In order to guide electric vehicle users to participate in orderly charging, this paper proposes an internal evolutionary game model of the electric vehicle group based on multi-strategy fusion. Firstly, an evolutionary game model including three strategies: Charge-only, charge-discharge, and peak-time-avoiding charging was designed. A dynamic threshold mechanism was introduced, combined with the empirical weighted attraction rule and the Fermi rule, to achieve multi-strategy fusion and update. By setting discharge incentives and charging subsidies, users′ enthusiasm for choosing charging and discharging strategies has been enhanced. Secondly, this paper establishes a game model within the electric vehicle group, analyzes the benefits of users under different strategies, and verifies the validity of the model through simulation. Finally, the multi-strategy fusion update rule method was adopted. Through the dynamic threshold mechanism, combined with the long-term learning ability of EWA and the shortterm response advantage of Fermi, the stability and adaptability of strategy adjustment were significantly improved. The simulation results show that this model can accurately simulate the decision-making behavior of users, effectively improve the efficiency of power distribution, and reduce the peak-valley difference of the power grid by approximately 36.7%. Compared with the update rule of a single strategy, the multi-strategy fusion method shows significant advantages in the stability and adaptability of strategy adjustment. This article provides theoretical support and reference methods for power grid operators to formulate incentive measures and for electric vehicles to participate in vehicle-to-grid interaction.