Harmonic Balance Co-Simulation for Multi-Resolution Synchronization
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Solution Overview
Problem
Co-simulation of complex systems with diverse subsystems, such as electric vehicles, faces challenges in synchronizing sub-simulations with different time resolutions, leading to instability and inefficiencies due to the need for large data storage and slow data transfer across different geographic zones or cloud environments.
Innovation Solution
A harmonic balance co-simulation method that converts time domain sub-simulation results into the frequency domain, using Fast Fourier Transform components and a harmonic balance engine to determine a cost function based on predetermined frequencies, allowing for efficient coordination and convergence of sub-simulations with different time steps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If time domain sub-simulation results are used for co-simulation of diverse subsystems, then all frequency information is preserved, but computational bandwidth and data transfer requirements increase significantly
Solution Approach 1:
The patent extracts only the necessary frequency components (predetermined frequencies and their harmonics) from the complete frequency spectrum of sub-simulation results. This extraction process removes unnecessary data while preserving the essential frequency information needed for accurate co-simulation, thereby reducing data volume without sacrificing measurement precision.
Solution Approach 2:
The patent applies local quality by treating different frequency components differently - predetermined frequencies and their harmonics are preserved with high fidelity, while other frequency components are discarded. This selective preservation optimizes the data set by maintaining quality only where it matters for the specific co-simulation application.
2Reliability
If all sub-simulation data is transferred and processed for convergence determination, then complete system behavior is captured, but computational time and processing resources increase
Solution Approach 1:
The patent extracts only the essential frequency components (predetermined frequencies and harmonics) needed to determine convergence. By processing only this subset of frequency data rather than the complete spectrum, the system achieves reliable convergence determination with significantly reduced computational time and processing resources.
Solution Approach 2:
The patent applies partial action by processing only the necessary portion of frequency data (predetermined frequencies and harmonics) rather than the complete frequency spectrum. This partial processing is sufficient to determine convergence accurately while avoiding the excessive computational burden of analyzing all frequency components.
3Adaptability or versatility
If sub-simulations with different time resolutions are synchronized in time domain, then all subsystem behaviors are captured, but data storage requirements and transfer bandwidth increase
Solution Approach 1:
The patent transitions from time domain to frequency domain representation, changing the dimensional perspective of the data. This transformation allows sub-simulations with different time resolutions to be synchronized more efficiently, as frequency domain representation naturally handles multi-resolution data with reduced storage and transfer requirements.
Solution Approach 2:
The patent extracts only the essential frequency components from each sub-simulation, reducing the volume of data that needs to be stored and transferred while maintaining the ability to synchronize diverse subsystems with different time resolutions.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Facilitates quicker simulation convergence and efficient data management by focusing on selected harmonics, reducing computational bandwidth and improving synchronization across diverse sub-systems.
Implementation Method 1
converting each time domain sub-simulation result into the frequency domain to provide a plurality of frequency domain sub-simulation result
Data Source
AI summary
A method of co-simulating a system comprising receiving a plurality of time domain sub-simulation results generated by a corresponding plurality of sub-simulations based on a current set of variables, each of the sub-simulations of the plurality of sub-simulations being a sub-simulation of the system, converting each time domain sub-simulation result into the frequency domain to provide a plurality of frequency domain sub-simulation result, determining a harmonic balance cost function of the co-simulation based on the plurality of frequency domain sub-simulation results and updating the current set of variables based on the harmonic balance cost function.