May 15–17, 2017 in Prague, Czech Republic
[Proceedings] [Sessions] [Authors] [Schedule] [Further material]

Papers by Omkar Kesarkar:

Title: A Simulation-Based Digital Twin for Model-Driven Health Monitoring and Predictive Maintenance of an Automotive Braking System
Authors: Ryan Magargle, Lee Johnson, Padmesh Mandloi, Peyman Davoudabadi, Omkar Kesarkar, Sivasubramani Krishnaswamy, John Batteh and Anand Pitchaikani
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 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.
Links: Full paper