A Simulation-Based Digital Twin for Model-Driven Health Monitoring and Predictive Maintenance of an Automotive Braking System

Abstract

This paper describes a model-driven approach to support heat monitoring and predictive maintenance of an automotive braking system. This approach includes the creation of a simulation-based digital twin, or numerical model, that combines different modeling formalisms into an integrated model of the braking system that can be used for monitoring, diagnostics, and prognostics. The paper provides an overview of the basic models including Modelica models, reduced order models for various key components of the system model, and controls and sensor models. The Modelica models are implemented in the ANSYS Simplorer simulation to leverage existing modeling work and connections with other ANSYS finite element software to utilize reduced order models. The simulation results include both baseline results for the system and the results of injecting failures into the system for monitoring and predictive maintenance.