Rotary-scaling fine-tuning (RSFT) method for optimizing railway wheel profiles and its application to a locomotive  

作　　者：Yunguang Ye Yayun Qi Dachuan Shi Yu Sun Yichang Zhou Markus Hecht 

机构地区：[1]Institute of Land and Sea Transport Systems,Technical University of Berlin,10587 Berlin,Germany [2]State Key Laboratory of Traction Power,Southwest Jiaotong University,Chengdu 610331,China [3]College of Transportation Science and Engineering,Nanjing Tech University,Nanjing 210009,China

出　　处：《Railway Engineering Science》2020年第2期160-183,共24页铁道工程科学（英文版）

基　　金：the Assets4Rail Project which is funded by the Shift2Rail Joint Undertaking under the EU’s H2020 program(Grant No.826250);the Open Research Fund of State Key Laboratory of Traction Power of Southwest Jiaotong University(Grant No.TPL2011);part of the experiment data concerning the railway line is supported by the DynoTRAIN Project,funded by European Commission(Grant No.234079);The first author is also supported by the China Scholarship Council(Grant No.201707000113).

摘　　要：The existing multi-objective wheel profile optimization methods mainly consist of three sub-modules:(1)wheel profile generation,(2)multi-body dynamics simulation,and(3)an optimization algorithm.For the first module,a comparably conservative rotary-scaling finetuning(RSFT)method,which introduces two design variables and an empirical formula,is proposed to fine-tune the traditional wheel profiles for improving their engineering applicability.For the second module,for the TRAXX locomotives serving on the Blankenburg–Rubeland line,an optimization function representing the relationship between the wheel profile and the wheel–rail wear number is established based on Kriging surrogate model(KSM).For the third module,a method combining the regression capability of KSM with the iterative computing power of particle swarm optimization(PSO)is proposed to quickly and reliably implement the task of optimizing wheel profiles.Finally,with the RSFT–KSM–PSO method,we propose two wear-resistant wheel profiles for the TRAXX locomotives serving on the Blankenburg–Rubeland line,namely S1002-S and S1002-M.The S1002-S profile minimizes the total wear number by 30%,while the S1002-M profile makes the wear distribution more uniform through a proper sacrifice of the tread wear number,and the total wear number is reduced by 21%.The quasi-static and hunting stability tests further demonstrate that the profile designed by the RSFT–KSM–PSO method is promising for practical engineering applications.

关 键 词：Wheel profile optimization Wear reduction Rotary-scaling fine-tuning Particle swarm optimization Kriging surrogate model 

分 类 号：U270.33[机械工程—车辆工程]