Hydrogen purification is an important part of hydrogen energy utilization. This study aimed to perform hydrogen purification of multi-component gas (H2/CO2/CH4/CO/N2 = 0.79/0.17/0.021/0.012/0.007) by one-column vacuum pressure swing adsorption (VPSA) and pressure swing adsorption (PSA). AC5-KS was selected as the adsorbent for hydrogen purification due to its greater adsorption capacity compared to R2030. Furthermore, VPSA and PSA 10-step cycle models were established to simulate the hydrogen purification process using the Aspen Adsorption platform. The simulation results showed that the hydrogen purification performance of VPSA is better than that of PSA on AC5-KS adsorbent. The effects of feeding time and purging time on hydrogen purity and recovery were also discussed. Results showed that feeding time has a negative effect on hydrogen purity and a positive effect on hydrogen recovery, while purging time has a positive effect on hydrogen purity and a negative effect on hydrogen recovery. By using an artificial neural network (ANN), the relationship between the inputs (feeding time and purging time) and outputs (hydrogen purity and recovery) was established. Based on the ANN, the interior point method was applied to optimize hydrogen purification performance. Considering two optimization cases, the optimized feeding time and purging time were obtained. The optimization results showed that the maximum hydrogen recovery reached 88.65% when the feeding time was 223 s and the purging time was 96 s. The maximum hydrogen purity reached 99.33% when the feeding time was 100 s and the purging time was 45 s.