Maximizing Regenerative Braking Energy in Railway Vehicle of Addis Ababa

dc.contributor.advisorMengesha, Mamo (PhD)
dc.contributor.authorYared, Tadesse
dc.date.accessioned2018-12-14T10:51:40Z
dc.date.accessioned2023-11-28T14:20:30Z
dc.date.available2018-12-14T10:51:40Z
dc.date.available2023-11-28T14:20:30Z
dc.date.issued2017-12
dc.description.abstractIn this thesis, the problem of maximizing regenerative braking energy is addressed to reduce electrical power consumption of Addis Ababa Light Rail Transit vehicle. The optimization problem is solved using Improved Arti cial Bee Colony(IABC) algorithm in case of Ayat-2 to Ayat-1, Mazoria to Chemical Corporation and Meskel Square-1 to Legehar stations and vice versa. The rail road has relatively smaller gradient from Ayat-2 to Ayat-1 station while steepest slope exist between Meskel Square-1 and Legehar Stations. After several simulation tests, the regenerative braking speed pro le that satis es di erent constrains of railway vehicle is recommended for selected stations. As seen from simulation result, IABC based optimization can restore 25:6383% to 29:4083% total kinetic energy of vehicle in case of Meskel Square-1 to Legehar (2:767 gradient) and Ayat-2 to Ayat-1 (0:00905 o gradient) uphill drive braking operation respectively. Signi cant amount of electrical energy is restored using IABC optimization algorithm as compared to constant braking rate operation. Particularly, 1:1984MJ electrical energy is regenerated using proposed method while 0:6115MJ is recovered using constant braking rate in case of Meskel Square-1 to Legehar uphill drive braking. In downhill drive braking operation, the increase in regenerative braking energy is observed since the tangential component of gravitational force which is exerted on vehicle acts in direction of velocity. Numerically, 3:3669MJ energy is regenerated using IABC algorithm while 3:1074MJ energy is restored by constant braking rate operation in case of 2:767 o o downhill gradient.en_US
dc.identifier.urihttp://etd.aau.edu.et/handle/12345678/15116
dc.language.isoen_USen_US
dc.publisherAAUen_US
dc.subjectRegenerative brakingen_US
dc.subjectArtifcial bee colony algorithmen_US
dc.subjectAddis Ababa light trainen_US
dc.titleMaximizing Regenerative Braking Energy in Railway Vehicle of Addis Ababaen_US
dc.typeThesisen_US

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