ANSYS. has been granted a patent for a method that efficiently fits black box simulation data to create Linear Parametrically Varying (LPV) models for thermal management systems. This approach enhances dynamic simulations to accurately predict temperatures in systems like battery packs and circuit boards. GlobalData’s report on ANSYS gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on ANSYS, Capillary blood collection devices was a key innovation area identified from patents. ANSYS's grant share as of June 2024 was 57%. Grant share is based on the ratio of number of grants to total number of patents.
Thermal management system modeling using linear parametrically varying models
The patent US12039238B1 outlines a method for simulating thermal properties of physical systems, specifically battery packs or circuit boards, using a computer-aided design (CAD) software system. The method involves executing a computer-implemented model that simulates outputs based on various inputs, each associated with specific energy inputs and scheduling parameters, such as coolant flow rates. The process includes running the model at fixed values of these parameters to obtain output responses, fitting Linear Time Invariant (LTI) representations to these responses, and updating coefficient matrices to ensure the negative real poles are arranged appropriately. The method further constructs a Linear Parameter Varying-Reduced Order Model (LPV-ROM) representation for each input, which incorporates the scheduling parameters and is refined through repeated iterations if prediction errors exceed a predetermined threshold.
Additionally, the method emphasizes the generation of training data from experimental measurements conducted on the physical system, which is used to calibrate the LPV-ROMs. The calibrated models are then combined to form an overall LPV-ROM that accurately represents the thermal dynamics of the system. The patent specifies that each LPV-ROM representation may include a diagonal system matrix and an input matrix consisting of a column vector of ones. The method also allows for the use of piece-wise linear interpolation functions and defines the number of state-space variables to be between 2 and 8. Overall, this innovative approach aims to enhance the control and simulation of thermal properties in complex physical systems.
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