基于粒子群算法的车体钢轨回路电流和过电压的抑制
Train-rail Circuit Currents and Overvoltage Suppression Based on Particle Swarm Algorithm
刘建城 1孙传铭 1张作钦 1朱涛 2肖嵩 2高国强2
作者信息
- 1. 中车青岛四方机车车辆股份有限公司,山东 青岛 266111
- 2. 西南交通大学 电气工程学院,成都 611756
- 折叠
摘要
高速动车组接地系统中的车体钢轨回路电流和车体过电压问题会引起车体电压升高,车体电磁环境恶化,车载弱电和通讯系统损坏等问题,严重影响动车组的安全运行.围绕车体钢轨回路电流及车体电位问题,建立高速列车动态运行等效模型,基于模型对比分析了实测和仿真结果,研究动车组过电分相区间时车体横向和纵向过电压的分布以及过电压在车体的传播规律,分析列车在吸上线区间运行时各接地轮轴上的电流幅值变化和分布规律,并基于实测和仿真结果,分析车体钢轨回路电流分布,最后综合考虑车体钢轨回路电流和车体过电压危害值,结合粒子群算法给出一种可参考的定常接地参数的最优解,使优化后各车体过电压幅值和各接地轴的电流幅值处在更均衡的范围内.
Abstract
The train body rail circuit current and train body over-voltage problems in the grounding system of high-speed EMUs will cause train body voltage rise,and worsen the electromagnetic environment of the train body,leading to problems such as vehicle borne weak current and communication system damage,which will seriously affect the safe operation of Multiple unit.Focusing on the problems of train body rail circuit current and train body potential,the equivalent model of high-speed train dynamic operation of Multiple unit is established.Based on the model,the measured and simulation results are compared and analyzed.The distribution of train body transverse and longitudinal over-voltage and the propagation law of over-voltage in the train body when the Multiple unit is in over-voltage phase separation section are studied.Based on the actual measurement and simulation results,the distribution of the current in the train body rail circuit was analyzed.Finally,a comprehensive consideration of the train body rail circuit current and the harm value of the train body overvoltage was given combined with particle swarm optimization algorithm to provide an optimal solution for the reference constant grounding parameters,so that the optimized overvoltage amplitude of each train body and the current amplitude of each grounding axis are in a more balanced range.
关键词
高速动车组/车体钢轨回路电流/车体过电压/粒子群算法/综合优化Key words
High-speed trains/train-rail circuit current/body overvoltage/particle swarm algorithm/integrated optimizatio引用本文复制引用
出版年
2024
NETL
NSTL
万方数据