Backward discrete state event-driven power electronic simulation method, device and medium

Abstract

The invention discloses a backward discrete state event-driven power electronic simulation method, and the method comprises the steps: carrying out the simulation initialization and the simulation calculation at a k-th step, wherein K is not less than zero, and the simulation calculation at the k-th step comprises the following steps: S1, generating a system state equation at the k-th step; S2, determining the candidate quantification function value of each state variable at a (k+1)-th step; S3, building a finite-state machine, and determining the quantification function value of each state variable; S4, calculating a derivative vector based on the quantification function values at the (k+1)-th step and the system state equation; S5, determining the moment of simulation calculation at the (k+1)-th step based on the occurrence moment of an event. The invention also discloses a simulation calculation device and a computer readable storage medium storing a simulation program. According to the invention, the simulation method provided by the invention can achieve the high-efficiency selection of a Q function vector, and the simulation efficiency and numerical value stability of the method are apparently superior to the simulation efficiency and numerical value stability of a quantification state system (QSS) method and a conventional time discretization rigid solving method during the solving of a rigid system.

Description

technical field [0001] The present invention relates to the technical field of power electronics simulation, and more specifically, to a simulation method for a power electronics converter system, a simulation computing device, and a computer-readable storage medium storing a simulation program. Background technique [0002] Computer numerical simulation is an important tool to analyze the non-ideal characteristics of power electronic systems. However, in the power electronic system considering the non-ideal model of the power switching device and the stray parameters of the circuit, the simulation model has the characteristics of large time scale span, many discontinuities, nonlinearity and rigidity. Traditional numerical calculation methods based on time discretization (such as trapezoidal method, Runge-Kutta method, etc.) have the following problems when solving such a system (1) The choice of step size is a dilemma—fixed step size may lead to the accumulation of calculat...

AI Technical Summary

Problems solved by technology

As an implicit event-driven algorithm, the biggest problem of BQSS is how to implement it efficiently. The difficulty lies in: (1) The derivative of the state variable is not only related to the value of its own Q function, but also due to the Q function of other state variables. Therefore, the determination of the Q function of each state variable is mutually influenced and restricted; (2) The Q function of each state variable in each step of calculation has two values. For a high-dimensional complex system, if the The way of enumeration will lead to a huge amount of combinations, which is difficult to implement

At present, the existing implementation schemes of BQSS do not consider the mutual constraints when the Q function is determined. For the part of the algorithm process where the value of the Q function has been determined, the sign of the derivative may change due to the value of the undetermined part, making its state The property that the variable approaches the Q function is destroyed, and in a multi-dimensional complex system, it will be impossible to find the correct Q function vector, or even impossible at all.

The limited calculation examples are also simple low-dimensional systems, and there is still no effective implementation plan for high-dimensional complex systems

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