Automatic integration of SystemC in the FMI standard for Software-defined Vehicle design

• URL: http://arxiv.org/abs/2508.19665v1
• Date: Wed, 27 Aug 2025 08:24:56 GMT
• Title: Automatic integration of SystemC in the FMI standard for Software-defined Vehicle design
• Abstract summary: This paper presents an approach for automatically wrapping SystemC models by using the Functional Mock-up Interface (FMI) standard.<n>We validate the proposed methodology on real-world case studies, demonstrating its effectiveness with complex designs.
• Score: 2.747736676233256
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The recent advancements of the automotive sector demand robust co-simulation methodologies that enable early validation and seamless integration across hardware and software domains. However, the lack of standardized interfaces and the dominance of proprietary simulation platforms pose significant challenges to collaboration, scalability, and IP protection. To address these limitations, this paper presents an approach for automatically wrapping SystemC models by using the Functional Mock-up Interface (FMI) standard. This method combines the modeling accuracy and fast time-to-market of SystemC with the interoperability and encapsulation benefits of FMI, enabling secure and portable integration of embedded components into co-simulation workflows. We validate the proposed methodology on real-world case studies, demonstrating its effectiveness with complex designs.

Related papers

• Distributed Motion Planning with Safety Guarantees for Self-Reconfiguring Robotic Boats [76.98547580312116]
  This paper proposes a hybrid framework that combines distributed Model Predictive Control (MPC) with Control Barrier Functions (CBFs)<n>To ensure safety in real time, distributed CBF-based filters are applied to enforce inter-agent avoidance.
  arXiv  Detail & Related papers  (2026-07-22T16:37:05Z)
• VFEAgent: A Multimodal Agent Framework for End-to-End Automated Finite Element Analysis [34.66954835079288]
  VFEAgent is an end-to-end multi-agent system designed to automate FEA modeling and simulation directly from input images and problem descriptions.<n>VFEAgent achieves a high success rate in generating complete and physically valid simulations.
  arXiv  Detail & Related papers  (2026-05-27T18:34:04Z)
• Integration of an Agent Model into an Open Simulation Architecture for Scenario-Based Testing of Automated Vehicles [1.0499611180329804]
  We present a standardized and modular simulation integration architecture that enables the tool-independent integration of traffic agent models.<n>The architecture builds upon the Open Simulation Interface (OSI) as a structured message format and the Functional Mock-up Interface (FMI) for dynamic model exchange.<n>As part of the evaluation, we show that the model yields consistent behavior in all simulation platforms.
  arXiv  Detail & Related papers  (2026-05-13T13:47:51Z)
• Integrating SystemC TLM into FMI 3.0 Co-Simulations with an Open-Source Approach [34.22252229309027]
  This paper presents a fully open-source methodology for integrating SystemC TLM models into Functional Mock-up Interface (FMI)-based co-simulation.<n>By encapsulating SystemC TLM components as FMI 3.0 Co Functional Mock-up Units (FMUs), the proposed approach facilitates seamless, standardized integration across heterogeneous simulation environments.
  arXiv  Detail & Related papers  (2025-08-27T19:02:53Z)
• SimMLM: A Simple Framework for Multi-modal Learning with Missing Modality [52.948791050405525]
  We propose SimMLM, a simple yet powerful framework for multimodal learning with missing modalities.<n>SimMLM consists of a generic Dynamic Mixture of Modality Experts (DMoME) architecture, featuring a dynamic, learnable gating mechanism.<n>Key innovation of SimMLM is the proposed More vs. Fewer (MoFe) ranking loss, which ensures that task accuracy improves or remains stable as more modalities are made available.
  arXiv  Detail & Related papers  (2025-07-25T13:39:34Z)
• Towards Mixed-Criticality Software Architectures for Centralized HPC Platforms in Software-Defined Vehicles: A Systematic Literature Review [1.94470674081983]
  We set up a systematic review protocol grounded in established guidelines.<n>Third, we extract key functional domains, constraints, and enabling technologies that drive changes in automotive SWAs.<n>We propose an exemplary SWA for a microprocessor-based system-on-chip.
  arXiv  Detail & Related papers  (2025-06-06T07:40:30Z)
• ASIL-Decomposition Based Resource Allocation Optimization for Automotive E/E Architectures [0.4143603294943439]
