Optimal charging and speed control of electric buses based on traffic flow predictions

This paper deals with electric and autonomous buses that have to follow a given route in extra-urban roads, with a given timetable for reaching the stops. All the stops are provided with a charging infrastructure allowing to charge the batteries when buses are present at stops. We propose a real-time control algorithm which computes the optimal speed of buses along the route and the charging times at stops. Since the trajectories of buses are affected by the traffic conditions, the proposed control algorithm is based on a prediction module in which a traffic model is run periodically to predict the traffic state in the road network. Thanks to this model, the average speed of the traffic flow in the different road sections is predicted and used as upper bound of the bus speed. The proposed control algorithm is based on the solution of an optimal control problem in which the cost function jointly minimizes the deviations of the stopping times from those defined in the timetable and the deviations of the final energy of the bus batteries from a desired value. Simulation results based on a real case show the trade-off between these objectives.

I. Introduction

The protection of the environment and the health of the planet represent the challenges that the present human gener-ations are called to face. Every year we witness an increase in the temperature of the atmosphere and in the pollution of the environment caused by human activities. Among these, road transport is one of the main sources of environmental pollution [1], and it is unanimously recognized that urgent actions are needed to reduce its impact on the environment. Governments and institutions all over the world are trying to counteract climate warming by setting new targets to be achieved in the next decades. The European Commission, for instance, has set the reduction of 90% of transport emissions as one of its climate goals to be met by 2050 [2], posing in this way a huge challenge for the entire community.