Controlling the train car’s center of gravity (COG) position based on train load levelling

The dynamic center of gravity (COG) shift of a train car affects the train’s running stability. Loss of running stability results in derailments and overturns. This study proposes a novel ticketing algorithm as an effort to prevent derailment and overturn. The algorithm limits the freedom for passengers in seat choosing. Instead, the passengers will be offered recommended seat positions that account for a minimum COG shift. The novel ticketing algorithm implementation was evaluated in comparison to the existing ticketing algorithm and safety-as-priority (SAP) algorithm. Each algorithm implementation was evaluated and compared analytically through a numerical simulation approach. The dynamic COG shift on a few loading scenarios was evaluated using COG loading shift and COG shift. COG shift evaluation shows novel algorithms have smaller shifts than existing algorithms but still bigger than SAP algorithm. The loading shift showing the loss of balance during iterative load addition and load reduction has been reduced through SAP and novel algorithm implementation. In the tested loading scenarios, the Existing algorithm shows (x=2.60x10^-5,z=3.41x10^-5,y=6.17x10^-5)% shift while SAP shows (x=1.28x10^-5,-z=-2.40x10^-5,y=2.36x10^-5)% and novel algorithm shows (x=1.60x10^-5,-z=3.07x10^-5,y=5.34x10^-5)% Cog shift. The result suggests that the novel algorithm has made it possible to maintain train running stability while considering the passenger needs. Hence, the running safety of a train can be altered without sacrificing passenger satisfaction.