The disorderly charging of electric vehicles (EVs) increases the peak-valley difference of load and users’ charging costs, and the traditional orderly charging strategy requires users to input information manually. This article proposes an orderly charging strategy for electric vehicles based on fuzzy logic and particle swarm optimization algorithm. By comprehensively considering the initial SOC and daily average driving mileage of electric vehicles, a fuzzy logic model is used to determine whether the EV participates in orderly charging optimization, without the need for vehicle owners to input information. Aiming to minimize the peak-valley difference of the load curve and the total charging cost of the user, the charging plan is optimized through particle swarm optimization algorithm. Compared with the disorderly charging calculated by Monte Carlo algorithm, the case analysis shows that the proposed strategy can effectively reduce the peak-valley difference and users’ charging costs.