Future Automotive Embedded Systems Enabled by Efficient Model-Based Software Development

Schaefer, Juergen; Christlbauer, Herbert; Schreiber, Alexander; Reith, G.; Jonker, M; Potman, Jordy; Dannebaum, Udo; Eissfeldt, Tjark

doi:10.4271/2021-01-0129

“…The automotive industry uses the model-based design (MBD) paradigm extensively [91]. A data-flow description with control-flow additions helps to manage the complexity of a system by allowing the modelling of both the control strategy and the physical systems and environment it interacts with in the same development environment.…”

Section: Automotive Applications Domainmentioning

confidence: 99%

Digital Electronic System-on-Chip Design: Methodologies, Tools, Evolution, and Trends

Cirstea,

Benkrid,

Dinu

et al. 2024

Micromachines

1

0

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This paper reviews the evolution of methodologies and tools for modeling, simulation, and design of digital electronic system-on-chip (SoC) implementations, with a focus on industrial electronics applications. Key technological, economic, and geopolitical trends are presented at the outset, before reviewing SoC design methodologies and tools. The fundamentals of SoC design flows are laid out. The paper then exposes the crucial role of the intellectual property (IP) industry in the relentless improvements in performance, power, area, and cost (PPAC) attributes of SoCs. High abstraction levels in design capture and increasingly automated design tools (e.g., for verification and validation, synthesis, place, and route) continue to push the boundaries. Aerospace and automotive domains are included as brief case studies. This paper also presents current and future trends in SoC design and implementation including the rising, evolution, and usage of machine learning (ML) and artificial intelligence (AI) algorithms, techniques, and tools, which promise even greater PPAC optimizations.

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“…Especially step (5), the implementation and integration of controllers into a larger system, is considered a challenging task [30]. In principle, engineers follow a model-driven approach [31], [32], relying on a variety of tools and modeling languages (e.g., (MATLAB/Simulink, Modelica, SCADE), where the control model is transformed into hardware-and environment-specific models and eventually into source code. Still the generated code, as we learned from the Ferrari case, needs to be further optimized and customized before it can be integrated into a larger system.…”

Section: Background and Motivationmentioning

confidence: 99%

Towards Mapping Control Theory and Software Engineering Properties using Specification Patterns

Caldas,

Ghzouli,

Papadopoulos

et al. 2021

Preprint

0

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A traditional approach to realize self-adaptation in software engineering (SE) is by means of feedback loops. The goals of the system can be specified as formal properties that are verified against models of the system. On the other hand, control theory (CT) provides a well-established foundation for designing feedback loop systems and providing guarantees for essential properties, such as stability, settling time, and steady state error. Currently, it is an open question whether and how traditional SE approaches to self-adaptation consider properties from CT. Answering this question is challenging given the principle differences in representing properties in both fields. In this paper, we take a first step to answer this question. We follow a bottom up approach where we specify a control design (in Simulink) for a case inspired by Scuderia Ferrari (F1) and provide evidence for stability and safety. The design is then transferred into code (in C) that is further optimized. Next, we define properties that enable verifying whether the control properties still hold at code level. Then, we consolidate the solution by mapping the properties in both worlds using specification patterns as common language and we verify the correctness of this mapping. The mapping offers a reusable artifact to solve similar problems. Finally, we outline opportunities for future work, particularly to refine and extend the mapping and investigate how it can improve the engineering of self-adaptive systems for both SE and CT engineers.

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Towards Mapping Control Theory and Software Engineering Properties using Specification Patterns

Caldas

¹

,

Ghzouli

²

,

Papadopoulos

³

et al. 2021

2021 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C)

0

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A traditional approach to realize self-adaptation in software engineering (SE) is by means of feedback loops. The goals of the system can be specified as formal properties that are verified against models of the system. On the other hand, control theory (CT) provides a well-established foundation for designing feedback loop systems and providing guarantees for essential properties, such as stability, settling time, and steady state error. Currently, it is an open question whether and how traditional SE approaches to self-adaptation consider properties from CT. Answering this question is challenging given the principle differences in representing properties in both fields. In this paper, we take a first step to answer this question. We follow a bottom up approach where we specify a control design (in Simulink) for a case inspired by Scuderia Ferrari (F1) and provide evidence for stability and safety. The design is then transferred into code (in C) that is further optimized. Next, we define properties that enable verifying whether the control properties still hold at code level. Then, we consolidate the solution by mapping the properties in both worlds using specification patterns as common language and we verify the correctness of this mapping. The mapping offers a reusable artifact to solve similar problems. Finally, we outline opportunities for future work, particularly to refine and extend the mapping and investigate how it can improve the engineering of self-adaptive systems for both SE and CT engineers.

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Future Automotive Embedded Systems Enabled by Efficient Model-Based Software Development

Cited by 4 publications

References 4 publications

Digital Electronic System-on-Chip Design: Methodologies, Tools, Evolution, and Trends

Digital Electronic System-on-Chip Design: Methodologies, Tools, Evolution, and Trends

Towards Mapping Control Theory and Software Engineering Properties using Specification Patterns

Towards Mapping Control Theory and Software Engineering Properties using Specification Patterns

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