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Migrating towards Using Electric Vehicles in Campus-Proposed Methods for Fleet Optimization

doi: 10.3390/su10020285
Managing a fleet efficiently to address demand within cost constraints is a challenge. Mismatched fleet size and demand can create suboptimal budget allocations and inconvenience users. To address this problem, many studies have been conducted around heterogeneous fleet optimization. That research has not included an examination of different vehicle types with travel distance constraints. This study focuses on optimizing the University of Tennessee (UT) motor pool which has a heterogeneous fleet that includes electric vehicles (EVs) with a travel distance and recharge time constraint. After assessing UT motor pool trip patterns as a case study, a queuing model was used to estimate the maximum number of each vehicle type needed to minimize the expected customer wait time to near zero. The break-even point is used for the optimization model to constrain the minimum number of years that electric vehicles should be operated under the no-subsidy assumption. The results show that the fleet has surplus vehicles. In addition to reducing the number of vehicles, total fleet costs could be minimized by using electric vehicles for all trips less than 100 miles. The models are flexible and can be applied and help fleet managers make decisions about fleet size and EV adoption.
- Department of Civil and Environmental Engineering University of California, Davis United States
- Tennessee State University United States
- Department of Civil and Environmental Engineering University of Minnesota United States
- University of Tennessee at Knoxville United States
- Department of Civil and Environmental Engineering University of California at Berkeley United States
Environmental effects of industries and plants, university motor pool, TJ807-830, TD194-195, Renewable energy sources, Environmental sciences, fleet optimization, fleet size and composition, electric vehicle adoption, queuing theory, GE1-350, fleet optimization; fleet size and composition; electric vehicle adoption; university motor pool; queuing theory
Environmental effects of industries and plants, university motor pool, TJ807-830, TD194-195, Renewable energy sources, Environmental sciences, fleet optimization, fleet size and composition, electric vehicle adoption, queuing theory, GE1-350, fleet optimization; fleet size and composition; electric vehicle adoption; university motor pool; queuing theory
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