Multi-Fidelity Simulation Model Synthesis Using Functional Operators
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Solution Overview
Problem
Designing modern cyber-physical systems, such as advanced automotive systems, is challenging due to the complexity of integrating hundreds of electronic control units and diverse components, requiring improved design automation tools that can manage heterogeneity and reduce development time and cost.
Innovation Solution
A method for synthesizing simulation models using functional operators, which involves parsing a functional model, receiving a functional operator, mapping functions according to a structural template, and generating an updated simulation model, allowing for the creation of high-fidelity simulation models that can handle complex systems like automotive HVAC systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional design automation tools are used to manage complex cyber-physical systems, then the system can handle basic design tasks, but the complexity of integrating hundreds of electronic control units and diverse components increases significantly, leading to longer development time and higher costs
Solution Approach 1:
The patent segments the complex system modeling task into multiple fidelity levels (high-level abstract models and low-level detailed models). Each level handles different aspects of system complexity, allowing manageable integration of hundreds of components without overwhelming the design process. The functional operator framework divides the synthesis process into discrete, composable operations.
Solution Approach 2:
The patent implements nested modeling where high-fidelity simulation models contain lower-fidelity models, and functional operators can be recursively applied. This nested structure allows complex systems to be built by composing simpler subsystems, each with its own level of detail, reducing the overall complexity burden on any single modeling layer.
2Measurement precision
If high-fidelity simulation models are created for complex systems, then the model accuracy and detail are improved, but the time required to generate and process these models increases significantly
Solution Approach 1:
The patent performs preliminary actions by automatically generating high-fidelity simulation models from existing lower-fidelity models using functional operators. This preliminary synthesis eliminates the need to manually create detailed models from scratch, significantly reducing model generation time while maintaining high fidelity. The functional operators encapsulate complex modeling logic that can be applied automatically.
Solution Approach 2:
The patent creates copies of models at different fidelity levels, where high-fidelity simulation models are generated as copies from lower-fidelity versions. This copying approach allows the system to reuse existing model structures and data, reducing the time required to create detailed simulation models while preserving accuracy through systematic refinement.
3Manufacturing precision
If detailed functional models are parsed and mapped using structural templates, then the accuracy of simulation model synthesis is improved, but the computational processing time and complexity increase
Solution Approach 1:
The patent implements universal structural templates that can be applied across multiple functional operators and model types. These templates define standardized patterns for parsing functional models and synthesizing simulation models, allowing the same framework to handle diverse system types. This universality maintains synthesis accuracy while improving efficiency by avoiding the need to create custom processing logic for each model type.
Data Source
AI summary
Methods for synthesis of simulation models using functional operators. A method includes parsing a functional model, receiving a functional operator for a function within a simulation component of the functional model, receiving a structural template of the functional operator from a functional operator structural template library, mapping a plurality of functions according to the structural template of the functional operator to update the simulation component, and generating a simulation model with the updated simulation component.