuators. Moreover, deterministic and redundancy protocols are necessary to integrate safety and real-time critical applications called as mixed-criticality systems. However, configuring and integrating essential applications into a vehicle’s E/E architecture while meeting safety requirements, guaranteeing reliable communication, and considering optimization objectives are time-consuming, complex, and error-prone tasks.
This paper presents a novel model-based framework, called E/E Designer, to facilitate the synthesis of a car’s E/E architecture supporting automotive embedded systems modeling. This framework includes an automatic mapping process of software components to hardware elements that satisfies safety requirements, such as application thread scheduling. It creates network message routing and communication task scheduling for the car’s topology, meeting safety demands such as redundancy. The framework also optimizes the system model using multi-objective optimization, and utilizes a single-step approach to solve mixed-integer programming (MIP) constraints in order to reduce the solving time and consider the relations among various constraints. In the final step, we use an experimental setup to investigate the framework’s performance through design-time and run-time evaluations. The results of our design-time experiments indicate that our formulations can scale to systems of reasonable size.
2023Published in IEEE Transactions on Intelligent Vehicles on pages 1-18. 10.1109/TIV.2023.3324617