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Parameter Estimation of Black Box Arc Model based on Heuristic Optimization Algorithms

机译:基于启发式优化算法的黑匣子弧模型参数估计

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The black box arc model is suitable to describe the arcing process of hybrid circuit breaker, since it provides an effective way to integrate the arc model into an electrical circuit. However, it is more difficult to determine the parameters of the arc model according to the performance of circuit breaker than to solve the analytical equations of arc model. A library of arc models including Mayr, Cassie, Kema and other models has been built and verified based on MATLAB Simulink/Simscape. Heuristic optimization methods, such as Genetic Algorithm, Simulated Annealing and Particle Swarm Optimization, have been used to develop the algorithms to estimate the parameters of arc models. The results show the inverse modelling technique is effective to find the proper parameters which describe the changing of conductance of arc plasma. It is also found that the GA with well-selected parameters has the advantage over other methods.
机译:黑盒电弧模型适用于描述混合断路器的电弧放电过程,因为它提供了将电弧模型集成到电路中的有效方法。但是,根据断路器的性能来确定电弧模型的参数比解决电弧模型的解析方程要困难得多。已基于MATLAB Simulink / Simscape建立并验证了包括Mayr,Cassie,Kema和其他模型的弧模型库。遗传算法,模拟退火算法和粒子群算法等启发式优化方法已被用于开发估计电弧模型参数的算法。结果表明,逆建模技术可以有效地找到描述电弧等离子体电导变化的合适参数。还发现具有良好选择的参数的GA与其他方法相比具有优势。

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