Integrated Optimization Study of Electric Bus Fleet Transformation

Abstract

With the increasing social demand for sustainable and environmentally friendly transportation, the transformation of public transportation systems has become an important issue. In this paper, three mathematical models are developed to synthesize the ecological consequences, financial models and transition scenarios in the transition from diesel to electric bus fleet. In Problem 1, this paper adopts the Life Cycle Assessment (LCA) method to examine the full life cycle energy consumption of the product. The model comprehensively considers the main raw material production stage, vehicle assembly and distribution stage, vehicle driving stage and vehicle scrapping and dismantling stage, as well as the production stage of all types of energy added to the vehicle driving stage, i.e., the production stage of fuels and electricity, and finally applies Gabi, the life cycle evaluation software developed by PE Germany, to carry out the evaluation of the life cycle energy consumption and greenhouse gas emissions. Finally, the energy-saving potential of pure electric buses reaches 12.69%, and the GHG emission reduction potential reaches 6.05%. The results are applied to the bus fleet in Beijing, and it is calculated that the replacement of the bus fleet with pure electric buses can save 21.87% of energy and bring about a total GHG emission reduction of 60,700 tons. In Problem 2, this paper adopts the research method of life cycle cost (LCC). The model quantifies all the technical, material, human and organizational measures involved in the whole bus system process into cost indicators, and then builds a financial model for the transition of the fleet to a pure electric bus fleet based on the model, which provides a reliable basis for the bus company's decision-making. From a long-term perspective, the public transport company to choose a pure electric bus fleet will be more economically efficient, but need to bear the costly transition to the acquisition of costs. Overall, this paper comprehensively explores the smart bus fleet transformation problem through three complementary models. It provides strong support for decision makers from the perspectives of life cycle cost, financial planning and environmental friendliness. The combined use of these models makes the article more comprehensive and provides useful lessons for future bus fleet transformation.