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Evaluation Methodologies in the Development of Dynamically Reconfigurable Systems in the Automotive Industry

Journal Article
2020-01-1363
ISSN: 2641-9645, e-ISSN: 2641-9645
Published April 14, 2020 by SAE International in United States
Evaluation Methodologies in the Development of Dynamically Reconfigurable Systems in the Automotive Industry
Sector:
Citation: Oszwald, F., Bertelo, R., Gericota, M., and Becker, J., "Evaluation Methodologies in the Development of Dynamically Reconfigurable Systems in the Automotive Industry," SAE Int. J. Adv. & Curr. Prac. in Mobility 2(5):2925-2937, 2020, https://doi.org/10.4271/2020-01-1363.
Language: English

Abstract:

Classical decentralized architectures based on large networks of microprocessor-based Electronic Control Units (ECU), namely those used in self-driving cars and other highly-automated applications used in the automotive industry, are becoming more and more complex. These new, high computational power demand applications are constrained by limits on energy consumption, weight, and size of the embedded components. The adoption of new embedded centralized electrical/electronic (E/E) architectures based on dynamically reconfigurable hardware represents a new possibility to tackle these challenges. However, they also raise concerns and questions about their safety. Hence, an appropriate evaluation must be performed to guarantee that safety requirements resulting from an Automotive Safety Integrity Level (ASIL) according to the standard ISO 26262 are met.
In this paper, a methodology for the evaluation of dynamically reconfigurable systems based on centralized architectures is presented. The aim is to evaluate the reliability and probability of failure while exploring the design space without compromise the overall system performance.
The methodology is divided into three stages. In the first stage, the system is decomposed, and its sub-systems are isolated before applying a Fault Tree Analysis on the elements of each sub-system. The mathematical stochastic model of Markov Chain is used in the second stage to obtain the reliability function and the quantification of the Mean Time to Failure (MTTF) of the system. Finally, the overall system is evaluated in terms of performance, and according to time constraints such as reconfiguration latency in case of failure.
Applying this method, we quantify the MTTF in Failure in Time (FIT) format of an E/E architecture. Additionally, we evaluate each sub-system independently and obtain the respective ASIL decomposition of the overall system. The aim is to evaluate the migration of safety-related functionalities/redundancy from traditional architectures into reprogrammable devices.
With the application of this methodology, we can evaluate the reliability and performance of dynamically reconfigurable systems and define new E/E automotive architectures.