Train drivers have different driving styles which require different amount of energy. These different styles are difficult to analyze to define an energy-efficient driving strategy. We present a reinforcement learning approach that learns to drive long-distance trains more energy-efficient while maintaining punctuality and safety. The method was used by DB Fernverkehr on a test-drive and showed an unexpected driving strategy that was very energy-efficient and material friendly.