Chengxiang(Tony) Zhuge B.Eng. Ph.D.
Investigating the Potential Expansion and Impact of the Electric Vehicle Market with an Agent-based Integrated Framework: A Case Study of Beijing, China
Chengxiang Zhuge got his first degree in Traffic and Transportation at Beijing Jiaotong University in 2010. His undergraduate thesis focused on developing a platform for evaluating the guidance performance of VMS (Variable Message Sign). He was in his first Ph.D. programme at Beijing Jiaotong University from 2010 to 2014, and his research was on "Dynamic Evolution Mechanism of Urban Transport-Land Use Based on Self-Organizing Theory". During the programme, he got the scholarship from Beijing Jiaotong University and studied as a visiting student at University of Washington for about 10 months. He began his second Ph.D. programme at University of Cambridge in 2014, and he is studying how the Electric Vehicle market expands and how the expansion impacts the charging/refuelling infrastructures, power grid system, environment, etc.
- Ph.D. Candidate, Department of Geography, University of Cambridge. (2014-present)
- Ph.D. in Traffic and Transportation Management and Planning, Beijing Jiaotong University, Beijing, China (2010-2014)
- B.Eng. in Traffic and Transportation, Beijing Jiaotong University, Beijing, China (2006-2010)
Chengxiang' Ph.D. project focuses on the potential expansion and impacts of EV Market from the micro-scale. As a strong dynamic interaction between EV market and other relevant fields exists, an integrated framework is being developed to systematically investigate the potential expansion and impact of the EV market. The integrated framework is based on an agent-based dynamic evolution of land use-transport model (SelfSim). It incorporates the EV market, transport, population, land use, power grid and the natural environment, and is aimed at revealing the relationships and simulating the interactions among them.
The potential expansion of EV market involves various factors. In this project, four stakeholders, including consumers, governors, automakers and fuel suppliers, will be taken into account, and their interactions will be simulated. More specifically, the emphasis will be placed on simulating the EV purchase behaviour of consumers, and how the characteristics, preferences, social network and EV driving experience, together with various EVs policies, affect purchase decisions. Model structure will be based on stakeholder interviews and consumer surveys, along with available third party data on household daily activity patterns.
The expansion of EV market may have several impacts. In this project, the potential impacts on charging infrastructure deployment, power grid system and environment will be explicitly analysed. With respect to the charging infrastructure deployment, the model will investigate locations of the charging infrastructure with the objective of minimizing the total charging utility of all drivers. For the power grid system, three management scenarios will be tested, namely "dumb" grid, tariff grid and smart grid, respectively. In addition, the interactions among the charging infrastructure locations, power grid system, and the travel behaviour of drivers will be simulated. Together these will allow estimation of the impact on the environment, through the GRRET (Greenhouse gases, Regulated Emissions, and Energy use in Transportation) model, connected to the travel demand model (EVSim) to calculate the Greenhouse Gas(GHG) and Black Carbon emissions from a spatial and temporal view.
The capital of China, Beijing, will be used as a case study. The proposed integrated framework will first be tested through sensitivity analysis and the historical validation, and then be applied to predict the potential expansion and impact of EV market in a variety of scenarios. The consequences may be useful for stakeholders, such as governments and manufacturers, as an aid to decision making. Further, they will contribute to understanding the possible mitigation of energy scarcity and of some of the drivers of climate change that could be provided by electrification of transport.
- Zhuge, C.X., Shao, C.F., Gao, J., Meng, M. and Xu, W.Y., (2014),"An Initial Implementation of Multi-agent Simulation of Travel Behavior for a Medium-Sized City in China", Mathematical Problems in Engineering.
- Zhuge, C.X., Shao, C.F., Gao, J., Meng, M. and Ji, X., (2014), "Study on Evolution Prospect and Structure of Urban Transportation and Land Use System", Journal of Transportation Systems Engineering and Information Technology.
- Li X., Zhuge, C.X., Zhang, X., Gao,J.and Zhang, H.,(2014), "Multi-objective Optimization Model of Residential Spatial Distribution", Mathematical Problems in Engineering.
- Zhuge, C.X., Shao, C.F., Zheng, C.Q., Liang, Q. and Gao, J., (2013), "Evaluation System for Evaluating the VMS Guidance Effect", Journal of Software.
- Zhuge,C.X., Shao, C.F., Li, X. and Meng, M.,(2012), "Commuter's Choice Behavior of Travel Time and Travel Mode", Journal of Transportation Systems Engineering and Information Technology.
- Dong, C.J., Shao, C.F. and Zhuge, C.X., (2012), "Short-term Traffic Flow Prediction for multi traffic states on urban expressway network", Acta Physica Sinica.
- Gao, J., Zhao, P., Zhuge, C.X. and Zhang, H., (2012),"Research on Public Transit Network Hierarchy Based on Residential Transit Trip Distance", Discrete Dynamics in Nature and Society.