列车节能运行目标速度控制优化研究

探讨了城市轨道交通列车节能运行控制问题，提出了一种分段目标速度控制策略，将目标速度的大小、调速范围和里程范围作为控制参量，建立了定时约束下的列车节能运行优化模型.设计了一种双重惩罚机制的实数编码遗传算法求解模型，对列车晚点和非节能方案进行惩罚以提高算法收敛速度.仿真分析表明，该方法得到的目标速度控制方案较好地适应了线路条件，有效地避免了列车在下坡道的制动调速，与启发式算法得到的运行结果相比，案例中不同富裕时分程度下的优化方案平均节能率22.2%.

Target Speed Control Optimization of Train Movement for Saving Energy

The paper studies the problem of urban rail transit train energy-saving operation control, proposes a discrete target speed control strategy, and takes the target speed parameters (velocity values, range of velocity bound and scale of cover mileage) as control variables. Then, an optimization model with timing constraints is established for efficient operation. To solve the model, a real coded genetic algorithm with a double punishment mechanism (DPM) is designed, and the DPM is applied to punish overtime scheme and non-energy-saving scheme so as to improve the convergence rate. The simulation results indicate that, the optimal target speed schemes obtained by this method are well adapted to the line conditions, and effectively avoid the train braking on the lower ramp. Compared with the results obtained by the heuristic algorithm, the average energy- efficient ratio under different rich time is 22.2%.