Uso de Hardware-In-The-Loop e reconhecimento de imagem para validação de centrais automotivas

This study presents the application of Hardware-in-the-Loop (HIL) techniques and image recognition to validate the Instrument Panel Cluster (IPC) in automotive control units, focusing on process optimization, cost reduction, and improved test reliability. HIL was integrated with tools such as dSPACE SCALEXIO, MATLAB Simulink, and Cognex In-Sight Series 7000 cameras, using communication protocols like CAN and TCP/IP to simulate and validate systems in real-time. The process involved: creation of simulation models, image training for automated analysis, and the development of test sequences in AutomationDesk. The methodology ensured a comprehensive analysis of the IPC's performance, verifying visual and operational functionalities with high precision. The results demonstrated that the proposed approach helps reducing validation time, detection of potential failures, and improves the efficiency of human and computational resources. This study contributes to the advance of validation practices in the automotive industry, highlighting the relevance of HIL tools and computer vision technologies.