Given that the electric vehicle’s power consumption rate is affected by the load, especially under dynamic load conditions, its power consumption rate and incomplete charging strategy have become the focus of research. To improve the operational efficiency of electric vehicles in logistics tasks, an innovative distribution route planning method is proposed. The method integrates multiple charging strategies slow charging followed by fast charging and direct fast charging in daily scheduling decisions. In addition, practical constraints such as real-time electricity prices, vehicle current power, load limitations, and a unilateral distribution time window are incorporated. Not only conventional factors such as battery loss, charging station service time, and time-sharing tariffs are considered, but also charging and discharging management between the vehicle and the grid is incorporated. In this paper, a mathematical optimization model is constructed with the objective of minimizing the sum of fixed costs, transport costs, power consumption costs, charging costs, penalty costs, slow charging and discharging costs, and battery depletion costs, and an improved genetic algorithm is used to solve this complex model. Simulation experiment results show that the proposed priority slow charging and incomplete charging strategy not only significantly reduces charging cost and battery loss but also significantly improves the economic performance of logistics and distribution, maximizes the economic benefits of logistics and distribution, and taps the potential of deep interaction between transportation and energy. It provides technical support and decision-making reference for the application of electric vehicles in logistics.