Energy-aware predictive control for electrified bus networks

For an urban bus network to operate efficiently, conflicting objectives have to be considered: providing sufficient service quality while keeping energy consumption low. The paper focuses on energy efficient operation of bus lines, where bus stops are densely placed, and buses operate frequently with possibility of bunching. The proposed decentralized, bus fleet control solution aims to combine four conflicting goals incorporated into a multi-objective, nonlinear cost function. The multi-objective optimization is solved under a receding horizon model predictive framework. The four conflicting objectives are as follows. One is ensuring periodicity of headways by watching leading and following vehicles i.e. eliminating bus bunching. Equal headways are only a necessary condition for keeping a static, predefined, periodic timetable. The second objective is timetable tracking. A conflicting objective to the former is minimizing passenger waiting time. When more than the expected passengers are waiting for the bus it is desirable to haste the vehicle in order to prevent bunching. The final objective is energy efficiency. To this end, an energy consumption model is formulated considering battery electric vehicles with recuperation during braking. Different weighting strategies are compared and evaluated through realistic scenarios, realized in a validated microscopic traffic simulation environment. Simulation results suggest 3–8% network level energy saving compared to bus holding control while maintaining punctuality and periodicity of buses.