Cluster system simulation solving method and device, storage medium and computer equipment

By dividing the cluster system into independent subsystems and judging the algebraic ring based on controlled relationships, and using appropriate solution methods, the efficient and accurate problem of simulation solution of power electronics and motor equipment cluster systems in the prior art is solved, and efficient simulation solution is achieved.

CN120449504APending Publication Date: 2025-08-08TSINGHUA UNIVERSITY +1
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Patent Information

Application Number
CN202510683632.0
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-05-26
Publication Date
2025-08-08

AI Technical Summary

Technical Problem

In the prior art, when dealing with power electronics and motor equipment cluster systems, there is a check and balance relationship between efficiency and accuracy of simulation solutions, resulting in increased computational complexity and time overhead.

Method used

The cluster system is divided into multiple independent subsystems, and a digital model of each subsystem is constructed, signal connection is performed through a controlled source method. The differential equation is first solved to determine whether there is an algebraic ring. If it exists, the Newton-Ravson iterative algorithm is used. If it does not exist, the display function is used for sequential solution.

Benefits of technology

By reducing matrix dimensions and avoiding blind iterations, the efficiency and accuracy of simulation solutions are significantly improved, especially when there is no algebraic ring.

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Abstract

According to the cluster system simulation solving method and device, the storage medium and the computer equipment provided by the invention, during simulation solving, the cluster system is divided into the multiple independent subsystems according to the topological structure of the cluster system, and the digital model of each subsystem is constructed, so that the model matrix dimension is reduced, and the single-step calculation amount is reduced; and then differential solution is carried out on the digital model of each subsystem to obtain a differential solution result, and then algebraic solution is carried out, so that mutual containment of the two subsystems is avoided, and the speed is increased. Before algebraic solution, dependence parameters of the cluster system are determined according to the controlled relationship among the subsystems, and whether the cluster system has an algebraic ring is determined and judged based on the dependence parameters; if yes, carrying out iterative solution on each digital model by adopting a Newton-Raphson iterative algorithm to avoid error accumulation caused by closed-loop dependence; and if not, sequentially solving the algebraic equations in the digital models by adopting a display function, and improving the solving efficiency to a millisecond level.
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