  We optimize the operation of a fuel cell hybrid train using convex
optimization. The main objective is to minimize hydrogen fuel consumption for a
target journey time while considering battery thermal constraints. The state
trajectories: train speed, energy management system, and battery temperature,
are all optimized concurrently within a single optimization problem. A novel
thermal model is proposed in order to include battery temperature yet maintain
formulation convexity. Simulations show fuel savings and better thermal
management when temperature is optimized concurrently with the other states
rather than sequentially -- separately afterwards. The fuel reduction is caused
by reduced cooling effort which is motivated by the formulation's awareness of
active cooling energy consumption. The benefit is more pronounced for warmer
ambient temperatures that require more cooling.
