دانلود رایگان مقاله انگلیسی بهینه سازی صرفه جویی در انرژی قطار بر اساس الگوریتم ژنتیک نسبت طلایی - IEEE 2018

Abstract

In order to reduce the energy consumption of train operation, an optimization method based on genetic algorithm of golden section is proposed. Firstly, the Multi-particle train model is established. Secondly, the optimal operation strategy of subway trains is analyzed according to different ramps. Then, a golden section genetic algorithm (GR-GA) is proposed to solve the problem that genetic algorithm is easy to fall into local optimum. A golden section genetic algorithm (GR-GA) is proposed to search for the optimal transfer position of train and the best adaptive point of searching crossover and mutation operator with golden ratio is introduced, which improves the local optimization ability and convergence performance. Taking Yizhuang line as a simulation case, the results show that the proposed algorithm has a better optimization effect.

V.CONCLUSION

In this paper, energy consumption of the train is regarded as the objective. Considering speed limit and the slope, the optimal controlling strategy of the train on different slopes is analyzed. Based on this, a golden section genetic algorithm is proposed to find out the position of the optimal operating point of the train, so as to obtain the optimal train controlling sequence. The effectiveness of the algorithm is verified by Matlab simulation. The results show that the algorithm converges faster than the traditional genetic algorithm and the reduction of the energy consumption is significant. To study the optimization of multi-objective of train is our next research direction.