Convex Optimization for Fuel Cell Hybrid Trains: Speed, Energy Management System, and Battery Thermals

We optimize the operation of a fuel cell hybrid train using convex optimization. The main objective is to minimize hydrogen fuel consumption while achieving target journey duration. This is achieved by jointly optimizing train speed and the energy management system. Moreover, a battery thermal model and thermal constraints are integrated into the optimization problem to improve battery thermal management. The proposed joint optimization approach outperforms a conventional driving strategy both in terms of fuel consumption and battery thermal management. The joint approach consumes around less 10% fuel because its speed profile exploits kinetic energy recovery more effectively. Moreover, the joint approach requires 12% less cooling because its acceleration profile leads to less battery heating. Lastly, it was noticed that the joint approach scheduled battery cooling commands exclusively around periods of regenerative braking. This form of auxiliary load scheduling is believed to lead to marginally improved efficiency and battery thermal management.