Driving Strategy Optimization and Field Test on an Urban Rail Transit System

Abstract

The reduction of train energy consumption is becoming more important due to increasing worldwide environmental concerns. This paper presents a driving strategy optimization study and field test results on an urban rail transit system. A genetic algorithm based optimization method has been developed specifically for this purpose. In order to identify and evaluate the practicability and performance of the optimization results, a field test has been carried out on Guangzhou Metro Line No. 7. A driver training study has been developed to help drivers to implement the energy saving features of the optimization. The field test results show that by applying the optimal driver strategy the train traction energy consumption can be significantly reduced within the given journey time constant, proving the developed optimization method is practicable and effective.