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

Ryan Magargle

Lee Johnson

Padmesh Mandloi

Peyman Davoudabadi

Omkar Kesarkar

Sivasubramani Krishnaswamy

John Batteh
Modelon Inc., USA

Anand Pitchaikani
Modelon Inc., USA

Ladda ner artikelhttp://dx.doi.org/10.3384/ecp1713235

Ingår i: Proceedings of the 12th International Modelica Conference, Prague, Czech Republic, May 15-17, 2017

Linköping Electronic Conference Proceedings 132:3, s. 35-46

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Publicerad: 2017-07-04

ISBN: 978-91-7685-575-1

ISSN: 1650-3686 (tryckt), 1650-3740 (online)


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 that combines models and 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 simulation results include both baseline results for the system and the results of injecting failures into the system for monitoring and predictive maintenance.


digital twin; electronics; Electromagnetics; hydraulics; pneumatics; braking system; automotive; FEA;


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