This study focuses on the development and optimization of intelligent transmission control systems in the field of new energy vehicles. The aim is to enhance the performance and energy efficiency of transmissions within new energy vehicles, particularly in terms of responsiveness and efficiency under constantly changing driving conditions. To this end, the research employed a combination of fuzzy logic control and deep reinforcement learning to develop intelligent control strategies. These strategies were validated through simulations and real road testing, proving their effectiveness in practical applications. The results indicate that the intelligent control system significantly improves shift speed and reduces energy consumption, outperforming traditional control systems. The findings underscore the crucial role of intelligent control systems in optimizing transmission performance in new energy vehicles and provide valuable insights for future vehicle control system design.