Intelligent control of the charging process is crucial to reduce energy costs, smooth grid loads and extend battery lifetime. Charging algorithms dynamically distribute energy, shift charging windows and prioritise vehicles depending on operational needs. This enables peak-shaving: grid load peaks are avoided by reducing or shifting charging power. At the same time, the algorithms take into account battery state, temperature and available layover time to prevent overload and protect the battery. Simulations over a full timetable year demonstrate how algorithms respond to disruptions, special services or short-term bottlenecks. In addition, dynamic tariff price signals can be integrated, ensuring fleets charge preferentially when energy costs are low. The result: lower infrastructure costs, longer battery life and higher fleet availability.