B-spline fitting method of optimal running-time-energy function in an urban rail section

Due to the complexity of the operation control of urban rail transit, it is very difficult to optimize the train operation strategy in different running times. This paper studied the functional relationship between running time and optimal energy consumption by abundant actual train operation data. Taking the running time and energy consumption corresponding to each train operation strategy as data points, the discriminant criterion of outliers was constructed to select the optimal fitting data set from the original data set. Furthermore, a B-spline curve fitting method combined with a Genetic Algorithm was proposed, which is proven to have high fitting accuracy and convergence speed. The validation of Guangzhou Metro’s actual operation data of one certain section shows that the energy-running-time function curve fitted by our method has lower energy and could be used for the operation of an urban rail train. © 2021, Central South University Press. All rights reserved.