Optimization analysis on the energy saving control for trains with adaptive genetic algorithm

In order to improve the train energy-saving control strategy, combine the existing energy-saving operation experiences and idea of typical subinterval, adaptive genetic algorithm is adopted to seek for the conversion points of different working conditions making energy consumption minimum under the circumstance of fulfilling the precondition of security, punctuality and driving comfort as well. The calculation methods of train braking stop curve and security protection curve are introduced. Adjust train running curve to enhance the proportion of feasible solutions and accelerate the algorithm iterative process. The chromosomes and operator of genetic algorithm as well as the fitness function are described in detail; the application of adaptive mechanism strengthens the global searching capability of genetic algorithm. Wuhan-Guangzhou line is chosen as simulation verifications. And the simulation result shows that this energy- saving control algorithm is effective.