GeneticBee: A theoretic and evolutionary formulation for the energy efficiency problem of urban trains

The electric motors of the trains in a railway system are powered by electricity, and the energy demand is high. In addition, rail-based transport systems continue to grow, and therefore, solutions are currently sought to optimise energy consumption. This article presents an analysis of electric multiple units (EMUs) of the Companhia Brasileira de Trens Urbanos - Brazilian Urban Train Company (CBTU) - Recife, Brazil and the use of electric power provided by the engines during acceleration and braking. To this end, a general model is proposed that encompasses an analysis of the speed and driving profiles, herein termed speed profile optimisation. This model is validated by empirical simulations with the aid of MATLAB software and the implementation of a genetic algorithm of artificial intelligence using the Java programming language. We intend to demonstrate that by controlling the train speed profiles and considering some limits, restrictions and parameters, a decrease in energy consumption in the analysed stations will follow, which will promote more sustainable transport and cost savings.