Energy Saving Strategy of Train Operation using Artificial Intelligence Technique
An artificial intelligence approach is proposed to investigate the optimum train operation strategy for energy saving. The train operation patterns of several train drivers are investigated along the Kyung-bu railway in Korea. The investigation shows that energy consumption for train operation may differ depending on the drivers. This energy consumption difference is increased as the Korea Railroad Corporation introduced a new-type electric locomotive which uses generative braking in addition to conventional air braking. It is investigated that the expert drivers can save 46 percents of energy consumption while keeping train schedule, compared with that of the inexperienced drivers. A rulebase is constructed from the train operation patterns and the know-how of veteran drivers, which can assist train drivers to make energy saving operation while keeping train schedule. The proposed rulebase system can be embedded into the train control and monitoring system(TCMS) to achieve optimal operation of train by assisting drivers.
electric locomotive electric railway energy saving train operation rulebase
Iikwon Seo Kyuhyoung Choi
国际会议
The International Conference on Electrical Engineering 2009(2009 电机工程国际会议)
沈阳
英文
1-4
2009-07-05（万方平台首次上网日期，不代表论文的发表时间）