Existing research on the traction control system(TCS) mainly focuses on control methods, such as the PID control, fuzzy logic control, etc, aiming at achieving an ideal slip rate of the drive wheel over long control periods. The initial output of the TCS (referred to as the torque base in this paper), which has a great impact on the driving performance of the vehicle in early cycles, remains to be investigated. In order to improve the control performance of the TCS in the first several cycles, an algorithm is proposed to determine the torque base. First, torque bases are calculated by two different methods, one based on states judgment and the other based on the vehicle dynamics. The confidence level of the torque base calculated based on the vehicle dynamics is also obtained. The final torque base is then determined based on the two torque bases and the confidence level. Hardware-in-the-loop(HIL) simulation and vehicle tests emulating sudden start on low friction roads have been conducted to verify the proposed algorithm. The control performance of a PID-controlled TCS with and without the proposed torque base algorithm is compared, showing that the proposed algorithm improves the performance of the TCS over the first several cycles and enhances about 5% vehicle speed by contrast. The proposed research provides a more proper initial value for TCS control, and improves the performance of the first several control cycles of the TCS. Existing research on the traction control system (TCS) mainly focuses on control methods, such as the PID control, fuzzy logic control, etc, aiming at achieving an ideal slip rate of the drive wheel over long control periods. The initial output of the TCS (referred to as the torque base in this paper), which has a great impact on the driving performance of the vehicle in early cycles, remains to be investigated. In order to improve the control performance of the TCS in the first several cycles, an First, torque bases are calculated by two different methods, one based on states judgment and the other based on the vehicle dynamics. The confidence level of the torque base calculated based on the vehicle dynamics is also obtained. . The final torque base is then determined based on the two torque bases and the confidence level. Hardware-in-the-loop (HIL) simulation and vehicle tests emulating sudden start on low friction roads have been condu cted to verify the proposed algorithm. The control performance of a PID-controlled TCS with and without the proposed torque base algorithm is compared, showing that the proposed algorithm improves the performance of the TCS over the first several cycles and enhances about 5% vehicle speed by contrast. The proposed research provides a more proper initial value for TCS control, and improves the performance of the first several control cycles of the TCS.