چكيده به لاتين
In this thesis, the goal is to optimize the distance of cars in a platoon in order to reduce fuel consumption. This field includes a number of trailers that move in a row at certain intervals. Reducing the distance of a string can reduce the force of air resistance to some extent, the amount of which depends on the amount of this distance. The length of the line is large or small, the road profile includes uphill and downhill, and the wind also affects the amount of this force. Considering all these conditions, it is possible to form and determine the distance between the trucks of a line in order to reduce their fuel consumption while maintaining safety. A speed planning algorithm is presented to calculate the optimal average speed of the platoon by solving a fuel time optimization problem based on Pontriagin's minimum principle. By using the sliding mode controller to control the vehicle tracking, the stability of the truck train with the desired distance between the vehicles is guaranteed. Then a quadratic distance policy (QSP) is applied in platoon control, where the distance between the target vehicle is a quadratic function of the commutator's speed, and a platoon control scheme based on distributed integrated sliding mode (DISM) for Disturbance control is used. The complete model of the truck line is modeled in Matlab/Simulink software. The verification part is divided into two parts: verification of the optimal speed path and vehicle tracking evaluation, and the curves of the optimal speed path and keeping the distance between the cars have been extracted. The output results of reducing fuel consumption by optimizing the distance and speed have also been compared with QSP and PMP, which shows the improvement in the output results of travel time and fuel consumption. The difference between the work and the reference article, in addition to the application of external disturbances, is the provision of a quadratic distance optimization policy (QSP) in terms of speed in platoon control, which is an innovation to set the optimal distance in a row of trucks. The optimization performed with (QSP) has caused a 50- second reduction in driving time and a 2.7% improvement in fuel consumption output results. Among the advantages of the method used is the use of distributed integrated sliding mode control in places where the nonlinear functions are unknown. (uncertainty, disturbance and error) which causes the system to resist uncertainty and disturbance and eliminate chattering in the system.
