基于粒子群优化的无接触网公共交通系统能量最小化

K. Colak, D. Czarkowski, F. de León
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引用次数: 9

摘要

针对无接触网轨道交通系统,提出了一种基于粒子群优化的列车模型和能量最小化控制算法。在MATLAB/Simulink中建立列车模型。由于列车的性能在很大程度上取决于超级电容器(SC)的电压。仿真中考虑了低电压下牵引力的减小。在运行时间、充电时间、最大充电电流、SC电压和站间距离等约束条件下,研究了充电点对运行时间的影响,并利用仿真结果找到了最佳充电点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Energy minimization for catenary-free mass transit systems using Particle Swarm Optimization
In this paper, a train model and algorithm of energy minimization control using Particle Swarm Optimization (PSO) are introduced for a catenary-free mass transit system. The train model is created in MATLAB/Simulink. Since the performance of the train heavily depends on the supercapacitor (SC) voltage. Tractive effort reduction is considered under low SC voltage in the simulations. Impact of coasting point on the running time is investigated and simulation results are used to find optimum coasting point under several constraints, such as running time, charging time, maximum charging current, SC voltage and distance between stations.
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