ZONG Congcong, CHEN Dilai, ZHOU Yunfei, et al. Parameter Optimal Design of Railway Vehicle Based on Genetic Algorithm[J]. Electric Drive for Locomotives, 2018,(4):33-36.
ZONG Congcong, CHEN Dilai, ZHOU Yunfei, et al. Parameter Optimal Design of Railway Vehicle Based on Genetic Algorithm[J]. Electric Drive for Locomotives, 2018,(4):33-36. DOI: 10.13890/j.issn.1000-128x.2018.04.008.
The natural frequency of railway vehicle’s car body and hunting frequency of bogie will be close to each other at a certain speed, and this can bring the coupling resonance between car body and bogie, which have a bad effect on stability of vehicle. In order to reduce the degree of resonance, a transformed Euclid nearness was selected as the index of modal similarity, and the hunting stability of vehicle was chosen as the control conditions of the model. Finally, genetic algorithm was used to optimize the second suspension parameter. The results showed that, the optimal second suspension parameter could be found by genetic algorithm when the other parameters were constant, and the results were satisfactory. The smaller the coupling degree was, the stronger the linear of the modal frequency curve was, and the more inconspicuous the frequency trapping among modes was,there was a faint influence between the modes in this case;The smaller the coupling degree was, the more gently the damping ratio changed, and the bigger the damping ratio of body-yawing or upper-sway was.