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dc.contributor.advisorZakkam, Daniel Sukumar
dc.contributor.authorBajpai, Anuj
dc.date.accessioned2020.-09-22T13:52:29Z
dc.date.available2023-02-17T13:52:29Z
dc.date.issued2020
dc.identifier.citationBajpai, Anuj (2020). Energy management control strategy modeling for a mild hybrid electric vehicle. Dhirubhai Ambani Institute of Information and Communication Technology. 36 p. (Acc.No: T00889)
dc.identifier.urihttp://drsr.daiict.ac.in//handle/123456789/971
dc.description.abstractFor years the automotive industry has been shifting towards hybridization and electrification of conventional powertrains due to increase in fossil fuel cost and environmental impact due heavy emission of Green House Gases (GHG) and various pollutants into atmosphere by combustion engine powered vehicles. Hybrid Electric Vehicles (HEV) have proved to achieve superior fuel economy and reduced emissions. In this work a strategy based on fuzzy logic control (FLC) is developed for torque distribution between internal combustion engine (ICE), as a major source of energy and a motor which uses electrical energy from battery. It will optimize the power output, fuel economy and also meets vehicle's operational requirements. In addition, Battery State of Charge (SOC) is kept within a suitable range to guarantee the life expectancy of the battery. Along with this a regenerative braking energy recovery control strategy is also developed. By analyzing the characteristic and the influence factors of the regenerative braking, the fuzzy logic controller is established. Under assurance of braking safety and stability, the strategy distributes regenerative braking force and frictional braking force reasonably during braking, to make use of regenerative braking characteristic of motor as much as possible, so that much more kinetic energy can be converted into electric energy and stored in the battery. A hybrid controller is also developed using stateflow which is the key component of the mild-hybrid vehicle which manages combustion engine, electric motor and clutches based on the torque requirements. MATLAB Simulink and Stateflow environments have been used to model and run the simulations.
dc.subjectSOC optimization
dc.subjectfuel efficiency
dc.subjectFuzzy logic control
dc.subjectMatlab/simulink
dc.subjecthybrid control logic
dc.classification.ddc629.2293 BAJ
dc.titleEnergy management control strategy modeling for a mild hybrid electric vehicle
dc.typeDissertation
dc.degreeM. Tech
dc.student.id201811064
dc.accession.numberT00889


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