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    Systems Integration, Modeling, and Validation of a Fuel Cell Hybrid Electric Vehicle

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    Date
    2000-05-04
    Author
    Ogburn, Michael James
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    Abstract
    The goals of the research documented in this thesis were the design, construction, modeling, and validation of a fuel cell hybrid electric vehicle based a conversion of a five-passenger production sedan. Over 60 engineering students working together as the Hybrid Electric Vehicle Team of Virginia Tech (HEVT), integrated a proton exchange membrane fuel cell system into a series hybrid electric vehicle. This design produced an efficient and truly zero-emission vehicle. This 1997 Chevrolet Lumina sedan, renamed ANIMUL H2, carries this advanced powertrain, using an efficient AC induction drivetrain, regenerative braking, compressed hydrogen fuel storage, and an advanced lead-acid battery pack for peak power load leveling. The vehicle weighed 2000 kg (4400 lb) and achieved a combined city/highway fuel economy of 9L/100 km or 26 mpgge (miles per gallon gasoline equivalent, charge depleting, state of charge corrected). A model of the vehicle was developed using ADVISOR, an Advanced Vehicle Simulator that tracks energy flow and fuel usage within the vehicle drivetrain and energy conversion components. The vehicle was tested using the Environmental Protection Agency city and highway driving cycles to provide data for validation of the model. Vehicle data and model results show good correlation at all levels and show that ADVISOR has the capability to model fuel cell hybrid electric vehicles. To make techniques proven by this work more versatile for real world application, VT worked with engineers at the National Renewable Energy Laboratory to develop a 'generic' version of this fuel cell system model that was released to the public in ADVISOR 2.2. This generic model correlates well to test data and incorporates both fuel cell stack and subsystem models. This feature allowed HEVT to predict the benefits of load following subsystem control, showing a 40% fuel economy improvement.
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    http://hdl.handle.net/10919/32124
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    • Masters Theses [21530]

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