Train Operation Curve Optimization for an Urban Rail Interval With Multi-Parameter Adjustment

This paper proposes an energy consumption optimization method of train operation by controlling multiple parameters for an urban rail interval. The parameters include the maximum operation speed, the ratio of the minimum coasting speed to the maximum speed, the maximum traction, and the braking force. Based on the mass belt model, an optimization model of train operation is built with these parameters as decision variables. The objective function is to minimize the energy consumption and the penalty on the running time delays for the observed rail interval. A simulated annealing algorithm is designed to solve the model, which adopts synergic adjustment of multiple parameters based on the influence of the running time with variation of each parameter. A numerical example of Guangzhou Metro Line 8 is adopted to test the method. The results show that the maximum operation speed has a decisive influence on the optimal train operation strategy, interval running time, and energy consumption; the train traction has a direct effect on energy consumption; the train braking force has multiple optimal solutions; moreover, the energy-saving strategy has a significant effect on energy saving in a longer running time.