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Optimization Tool for Transit Bus Fleet Management

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Optimization Tool for Transit Bus Fleet Management Graduate Theses, Dissertations, and Problem Reports 2012 Optimization tool for transit bus fleet management Feng Zhen West Virginia University Follow this and additional works at: https://researchrepository.wvu.edu/etd Recommended Citation Zhen, Feng, "Optimization tool for transit bus fleet management" (2012). Graduate Theses, Dissertations, and Problem Reports. 600. https://researchrepository.wvu.edu/etd/600 This Dissertation is protected by copyright and/or related rights. It has been brought to you by the The Research Repository @ WVU with permission from the rights-holder(s). You are free to use this Dissertation in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you must obtain permission from the rights-holder(s) directly, unless additional rights are indicated by a Creative Commons license in the record and/ or on the work itself. This Dissertation has been accepted for inclusion in WVU Graduate Theses, Dissertations, and Problem Reports collection by an authorized administrator of The Research Repository @ WVU. For more information, please contact [email protected]. OPTIMIZATION TOOL FOR TRANSIT BUS FLEET MANAGEMENT by Feng Zhen Dissertation submitted to the College of Engineering and Mineral Resources at West Virginia University in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Mechanical Engineering Approved by Nigel N. Clark, Ph.D., Committee Chairperson W. Scott Wayne, Ph.D. Hailin Li, Ph.D. Benjamin C. Shade, Ph.D. Roy S. Nutter, Jr., Ph.D. Department of Mechanical and Aerospace Engineering Morgantown, West Virginia 2012 Keywords: Transit Bus Operation, Cost Evaluation, Greenhouse Gas Emissions, Operation Optimization, Genetic Algorithm Copyright 2012 Feng Zhen ABSTRACT OPTIMIZATION TOOL FOR TRANSIT BUS FLEET Management By Feng Zhen Transit agencies face the challenge of being environmentally-friendly, while maintaining cost-effective operation. Many studies have focused on investigating new bus technologies to reduce emissions and cost. However, they ignored the potential environmental and economic gain by improving the fitness and harmony between individual buses and routes in fleets. This dissertation provided, for the first time, a tool for fleet operator to intelligently dispatch buses and select new technologies that are tailored to their needs and business. One key element in this tool is a bus life cycle cost model that can simulate and predict every capital and operational cost category for different bus technologies. The cost model was funded by Transportation Research Board and developed in Transit Cooperative Research Program (TCRP) C-15 project, the purpose of which was to assess hybrid-electric bus performance in real-world operation. The research team (author as a key member) picked four bus transit agencies among a handful of test sites that were operating hybrid-electric buses and collected 28 month bus operation data at almost all data collection sites. The sophisticated life cycle cost model is the backbone of this tool to calculate cost. The other key element is a green house gas (GHG) emissions model, which was based on the fuel consumption model in the TCRP C-15 project and GREET model generated at Argonn National Laboratory. The GHG model utilizes fuel consumption data to provide tail pipe GHG emissions and well-to-tank GHG emissions for specific fuels and bus propulsion technologies. The last key element is the use of genetic algorithm (GA) as a search and optimization scheme in the fleet management tool. A ranking matrix was developed to rate and compare different dispatch strategies on multiple criteria, which can vary in units or scales. When a fleet has large number of buses (dozens to thousands) on multiple routes, the number of all possible bus dispatch strategies becomes tremendously huge and difficult to explore. The GA uses the evolution theory of “Only the strongest survive” to find the best strategy. The tool shows that optimization objectives dictated dispatch strategies that are successful in specific applications. For example, in a 35-bus fleet examined in this dissertation, the proposed dispatch strategy could reduce fleet well-to-wheels (WTW) GHG emissions up to 364 metric tons of carbon dioxide equivalents, a 17.5% GHG emissions reduction from the initial dispatch strategy. The same dispatch strategy increased $75K in annual operation cost, a 7% increase. However, a different dispatch strategy, found for maximizing cost reduction, could save $90K instead, a 9% reduction in annual operation cost. For the case of reducing operation cost, the operation cost difference between the best and worst dispatch strategy was $220K a year. DEDICATION I dedicate this dissertation work to my family, especially to my sweet wife, Hua Jing. I cannot accomplish this without your endless support. This work is for my precious daughters, Ivy and Elly, the best products we have made. You bring eternal joy to mother and me. I especially appreciate you two kept sticking with your mother all the time. I also dedicate this dissertation to my parents, Zhizhong Zhen and Suzhen Yuan who brought me to science and art fields and required me to pursue academic excellence. I must also thank my parents-in-law, Jingwen Jing and Xiulan Ren for helping us with baby-sitting and taking care of us. iv ACKNOWLEDGEMENTS I want to sincerely thank Professor Nigel Clark for his long-term guidance, support, and patience during my PhD program. He has taught me so much how to do well both in academia and life. My thanks also go to my committee members. I gratefully acknowledge your valuable inputs and helps. The work is an expansion of bus life cycle cost model developed under TCRP Project C-15. The C-15 project was led by West Virginia University (WVU), with major subcontract support from the Transit Resource Center (TRC), and Battelle Memorial Institute (Battelle). TRC contributes significantly on the life cycle cost (LCC) model development. For this doctoral research, I both played a major role in a team executing the C-15 program, and then individually extended the C-15 philosophy to cover whole fleet evaluations and assignments. The C-15 program benefited greatly from the assistance of the managers and staff at six transit agencies (New York City Transit, King County Metro, Washington Metropolitan Area Transit Authority, Long Beach Transit, Dallas Area Rapid Transit, and OC Transpo (Ottawa City, Canada)), and three hybrid drive OEMs (Allison Transmission, BAE SYSTEMS, and ISE Corporation). WMATA also provided the test buses and the test site for emissions testing that provides the emissions data for life cycle emissions modeling. Significant data used in the C-15 program were gathered through a US Department of Energy funded program, conducted by the National Renewable Energy Laboratory (NREL, Golden, Colo.), with support from Battelle. I also gratefully acknowledge the valuable input from the members of the TCRP C-15 Panel, and from TRB program managers Stephan Parker and Larry Goldstein and CAFEE staff who helped operate the Translab and analytic facilities. I highly appreciated that Transportation Research Board (TRB) through the National Academy of Sciences (NAS) grants permission to use the C-15 project material in my dissertation. v TABLE OF CONTENTS ABSTRACT .........................................................................................................................................ii DEDICATION .................................................................................................................................... iv ACKNOWLEDGEMENTS .................................................................................................................... v TABLE OF CONTENTS....................................................................................................................... vi LIST OF FIGURES ............................................................................................................................ viii LIST OF TABLES .............................................................................................................................. xiii ACRONYMS ................................................................................................................................... xvi INTRODUCTION ............................................................................................................................... 1 CHAPTER 1 - LITERATURE RESEARCH .............................................................................................. 4 1.1 Transit Bus Technology ............................................................................................. 4 1.2 Transit Bus Emissions and Fuel Economy ............................................................... 17 1.3 Transit Bus Life Cycle Cost Studies .......................................................................... 50 1.4 Conclusion of Literature Research .......................................................................... 53 CHAPTER 2 - MODEL CREATION .................................................................................................... 54 2.1 Input Module .......................................................................................................... 56 2.2 Calculation Module ................................................................................................. 66 2.3 Optimization Module ...........................................................................................
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