Railway Traffic Regulation Optimization: For Case of AA-LRT

dc.contributor.advisorYalemzewd, Negash (PhD)
dc.contributor.advisorAbi, Abate (Mr.) Co-Advisor
dc.contributor.authorMeron, Muktar
dc.date.accessioned2022-03-17T08:12:36Z
dc.date.accessioned2023-11-04T15:17:40Z
dc.date.available2022-03-17T08:12:36Z
dc.date.available2023-11-04T15:17:40Z
dc.date.issued2016-06
dc.description.abstractThe presented thesis is a study on train energy consumption calculation and optimal train driving strategies for minimum energy consumption and travel time of train by optimizing the train speed profile. Speed profile signifies time spent to complete the given journey and energy consumed for that period. It is desirable to develop optimal speed profiles for the operation of the trains on the AA-LRT network by considering both energy and time as the objectives and by taking into account the effect of every kind of system constraint. So that maximum possible energy savings can be made while at the same time improving network capacity. This study is focus divided into four parts, the first parts discuss about the model for energy consumption calculation for train and second part discussed about optimization tool used for the study called Dynamic Programming (Background Approach) for obtaining optimal speed and control profiles leading to minimum energy consumption. The third part is about simulating the developed algorithm in MATLAB optimization toolbox and finally the fourth part is about traffic controller which control traffic pattern due to disturbances like train delays. The main achievements of this thesis are: a) the development of a model that can be used to calculate energy consumption in trains based on the driving resistances. b) A preliminary algorithm that returns the optimal speed profile for minimum energy consumption by consideration the forces of rolling resistance, the acceleration force and the tractive force needed by the train. The result obtained from simulation helps the driver to attain the required driving performance by driving the train with the respective speed profile.en_US
dc.identifier.urihttp://etd.aau.edu.et/handle/123456789/30648
dc.language.isoen_USen_US
dc.publisherAddis Ababa Universityen_US
dc.subjectOptimal Controlen_US
dc.subjectTrain Energy Consumptionen_US
dc.subjectDynamic Programming (Backward Approach)en_US
dc.subjectSpeed Profileen_US
dc.titleRailway Traffic Regulation Optimization: For Case of AA-LRTen_US
dc.typeThesisen_US

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
Meron Muktar.pdf
Size:
1.32 MB
Format:
Adobe Portable Document Format
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Plain Text
Description: