Decision Method of Electric Change Behavior of Electric Change Vehicle Based on Ant Colony Algorithm

Electric vehicles boast the merits of emitting no pollutants, achieving high energy efficiency, and possessing a straightforward design, but there are still problems such as short battery life and long charging time. To mitigate the expense incurred by electric vehicle owners for changing and minimize the influence of changing stations on the power distribution network, this paper combined the three influential factors of electric vehicle driving distance, total travel time and attraction of the replacement station, established the relevant objective function, calculated the relevant weight coefficient using the analytic hierarchy process. Subsequently, the ant colony algorithm was employed to devise a specific replacement route based on the computation outcomes. Based on this, the power change path planning model is constructed. Lastly, the efficacy of the proposed power charging route planning model is demonstrated through an illustrative case study of an urban regional transportation network. The outcome of the example validates that the model is capable of catering to the diverse requirements of various users.