Closed-Loop Virtual Calibration – Controls and Diagnostic Development
In a prior blog, I discussed a few methods and benefits of open-loop virtual calibration. Now I will explain what closed-loop virtual calibration is and the types of analysis that can be performed.
Closed-loop virtual calibration is something that almost all powertrain manufacturers can perform by having 3 traditionally separate groups (controls, simulation/CAE, and calibration) work together. Every OEM will have the resources they need to complete this type of analysis: a simulation model of their powertrain (simulation group), engineers who develop calibration (calibration group), and a model of the controls on the ECM or physical ECM (controls group).
What is Closed-Loop Virtual Calibration?
Closed-loop virtual calibration is when the simulation model is used as a plant model to the controls system. This means having a simulation model of the powertrain with supplemental controls in virtual/hardware that control the simulated powertrain. In the end, the goal is to have an entire virtual system that behaves the same as a physical powertrain with a computer. This enables powertrain calibration to be performed upfront and provides a system level understanding.
There are two common ways that the industry performs closed-loop virtual calibration. Those two methods are HiL (Hardware in the loop) and MiL (model in the loop).
- HiL – Hardware-in-the-loop tells the virtual powertrain how to interact with a physical control unit and other actuator/sensor (Hardware).
- MiL – Model-in-the-loop tells the virtual powertrain how to interact with a model of the controls and actuators/sensors (Model).
Regardless of what type of closed-loop virtual calibration is performed, each will improve the existing iterative process of physical powertrain calibration when used upfront.
Basic example of MiL with Fueling PI Controller
Why Closed-Loop Virtual Calibration Is So Powerful
One of the most important benefits of closed-loop virtual calibration is that there is zero risk of damage or unintentional aging to any expensive hardware. It allows existing calibration tasks to be performed more efficiently upfront by a virtual model with controls.
Closed-loop virtual calibration also enables new insights and tasks to be performed due to the virtual nature of the powertrain. For example, the model can have failure modes induced that would be difficult or risky to recreate as desired on a physical powertrain. That means engineers are able to detect and respond to key failures that would otherwise be challenging to catch.
With enough parallelization, robustness studies are performed to understand powertrain performance in various scenarios. This is critical in understanding product performance with respect to defining warranty and determining regulatory compliance as well as customer satisfaction.
The value proposition to pursue a virtual calibration workflow is significant. Some tasks that can be performed upfront are:
- Test Trips/Cycles
- Diagnostic Tuning
- Off-Nominal Calibration
- Robust Controls Development (to predict aging, component quality, etc.)
- Software Verification
Any single one of these tasks incurs significant costs in the tens of thousands to millions of dollars. Performing work upfront with a model that has controls included will increase efficiency of these tasks, reducing time and saving money while also supporting physical tests.
In the next blog I will go in depth on one of the powertrain development tasks mentioned (diagnostic tuning) and how that process is improved with virtual calibration.
If you are interested in discussing virtual calibration or would like more details please reach out and contact us.
Written By: Michael Bambula