Electric Vehicle Travel Chain Model and Case Analysis Based on Time and Space Characteristics

Aiming at the travel model of electric vehicle, a travel chain method is proposed to describe the daily travel rule of electric vehicle users. The characteristics of the time chain are fitted by the mixture Gaussian distribution and the normal distribution, and the parameters are estimated by the maximum expectation algorithm and the maximum likelihood estimation. The regional transfer probability model of the electric vehicle is established on the space chain to analyze the driving path and the remaining electricity of the electric vehicle under the conditions of charging and not charging. In this paper, Freud algorithm is used to find the shortest path between the starting point and the end point of EV in the network. The actual case is selected for analysis and calculation. The calculation results show the effectiveness and practicability of the established model and algorithm.