Abstract: Abstract: The slip phenomenon is common for heavy truck which is starting. This paper develops the anti-slip control strategy based on optimal slip rate, and the ASR (anti-slip regulation) is applied to heavy truck. In this paper, the speed is estimated by the acceleration; the wheel rotation speed can be easily got because the alternating current motor speed is easy to monitor; and then the slip rate is known. The fuzzy controller's knowledge bank is designed based on references' theory and engineering experience. At the same time, the SPWM (sinusoidal pulse width modulation) model is built. In the SPWM model's inner ring, the torque is positively related to the current. And the torque can be adjusted, so the current can be modified, and the motor output torque can be rectified. If the motor output torque is adjusted, the torque which is input to the wheel is increasing or decreasing correspondingly. So the driving torque on wheel can be balanced with the resistance torque on wheel, which means the truck can operated at a steady state. The fuzzy control system adjusts the torque distribution of the wheel-motors to maintain the optimal slip rate. The system is modeled with Matlab/Simulink software. Using this model, serial tests are simulated on various terrains including the road with low attachment coefficient, the bisectional road and the joint road. In the road with low attachment coefficient, the slip rate without control is very high that can reach 1, which means the wheel is rotating but truck wouldn't move. After applying the control, the slip rate can stabilize at a given reference value. Meanwhile, the attachment coefficient can be controlled at an optimal level. In the bisectional road, the slip rate is ideal when the truck's wheel is at the side of the road with high attachment coefficient; but when the truck moves into the road with low attachment coefficient, the slip rate sharply increases. At this moment, the truck can't ensure the direction of stability. So the danger coefficient is high. But the slip rate with control is stabilized at a given value. The result shows that the fuzzy control system can raise the utilization attachment coefficient and improve the power, stability and safety. Finally, to verify the controller's feasibility and calculation efficiency, the hardware-in-loop (HIL) simulation system is implemented. The national instrument (NI) embedded system is used. The truck's model that includes the dynamic model and the AC motor's control model is operated in PXI8110. And the control algorithm is running in CompactRIO-9024 which is an excellent controller to simulate the real-time situation. All the simulation operations are run again in the HIL system, and the road with low attachment coefficient, the bisectional road and the joint road are included. In the HIL simulation, the shapes of slip rate curve and attachment coefficient curve are consistent with the simulation results in Matlab/Simulink. The real-time simulation result shows that the slip rate and attachment coefficient can be quickly stabilized at an optimal level. But the response time is really different. For example, the simulation time in Matlab/Simulink is much more than the HIL time. The HIL simulation system's advantage is that not only the simulation time is much less than the Matlab/Simulink but also the response time is much less. On the other hand, the response time is short, which means that the HIL simulation system has a more perfect real-time performance. In short, the real-time performance of the fuzzy control algorithm has been proved.