Powertrain Digital Twin for Replacement Component Selection
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Solution Overview
Problem
Large and complex fluid control systems, such as cooling and ventilation systems, often contain inefficient or improperly dimensioned electric motors, leading to significant energy wastage.
Innovation Solution
A computer-implemented method using a digital twin model to simulate and evaluate potential replacement components, such as variable speed drives (VSDs), to optimize the powertrain by selecting a suitable replacement component that enhances energy efficiency and reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If physical testing is conducted for each potential replacement component, then selection accuracy is improved, but time consumption and cost increase significantly
Solution Approach 1:
The patent creates a digital twin model that replicates the physical powertrain system's behavior and characteristics. This digital copy allows for virtual evaluation of replacement components, eliminating the need for physical testing while maintaining selection accuracy. The digital twin captures the system's operational parameters, performance characteristics, and interaction patterns, enabling realistic simulation of replacement scenarios.
Solution Approach 2:
The patent performs preliminary analysis by collecting and processing operational data from the existing powertrain system before actual replacement occurs. The digital twin model is prepared in advance with all necessary system parameters and performance metrics, allowing rapid evaluation of multiple replacement components without time-consuming physical testing during the actual replacement process.
2Loss of energy
If comprehensive evaluation of multiple replacement components is performed, then energy savings are maximized, but system complexity increases
Solution Approach 1:
The patent implements a multi-functional evaluation system that simultaneously assesses multiple replacement components across various performance criteria (energy efficiency, compatibility, operational characteristics). The digital twin model serves multiple purposes: system replication, performance prediction, compatibility verification, and optimization analysis, all within a single integrated platform that handles comprehensive component evaluation.
3Productivity
If digital twin modeling is implemented for powertrain evaluation, then physical testing is reduced, but data processing requirements increase
Solution Approach 1:
The patent extracts only the essential and relevant operational parameters from the powertrain system to create the digital twin model. Rather than processing all possible data, the system identifies and extracts key performance indicators, operational characteristics, and critical system parameters that are necessary for accurate replacement component evaluation, reducing overall data processing requirements while maintaining evaluation accuracy.
Data Source
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AI summary
A method for selecting a replacement component (103) for a powertrain (100) comprising at least one electric motor (101) configured to drive a fluid moving device (102) in a fluid control system (110), the method comprising: receiving data relating to the powertrain, comprising at least nameplate data and powertrain operational data relating to operational characteristics of the powertrain within the fluid control system; creating a digital twin model of the powertrain; identifying system requirements of the fluid control system; obtaining technical information (t1, t2, ..., tn) relating to a plurality of potential replacement components from a database (150); digitally evaluating the use of each one of the potential replacement components within the powertrain by using the digital twin model in combination with the technical information and the system requirements; selecting the replacement component from the plurality of potential replacement components based on the digital evaluation.