Design Space Exploration for Automotive E/E Architecture Component Platforms

Graf, Sebastián; Glaß, Michael; Teich, Jürgen; Lauer, Christoph

doi:10.1109/dsd.2014.43

Cited by 7 publications

(3 citation statements)

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“…In particular, we want to investigate to which extend robust component platforms are achievable and what the overhead, e. g., in terms of cost overheads or increased/decreased number of component manifestations, might be. By incorporating this aspect in the optimization of a component platform [3], we aim at finding such trade-offs between design objectives and robustness automatically.…”

Section: Related Workmentioning

confidence: 99%

“…As a remedy, the concept of component platforms [3,4] has been investigated where parts may be reused between different variants to an extend that delivers a sound trade-off between the concrete costs of individual variants and the overall development, management, and maintenance costs of the component platform. Major car companies like Volkswagen or Toyota have already developed mechanical component platforms that are widely used as a basis of new car models and series.…”

Section: Introductionmentioning

confidence: 99%

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Robust design of E/E architecture component platforms

Graf

Reinhart

Glab

et al. 2015

Proceedings of the 52nd Annual Design Automation Conference

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Already today, car manufacturers are designing E/E architectures using so-called component platforms. Such a platform comprises the superset of all components that are required to build all acquirable variants of a certain or even multiple car models. To find and optimize such component platforms, each candidate platform has to be evaluated by (a) determining a number of design objectives (monetary cost, etc.) of each car variant when derived from the candidate platform and then (b) approximating the platform's design objectives themselves, e. g., by a weighted sum that includes the expected sales of each variant. But typically, since this optimization has to take place in early design stages, important parameters like the number of expected sales numbers per car variant can only be projected and are, thus, uncertain. To investigate the susceptibility of the optimization to such uncertain parameters, this paper proposes a Monte-Carlo simulation-based method that enables to evaluate the uncertainty of a combined multi-variant objective wrt. parameter variations. By treating the minimization of uncertainty as an additional design objective, not only can the robustness of the derived component platforms be improved but also the confidence of the manufacturer. Moreover, we also propose to treat uncertainty not as a conventional design objective, but to use uncertain objectives: Here, not a single (e. g., mean) value but an interval given by observed upper and lower objective values is used. Experimental results show that the design objectives of an E/E architecture component platform are relatively robust wrt. parameter variations (here expected sales numbers of car variants). Moreover, it will be shown that the difference in expected overall costs between different non-dominated solutions is often much higher than the expected variation in cost as a result of parameter uncertainty

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Robust design of E/E architecture component platforms

Graf

Reinhart

Glab

et al. 2015

Proceedings of the 52nd Annual Design Automation Conference

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“…This SW-C activity configuration is called one manifestation of that ECU. The number of manifestations of one ECU should also be minimized during the optimization to increase the utilization of that ECU [19]. The schedule of tasks on ECUs with multiple manifestations can be designed by the method introduced in [38].…”

Section: ) Product Line and Variabilitymentioning

confidence: 99%

Architecture exploration for distributed embedded systems: a gap analysis in automotive domain

Zhang

Mohan

Törngren

et al. 2017

2017 12th IEEE International Symposium on Industrial Embedded Systems (SIES)

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A large body of work can be found in literature on Design Space Exploration (DSE) methods for distributed embedded system architecting (DESA). However, almost none of these methods is successfully adopted in automotive industry. To clarify the reasons, this paper 1) analyzes the current state of the art (SOTA) on DSE methods for DESA through a systematic literature study, focusing on the assumed architecting process and concerns; 2) investigates the state of practice (SOP) on DESA in the automotive industry through a literature study and interviews with experienced system architects from five different automotive manufacturers; and 3) analyzes the gap between SOTA and SOP, and thereby discusses potential improvements of DSE methods.

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