The speed profile of a train plays an important role in energy consumption and resulting costs. The industrial objective of this work is thus to develop a method to reduce the energy consumed by a train over a journey by playing on the driver commands (traction and braking forces) while respecting punctuality constraints. First, a rigid body approach (Lagrangian formalism) is introduced to characterise the dynamics of the train. In particular, the aerodynamic (including the wind effect), traction, and braking forces are taken into account, and a special attention is paid to the vertical and lateral characteristics of the track as they play a key role in the train dynamics. Second, a model for energy consumption and recovery (thanks to dynamic braking) is introduced. Experimental measurements of a high-speed line are then used to estimate the parameters on which the two previous models are based and to validate their predictive capacities. The optimisation problem under constraints is finally solved using an evolutionary algorithm where the constraints are implemented using an augmented Lagrangian formalism. The performance of the proposed method in terms of speed optimisation and energy consumption reduction is compared to measurements associated with commercial trains.

火车的速度曲线在能源消耗和由此产生的成本中起着重要作用。因此，这项工作的工业目标是开发一种方法，通过在遵守准点限制的同时执行驾驶员命令（牵引力和制动力）来减少火车在旅途中消耗的能量。首先，引入刚体方法（拉格朗日形式主义）来表征火车的动力学。特别是空气动力学（包括风效应）、牵引力和制动力都被考虑在内，并特别注意轨道的垂直和横向特性，因为它们在列车动力学中起着关键作用。其次，介绍了一种能源消耗和回收模型（由于动态制动）。然后使用高速线路的实验测量来估计前面两个模型所基于的参数并验证它们的预测能力。约束下的优化问题最终使用进化算法来解决，其中约束是使用增强的拉格朗日形式实现的。所提出的方法在速度优化和能耗降低方面的性能与商业列车相关的测量结果进行了比较。