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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

A control strategy for the power system of a hybrid vehicle

Furrutter, Marco Klaus 24 October 2012 (has links)
M.Ing. / The increase in awareness of the environmental problems resulting from emissions released from vehicles have forced governments and car manufactures to invest more time in to the designing a vehicle that is an alternative to petrol driven vehicles. This dissertation aims to introduce a control strategy to manage the flow of energy of different power sources that may be found on a vehicle. Hybrid vehicles are a possible solution to reducing carbon emissions that play a part in global warming. In this dissertation, di erent hybrid vehicles are de ned and their components discussed in detail. The possibility of more than one energy source to power the vehicle introduces more exibility in terms of the drivetrain but this increases the complexity of the energy control management. The goal is to optimize the energy control management to reduce fuel consumption and therefore reduce emissions. Operating procedures for the various hybrid con gurations are discussed. Simulations of the Energy Management System of the hybrid electric vehicle are used to develop the control optimization algorithm. Various control optimization procedures are discussed. Satisfactory results from the simulations allow the implementation of the hybrid onto a platform entered into the South African Solar Challenge 2010, which covered a distance of 4000 km. The Energy Management system selected for the parallel hybrid electric vehicle demonstrated fuel savings, which meant a reduction in emissions, which is the goal of any hybrid vehicle. Further investigations include more intelligent controllers to adjust the parameters of the energy management controller to allow for adaptation to various driving conditions, e.g. urban and motorway driving.

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