With the rapid growth of electric vehicles, insufficient charging stations, uneven distribution, and reliability issues have become key factors affecting usage experience and operational efficiency. Considering potential disruption risks during the charging station location process, this paper develops a multi-objective optimization model for reliable electric vehicle charging station location. The model aims to achieve coordinated optimization of economy, efficiency, and accessibility by minimizing the total system cost, maximizing user temporal satisfaction, and improving the average station accessibility. NSGA-III is adopted to solve the model, yielding a Pareto-optimal solution set that reflects the trade-offs among system cost, user satisfaction, and accessibility. Experiments are conducted based on the road network and POI data within the Third Ring Road of Chengdu to validate the model’s applicability in real-world scenarios. The algorithm’s performance is evaluated using hypervolume, inverted generational distance, uniformity, and diversity metrics, and compared with that of NSGA-II. Additionally, a sensitivity analysis is performed on the disruption probability and the proportion of emergency to explore the model’s stability and adaptability. The results indicate that the proposed model and method effectively address disruption risks in charging station location, enhance the resilience of the charging network, and provide a scientific reference for reliable charging station location optimization.