Abstract: Gearshift control poses significant influence on smoothness and dynamics of vehicles, especially for vehicles equipped with dual clutch transmissions (DCT). However, classical strategies are difficult to account for complex transient variations of the clutch friction coefficient during gear shifting. To cope with this challenge, this study proposes an adaptive gearshift control algorithm based on physical and data-driven modeling for regulation of the clutch friction coefficient. A closed-loop strategy is proposed for the speed control in the gearshift process of DCT vehicles. The reference speeds of clutch and engine are determined via online invocation of the pseudo-spectrum method. Meanwhile, an adaptive sliding mode controller based on the fused physical and data-driven hybrid model is designed to control the clutch oil pressure in the torque phase, thereby enabling precise tracking of the reference speed of the clutch. Then, an efficient engine controller is designed based on sliding mode control to regulate the throttle opening for following the engine reference speed in the torque phase. The simulation and experimental results manifest that the proposed adaptive control method maintains satisfactory shift quality with high adaptive capability and strong robustness under time-varying throttle pedal opening.