Rather than just listing all the new capabilities for system simulation and analysis in the latest release of ANSYS Simplorer, I thought it would be interesting to share a cool example of how our systems capabilities have been applied to health monitoring of an automotive braking system. And along the way, I’ll highlight how the advancements in ANSYS 18 help our customers model and simulate systems such as these.
This example illustrates a physics-based system model intended to support health monitoring and predictive maintenance of automotive braking systems. And while this is an automotive example, our customers throughout different industries are developing similar capabilities to monitor and manage the performance of their products in operation — all in the name of improving safety, performance, and overall customer satisfaction.
Model-based approaches and physics simulation are powerful components of creating the digital twin of a physical asset in operation — a digital replica of the asset that is used to diagnose anomalies in performance and for predicting the state of health and remaining useful life of that asset. These insights can subsequently be used to optimize operational downtime, trigger preemptive maintenance, and mitigate costly failures.
Back to the example…the braking system model was created in ANSYS Simplorer, making use of a number of different modeling approaches and interfaces for assembling the essential dynamics and behaviors to simulate braking system performance during normal and abnormal operation.
The system-level model of an anti-lock brake system for predicting brake pad wear is modeled and simulated with Simplorer.
Reduced-order models (ROMs) are used throughout the braking system model, providing important source of detailed component behavior from 3-D physics simulation. The system model includes ROMs from ANSYS Maxwell for the electromagnetic behavior of the brake actuator and the magnetoresistive wheel speed sensor, and a ROM created from ANSYS Mechanical simulations that accurately model brake pad wear as a function of wheel speed and brake pressure.
System-level models for the braking actuator and wheel speed sensor are ROMs from electromagnetic simulations in ANSYS Maxwell.
Adding to the rich collection of ANSYS’ reduced-order modeling capabilities, ANSYS 18 includes the new Thermal Model Identification Toolkit, the Battery Design Toolkit (available from the ANSYS App Store), and the System Model Identification Toolkit, all used within Simplorer to create system models at higher levels of physics-based fidelity.
The hydraulic and pneumatic dynamics of the braking system were modeled using the new Modelica diagram editor in Simplorer 18, using the freely-available Modelica Standard Library as well as the Hydraulics Library and Pneumatics Library offered by Modelon. We continue to expand support for Modelica within Simplorer, allowing users to combine their Modelica models with ROMs and other modeling formats, and to analyze them within Simplorer’s powerful simulation environment.
Detailed simulation in ANSYS Mechanical is used to produce a ROM that predicts brake pad wear during system analysis.
Finally, an antilock braking control algorithm was built with ANSYS SCADE and integrated into the Simplorer system model through the standard Functional Mock-up Interface (FMI).
Simplorer 18 features a graphical environment for creating Modelica models from a number of standard and commercial libraries.
In ANSYS 18, we have introduced support for FMI Co-simulation, allowing our users to integrate even more models from the continually growing list of FMI-compliant tools, and making it easier than ever to assemble complete system functionality within Simplorer. Check out this short video for more highlights of how we’ve expanded ROM support and system modeling interoperability within Simplorer 18.
How is this system model used? As an example, we included the effect of a malfunctioning wheel speed sensor and simulated the resulting effect on system performance to observe the telltale signatures that would assist an automotive manufacturer in diagnosing a failing component. Further, we can use the system model to predict the amount of brake pad wear due to abnormal conditions in the system.
ANSYS SCADE is used to model control algorithms that are integrated into the system model using the FMI.
System simulation produces results to assess system performance under normal and abnormal conditions.
We could go into a lot more detail for this example…and we do. We are presenting “A Simulation-Based Digital Twin for Model-Driven Health Monitoring and Predictive Maintenance of an Automotive Braking System” at the 12th International Modelica Conference in Prague, Czech Republic, on May 15-17, 2017. But for now, I hope this brief overview gives you a sense of how system simulation can be used to complement monitoring and diagnosis of actual products in operation, enabled through higher levels of physics-based model fidelity and flexibility.
Register for the ANSYS 18 System Simulation Webinar Today!
Learn more about what ANSYS 18 is delivering for system simulation and Simplorer in my ANSYS 18 Innovations Systems webinar on March 2.
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