Longitudinal control approach for intelligent vehicles considering the impact of road slope and load

Aiming at the problem of inconsistent response caused by the degradation of the performance of parts and components of automobiles used for a long time as well as the deviation of the manufacturing accuracy in the process of batch production, we proposes a longitudinal control method for intelligent vehicles. Among them, load compensation, drive steady-state compensation, brake steady-state compensation and the design of controller parameters are studied. The vehicle sensor information is used to estimate the slope and total mass of the vehicle online, and the steady-state compensation gain coefficients of the forward channel are dynamically corrected on this basis. Taking into account the deviation of the estimation algorithm from the steady-state calibration parameters of the test vehicle, this paper further optimizes the closed-loop control parameters, which ensures the consistency of the dynamic response performance of the closed-loop system under the interference of the roadway slope/load/component performance, and improves the driving performance of the vehicle. In the gain and compensation deviation validation, it can be seen that it can still be corrected quickly at 30% deviation. In the slope and load adaptive validation, it can be seen that the acceleration consistency is high when the load difference is 200 kg and the slope difference is 10%.