Investigation on Optimal Control of Hybrid Vehicle Energy Management System Based on Multi-source Traffic Information

Abstract

Energy shortage and air pollution is an important problem facing the world. One of the effective ways to mitigate it is to develop hybrid vehicles and other energy resource vehicles. However, traffic decision information needed by hybrid vehicle energy management system has become the major bottleneck to restricting hybrid vehicle's popularization, which shows the characteristics of multi-source, time varying and fuzzy. Hybrid vehicle Energy management problem using multi- source traffic information cycle of s is taken as the aim, numerical simulations and laboratory tests are the two methods to solve it in this project. First, dynamic extraction mechanism of multi-source traffic information, such as dynamic link travel time and vehicle path are studied based on support vector regression theory and quantum ant colony algorithm. And then, Markov theory is adopted to study the system level energy optimization modeling of hybrid vehicle energy management system based on multi-source traffic information. Finally, using multi-source traffic information, quantitative control model of energy optimization performance is constructed .This topic is aim to reveal the energy optimal law in hybrid vehicle energy management system using multi-source traffic information, which would lay the theoretical and technical basis for developing new intelligent energy management system suitable for the conditions of multi-source traffic information.