Virtual Test Cell for Automotive Powertrain Calibration
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Solution Overview
Problem
Automated testing procedures for complex electromechanical systems, such as automotive powertrains, are costly and time-consuming due to the high number of variables and interactions, which existing methods fail to adequately account for, resulting in inefficient calibration processes.
Innovation Solution
The implementation of a virtual test cell methodology using sequential space-filling sampling to collect a limited set of test data, creating a mathematical model that allows for the simulation of additional test points, thereby reducing the need for extensive physical testing and optimizing calibration relationships.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If individual tests are performed for each calibration of interest, then calibration accuracy can be achieved, but testing time and cost increase dramatically
Solution Approach 1:
The patent creates a virtual test cell that copies the essential characteristics and response behaviors of the physical test cell through mathematical modeling. This virtual replica allows multiple calibration tests to be performed computationally without requiring corresponding physical tests, dramatically reducing testing time while maintaining calibration accuracy. The virtual test cell serves as a surrogate that preserves the input-output relationships of the actual system.
Solution Approach 2:
The patent performs preliminary characterization of the physical test cell by collecting input-output data pairs and using this information to build the virtual model before actual calibration tests are conducted. This preliminary action includes identifying the system's response surfaces and creating mathematical representations that can be used to guide subsequent calibration efforts, reducing the need for extensive trial-and-error physical testing.
2Reliability
If exhaustive measurements are performed to properly calibrate all variables, then calibration completeness is achieved, but the process becomes prohibitively expensive
Solution Approach 1:
The virtual test cell serves multiple calibration functions simultaneously through a single mathematical model. Rather than requiring separate physical test setups for each calibration objective, the virtual model can be queried for different calibration targets (fuel economy, performance, quality metrics) by simply changing the optimization objectives, making the testing process universally applicable to multiple calibration goals.
Solution Approach 2:
The patent transforms the calibration problem from physical domain measurements to mathematical parameter optimization. By representing the test cell behavior through response surfaces and mathematical models, the system can evaluate calibration candidates through computational parameter changes rather than expensive physical reconfigurations, significantly reducing testing costs while maintaining calibration completeness.
3Productivity
If Design of Experiments techniques are used to limit test conditions, then test efficiency improves, but interaction between multiple variables is not properly accounted for
Solution Approach 1:
The patent moves the analysis from traditional DOE's discrete factor-level space to a continuous response surface dimensionality. Instead of testing at discrete combinations of factor levels, the system creates continuous mathematical surfaces that represent system behavior across the entire input space, allowing variable interactions to be captured and analyzed in this additional dimensional space without sacrificing test efficiency.
Solution Approach 2:
The patent replaces the mechanical testing system with a mathematical modeling system. Rather than physically adjusting and measuring each variable combination, the system uses computational mathematics to represent and analyze variable interactions. This substitution preserves test efficiency while eliminating the information loss inherent in discrete DOE approaches, as the mathematical models can capture continuous interactions between variables.
Data Source
AI summary
A method for calibrating a physical test cell includes the steps of: determining a set of inputs to be provided to the physical test cell based in part on a set of historical test data; providing the inputs to the physical test cell and receiving a set of outputs associated therewith, wherein the providing includes implementing a sequential space filling sampling procedure to substantially cover a region defined by the set of historical values; creating a virtual test cell comprising one or more response surfaces based on the set of outputs; and interrogating the virtual test cell to determine a calibration relationship between at least one of the inputs and at least one of the outputs. Smooth Kriging may be used to determine the virtual test cell.