  We present an approach to automatically map software components to available hardware resources.<n>Compared to existing frameworks, our method provides a wider range of safety analyses in compliance with the ISO 26262 standard.<n>We formulate a multi-objective optimization problem to minimize both the development cost and the maximum execution times of critical function chains.
  arXiv  Detail & Related papers  (2025-05-10T15:48:29Z)
• An LLM-enabled Multi-Agent Autonomous Mechatronics Design Framework [49.633199780510864]
  This work proposes a multi-agent autonomous mechatronics design framework, integrating expertise across mechanical design, optimization, electronics, and software engineering.<n> operating primarily through a language-driven workflow, the framework incorporates structured human feedback to ensure robust performance under real-world constraints.<n>A fully functional autonomous vessel was developed with optimized propulsion, cost-effective electronics, and advanced control.
  arXiv  Detail & Related papers  (2025-04-20T16:57:45Z)
• APIKS: A Modular ROS2 Framework for Rapid Prototyping and Validation of Automated Driving Systems [0.0]
  APIKS is a modular framework based on ROS2 for testing and validation of autonomous vehicle software.<n>It offers a simplified, standards-based architecture designed specifically for small-scale proofs of concept.
  arXiv  Detail & Related papers  (2025-02-27T20:29:31Z)
• Transforming the Hybrid Cloud for Emerging AI Workloads [82.21522417363666]
  This white paper envisions transforming hybrid cloud systems to meet the growing complexity of AI workloads.<n>The proposed framework addresses critical challenges in energy efficiency, performance, and cost-effectiveness.<n>This joint initiative aims to establish hybrid clouds as secure, efficient, and sustainable platforms.
  arXiv  Detail & Related papers  (2024-11-20T11:57:43Z)
• Digital Twin-Assisted Federated Learning with Blockchain in Multi-tier Computing Systems [67.14406100332671]
  In Industry 4.0 systems, resource-constrained edge devices engage in frequent data interactions. This paper proposes a digital twin (DT) and federated digital twin (FL) scheme. The efficacy of our proposed cooperative interference-based FL process has been verified through numerical analysis.
  arXiv  Detail & Related papers  (2024-11-04T17:48:02Z)
• Spatio-Temporal Analysis of Concurrent Networks [1.2475573869999146]
  Many large-scale systems are networks of cyber-physical systems in which humans and autonomous software agents cooperate. To make the cooperation safe for the humans involved, the systems have to follow protocols with rigid real-time and real-space properties. This paper focuses on modellingtemporal-temporal properties and their model-checking and simulation using different analysis tools.
  arXiv  Detail & Related papers  (2024-10-18T01:40:24Z)
• Correct-by-Construction Control for Stochastic and Uncertain Dynamical Models via Formal Abstractions [44.99833362998488]
  We develop an abstraction framework that can be used to solve this problem under various modeling assumptions. We use state-of-the-art verification techniques to compute an optimal policy on the iMDP with guarantees for satisfying the given specification. We then show that, by construction, we can refine this policy into a feedback controller for which these guarantees carry over to the dynamical model.
  arXiv  Detail & Related papers  (2023-11-16T11:03:54Z)
• CSM-H-R: A Context Modeling Framework in Supporting Reasoning Automation for Interoperable Intelligent Systems and Privacy Protection [0.07499722271664144]
  We propose a novel framework for automation of High Level Context (HLC) reasoning across intelligent systems at scale. The design of the framework supports the sharing and inter context among intelligent systems and the components for handling CSMs and the management of hierarchy, relationship, and transition. The implementation of the framework experiments on the HLC reasoning into vector and matrix computing and presents the potential to reach next level of automation.
  arXiv  Detail & Related papers  (2023-08-21T22:21:15Z)
• Recursively Feasible Probabilistic Safe Online Learning with Control Barrier Functions [60.26921219698514]
  We introduce a model-uncertainty-aware reformulation of CBF-based safety-critical controllers. We then present the pointwise feasibility conditions of the resulting safety controller. We use these conditions to devise an event-triggered online data collection strategy.
  arXiv  Detail & Related papers  (2022-08-23T05:02:09Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.