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Writer's pictureS+M.ai

Optimization of transit bus fleet's life cycle assessment impacts with alternative fuel options


The goal of this study is to find an optimal bus fleet combination for different driving conditions to minimize life cycle cost, greenhouse gas emissions, and conventional air pollutant emission impacts. For this purpose, a Multi-Objective Linear Programming approach is used to select the optimum bus fleet combinations. Given different weight scenarios, this method could effectively provide solutions for decision makers with various budget constraints or emission reduction requirements. The results indicate that in heavily congested driving cycles such as the Manhattan area, the battery electric bus is the dominant vehicle type, while the hybrid bus has more balanced performances in most scenarios because of its lower initial investment compared to battery electric buses. Petroleum powered buses have seldom been selected by the model. The trade-off analysis shows that the overall greenhouse gas impact performance is sensitive to the life cycle cost after certain points, which could provide valuable information for the bus fleet combination planning.



Fig.1: Multi Objective Linear Programming (MOLP) Results for MAN, CBD, and OCTA driving cycles under different objective weighting scenarios.

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