Automotive Networks Based Intra-Vehicular Communication Applications

Bajaj, Preeti; Khanapurkar, Milind · 2012 · Crossref

DOI: 10.5772/45792

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Summary

This paper addresses the evolution and implementation of intra-vehicular communication systems, which facilitate data exchange among Electronic Control Units (ECUs) within a vehicle. Motivated by the increasing complexity of modern automobiles—where high-end cars now contain approximately 100 ECUs exchanging up to 2500 signals—the authors aim to demonstrate how automotive networks replace unwieldy wiring harnesses to enhance safety, reliability, and comfort. The study focuses on four primary network controllers: Local Interconnect Network (LIN), Controller Area Network (CAN), FlexRay, and Media Oriented System Transport (MOST). The methodology involves designing, simulating, and prototyping specific intra-vehicular applications using these protocols. The authors utilized simulation tools such as Modelsim, LabVIEW, and MATLAB, alongside hardware implementation on Field-Programmable Gate Arrays (FPGAs) like Altera DE1 and Xilinx boards. The experimental design followed a structured process: selecting appropriate network controllers, designing interface prototypes, downloading designs to programmable platforms, interfacing with electromechanical systems for real-time data simulation, and validating results in real-time environments. Key findings include the successful implementation of several distinct applications. A three-node LIN network was implemented on an FPGA to sense steering wheel angles and control dependent parameters, such as adjusting front light angles for better illumination and displaying safe speed limits. A CAN-based prototype was developed for an automotive "black box" application, where an Analog-to-Digital Converter (ADC) simulated emergency sensor signals; the resulting data frames were stored in memory for post-accident analysis. FlexRay applications were simulated in LabVIEW to control vehicle doors, air conditioning, oil temperature, and external weather responses, such as activating wipers during rain or AC during heat. Additionally, a System for Detecting Sudden Change in Speed (SDSCS) was interfaced with an Adaptive Front Light System (AFS). This prototype simulated accident scenarios by detecting rapid speed changes and recorded real-time steering angles and headlight positions, alongside virtual parameters like airbag status and seatbelt usage. The significance of this work lies in demonstrating the practical viability of heterogeneous automotive networks for critical safety and comfort applications. By successfully prototyping these systems, the authors validate that LIN, CAN, and FlexRay can effectively manage complex intra-vehicular tasks, from basic sensor actuation to sophisticated accident data recording. The study provides a technical framework for integrating these networks to improve vehicle diagnostics, safety mechanisms, and driver assistance systems, contributing to the broader field of Intelligent Transportation Systems.

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• v2x connected vehicle