Type of Document Master's Thesis Author Del Barga, Christopher Author's Email Address email@example.com URN etd-06112015-230304 Title Design and Optimization of a Mobile Hybrid Electric System to Reduce Fuel Consumption Degree Master of Science Department Mechanical Engineering Advisory Committee
Advisor Name Title Dr. Alfred Wicks Committee Chair Dr. John Bird Committee Member Dr. Pablo Tarazaga Committee Member Keywords
- hybrid energy
- Off-grid power systems
- fuel efficiency
Date of Defense 2015-05-29 Availability unrestricted AbstractThe high costs and high risks of transporting fuel to combat zones make fuel conservation a dire need for the US military. A towable hybrid electric system can help relieve these issues by replacing less fuel efficient standalone diesel generators to deliver power to company encampments. Currently, standalone generators are sized to meet peak demand, even though peak demand only occurs during short intervals each day. The average daily demand is much less, meaning generators will be running inefficiently most of the day.
In this thesis, a simulation is created to help determine an optimal system design given a load profile, size and weight constraints, and relocation schedule. This simulation is validated using test data from an existing system. After validation, many hybrid energy components are considered for use in the simulation. The combination of components that yields the lowest fuel consumption is used for the optimal design of the system. After determining the optimal design, a few design parameters are varied to analyze their effect on fuel consumption.
The model presented in this thesis agrees with the test data to 7% of the measured fuel consumption. Sixteen system configurations are run through the simulation and their results are compared. The most fuel efficient system is the system that uses a 3.8kW diesel engine generator with a 307.2V, maximum capacity LiFeMgPO4 battery pack. This system is estimated to consume 21% less fuel than a stand-alone generator, and up to 28% less when solar power is available.
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