A Vehicle Simulator for an Efficient Electronic and Electrical Architecture Design
DOI: 10.1109/tits.2013.2286091
archive: archived pipeline: cataloged verified
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Summary
This paper addresses the increasing complexity of vehicle design driven by the proliferation of active safety functions and driver assistance systems. The authors identify a critical problem in the automotive development process: compatibility issues among electronic and electrical (E/E) components often emerge late, during Hardware-in-the-Loop (HIL) testing or physical prototyping, leading to costly delays and instability. To mitigate this, the paper proposes a vehicle simulator designed to support the early-stage design of functional and physical architectures. By simulating complete vehicle behavior, including drivetrain and controller subsystems, the tool allows engineers to validate functional allocations—such as sensor requirements, communication delays, and memory needs—before hardware implementation. The simulator is built upon a functional architecture that ensures scalability and independence between vehicle functions. It integrates two complementary platforms: MATLAB/Simulink for rapid prototyping and scenario definition, and SiVIC, a C-code-based platform enabling quasi-real-time simulation with realistic sensor and environment modeling. The vehicle dynamics model employs a solid mechanics approach with six degrees of freedom for the body and three for each wheel, incorporating nonlinearities such as tire-road contact forces (using Pacejka or Burckhardt models), aerodynamic resistance, and mechanical phenomena like Ackerman steering. The drivetrain models are calibrated using data from a Mini Cooper and include simplified but accurate representations of the combustion engine, automatic gearbox, limited-slip differential, braking system, and electric power steering. These models balance computational efficiency with sufficient accuracy to represent actuator dynamics and vehicle motion. The paper details the specific modeling strategies for key components. The engine model uses lookup tables for torque and fuel consumption based on RPM and throttle angle, while the gearbox utilizes deterministic finite-state machines to manage gear shifts across sporty, standard, and economical strategies. The braking system models hydraulic pressure propagation and disc friction, and the steering column accounts for driver torque, assistance torque, and self-aligning torque. Stability controllers, such as the Electronic Stability Controller (ESC), are integrated to override other requests during safety-critical situations. The simulator’s architecture allows for the assessment of vehicle performance under various functional and hardware configurations, specifically testing the impact of latency times and parallel function interactions. The significance of this work lies in its ability to reduce development complexity and integration risks by enabling early validation of E/E architectures. By providing a tool that bridges the gap between requirement specification and system design, the simulator helps identify potential instability issues, such as those caused by communication delays or conflicting control signals, before physical prototypes are built. This approach aligns with functional development standards like Autosar and offers a cost-effective method for optimizing vehicle safety and performance during the initial design phases.
Provenance
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-06-25 |
| archive | success | unpaywall | — | — | 2 | 2026-06-26 |
| extract | success | cached | — | — | 2 | 2026-06-26 |
| clean | success | clean | — | — | 1 | 2026-06-26 |
| chunk | success | chunk | — | — | 1 | 2026-06-26 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-26 |
| enrich | success | openalex | — | — | 1 | 2026-06-26 |
| promote | success | — | — | — | 1 | 2026-06-25 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 1 | 2026-06-26 |
| tag | success | vector_similarity | — | — | 6 | 2026-06-26 |
| verify | success | — | — | — | 1 | 2026-06-26 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.
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Information type
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- Methodological Resource: tool software, validation psychometrics
- Theoretical Contribution: computational model