| Tracked vehicle is a special non-highway vehicle. As the driving road situation of tracked vehicle is complex and changeful, running resistance changes greatly. As drivers have to dispose more and more information, current control strategy of automatic transmission of tracked vehicle cannot adapt to the complicated internal and external driving conditions. In order to decrease the frequency of gear shifting and alleviate the driver's fatigue, new style tracked vehicle often adopt hydraulic mechanical transmission. After the investigations of intelligent shift strategy and adaptive fuzzy control technology of tracked vehicle drivetrain are implemented, a new technology of intelligent fuzzy control is presented to optimize manipulation according to road and vehicle conditions, and thus the cross-country maneuverability is improved.Based on the randomicity of road condition variety, the statistic simulation maths models of random parameters are built using statistic simulation method, such as vehicle ground resistance coefficient, ramp resistance coefficient, turning resistance coefficient, ground adhesion coefficient. According to tracked vehicle steering parameters obtained by the sensors in automatic transmission, the driver manipulating intention and driving environment are concluded by fuzzy inferential method. It establishes foundation of intelligent shift system in complicated running conditions. The dynamic models of engine, hydraulic torque converter, planetary transmission and bodywork are built by means of maths model and table model. According to together working characteristics of engine and hydraulic torque converter, both of them not only have enough functions but also well matching. It establishes theoretic foundation of intelligent control and simulation system of automatic transmission.According to the sum-up of drivers control experience, the primary principle of a fuzzy shift control of tracked vehicle under varying driving conditions is ascertained. Using the fuzzy control theory, an intelligent fuzzy shift control system composed of a basic fuzzy shift strategy and a fuzzy modification module is developed. A basic fuzzy shift strategy regards the conventional dynamic 3-parameter (vehicle speed, throttle position and vehicle acceleration) as input variables of fuzzy control and gear position as output variable. Because this shift strategy don't adapt to the complicated driving conditions of tracked vehicle, this dissertation adds a fuzzy modification module. Therefore driver manipulating intention and driving environment are concluded. Based on a basic fuzzy shift strategy, a two-stage adaptive fuzzy control system and neural network control system for automatic transmission of tracked vehicle were established. According to the measured vehicle speed and acceleration, the adaptive fuzzy control module could identify linear running resistance and adhesive force of tracked vehicle and automatically regulated the fuzzy normalized factors. This system improves the shift quality of tracked vehicle under manifold driving conditions.In order to validate the reliability of intelligent fuzzy shift strategy of tracked vehicle, based integrated methods both system discriminate and theoretics modeling, simulation models of intelligent shift of a tracked vehicle are established. The shifting parameters can be modified duly in system so as to provide referenced preliminary parameters. The vehicle performance and dynamic process of shifting in multifold shifting strategy are simulated. It can forecast the performance of automatic transmission and evaluate quality of shifting strategies. The purpose of the bench test of automatic transmission has been put forward and total project and test item of the bench test system have been described. So the feasibility of intelligent shift strategy built by this dissertation has been validated in the bench test.
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