Based on the theory of vehicle dynamics, this paper first constructs a dynamic model of the cab air suspension system, laying a core theoretical framework for subsequent optimization research. At the level of performance evaluation indicators, the root mean square (RMS) values of the cab’s vertical acceleration, roll acceleration, and pitch acceleration are selected as key parameters. On this basis, an objective function for the damping matching of the cab air suspension system is established, clarifying the optimization direction. Building on this objective function, the paper further takes into account the constraint conditions in the actual operation of the system, using the probability of the cab air suspension system hitting the limit stop as a constraint. Finally, a complete mathematical model for the damping matching of the cab air suspension system is formed, and a genetic algorithm is used to solve this model, ensuring the scientificity and feasibility of the optimization results. To verify the effectiveness of the established model and optimization method, this paper conducts verification based on the aforementioned dynamic simulation model of the cab air suspension system: the frame displacement signals collected under actual random road conditions are used as the model input, and the established mathematical method for damping matching is applied to carry out the optimal matching design of the damping parameters of the cab air suspension system. The simulation optimization results show that the performance of the optimized system is significantly improved: the RMS value of vertical acceleration is reduced by 5% compared with that before optimization, the RMS value of roll angular acceleration is reduced by 11.2%, and the RMS value of pitch angular acceleration is reduced by 4.7%. In conclusion, the method constructed in this paper can effectively improve a practical and feasible reference for the damping optimization design of the cab suspension system.