Control Algorithm Selection Technique for Vehicle Robotic Transmission in the Urban Cycle

Environmental pollution is one of the most crucial problems in modern world. The toughening of emission standards for toxic fumes, which appear due to the combustion of fossil fuels in internal combustion engines, forces manufacturers to reduce fuel consumption, for example, via more rational use of the internal combustion engine capabilities. This paper is devoted to developing a control algorithm selection technique for economy class passenger car robotic transmission in the conditions of an urban cycle, using Lada Vesta SW Cross as a research subject. At the beginning of the paper, vehicle movement imitational mathematical model implementation, which was developed using LMS Imagine. Lab Amesim program complex. is shown. Also the main assumptions and parameters of engines, cooling systems, transmissions and chassis are given. Then imitational mathematical model verification results, which were processed by comparing movement computer simulation results with the vehicle passport data, are shown. Imitational mathematical model demonstrates the car behavior adequately and very precisely, which means it can be used for vehicle fuel efficiency research. In the main part of the paper, vehicle movement research is conducted in case of three different versions of the internal combustion engine (which has 1,4-, 1,6- and 1,8-liters volume) used in an urban cycle INRETS urbanfluide2. It is clearly shown that the lowest consumption is achieved by reducing the acceleration and braking dynamics via “early” gear shifting, and the crankshaft rotation speed at the corresponding moment of the shift has to be selected for each gear separately. Based on the research results, a switching algorithm and its selection technique, which takes the throttle valve opening degree and the type of the internal combustion engine external speed characteristic into consideration, are presented. In conclusion, this paper presents the results of vehicle movement imitational mathematical modeling in the urban cycle with a modified robotic transmission control algorithm. It is clear that this algorithm can reduce fuel consumption in the urban cycle by 12-20%, depending on the engine volume.