As battery technology matures and new energy sources advance, electric vehicles (EVs) are increasingly integral to future power grids. Aggregating and dispatching EVs for frequency regulation has emerged as a research focus. This study examines the subjective willingness and objective travel behaviors of EV clusters participating in frequency regulation services, quantitatively assessing their frequency modulation capacity. A tri-objective optimization model based on credibility theory is proposed to analyze aggregator bidding strategies in the electricity day-ahead market (DAM), incorporating a reformulated revenue framework. The non-dominated sorting genetic algorithm II (NSGA-II) is used to derive Pareto-optimal solutions. Simulation results indicate that the proposed model enhances the economic feasibility and stability of aggregator participation in frequency regulation services and provides diverse bidding strategy options.