ADIOSS Automatic Diagnostic Of System Simulations

TL;DR

ADIOSS is a diagnostic tool for system simulations in automotive engineering that detects faulty modules efficiently, using minimal simulations and established techniques like Dynamic Mode Decomposition and autoencoders.

Contribution

It introduces a novel method for fault detection in system-level simulations that requires few simulations and integrates seamlessly into existing workflows.

Findings

Effective fault detection with limited simulations

Integration capability with current engineering processes

Utilizes validated techniques like DMD and autoencoders

Abstract

Automotive engineering makes extensive use of numerical simulation throughout the design process. The development of numerical models, their validation against experimental tests, and their updating during vehicle and engine projects constitute a core engineering activity. However, this activity must continuously evolve to reduce costs and lead times. In this context, we propose a method for detecting faulty modules within a system-level simulation workflow, represented as a graph of 0D models, following model updates. The proposed method requires a very limited number of system simulations and can therefore be easily integrated into existing engineering processes. It is designed as a toolbox based on well established and widely validated techniques, including Dynamic Mode Decomposition commonly used for 3D model reduction, linear programming, and autoencoders.