Due to the high risk of energy shortage of electric vehicles(EVs)on the roads

it is urgent to propose a charging route planning method for EVs which is conducive to alleviating EV users' travel anxiety. By selecting the driving condition characteristic parameters which can accurately reflect the driving characteristics of EV users on the actual roads

this paper analyzes the correlation between the characteristic parameters and the energy consumption as well as the strength of correlation between characteristics. The principal component analysis method is used to reduce the dimension of characteristics

and then the information entropy fuzzy clustering method is used to classify the driving conditions. Thus

the dynamic energy consumption model for EV driving is established. Based on the energy consumption model and the constraint of route selection and battery residual capacity

the charging route planning model for EV is developed with the objective of minimizing the sum of weighted EV users' travel distance

travel time and charging price. Finally

taking the actual traffic network area(18 km×18 km)as an example to verify the performance of the proposed method. The effect of the real-time energy consumption on the charging route planning is analyzed

and the effect of different optimization objectives on the charging route optimization results is also verified.