A Simulation-Based Digital Twin for Model-Driven Health Monitoring and Predictive Maintenance of an Automotive Braking System
A Simulation-Based Digital Twin for Model-Driven Health Monitoring and Predictive Maintenance of an Automotive Braking System
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DOI：
10.3384/ecp1713235
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发表时间：
2017-07
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通讯作者：
R. Magargle;L. Johnson;Padmesh Mandloi;Peyman Davoudabadi;Omkar Kesarkar;Sivasubramani Krishnaswamy;John Batteh;Anand Pitchaikani
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作者：
R. Magargle;L. Johnson;Padmesh Mandloi;Peyman Davoudabadi;Omkar Kesarkar;Sivasubramani Krishnaswamy;John Batteh;Anand Pitchaikani
本文介绍了一种模型驱动的方法，以支持汽车制动系统的热监测和预测性维护。这种方法包括创建基于仿真的数字孪生模型或数值模型，该模型将不同的建模形式结合到制动系统的集成模型中，该模型可用于监测、诊断和故障诊断。本文概述了基本模型，包括Modelica模型、系统模型各个关键组件的降阶模型以及控制和传感器模型。Modelica模型在ANSYS Simplifiers仿真中实现，以利用现有的建模工作和与其他ANSYS有限元软件的连接来利用降阶模型。仿真结果包括系统的基线结果和将故障注入系统以进行监控和预测性维护的结果。
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.