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With more and more countries proposing timetables for stopping selling of fuel vehicles, China has also issued a “dual-slope” policy. As electric vehicles are the most promising new energy vehicle, which is worth researching. The integration and control of the motor and gearbox have gradually become a hot research topic due to low cost with better performance. This paper takes an electric vehicle equipped with permanent magnet synchronous motor and two-gear automatic transmission without synchronizer and clutch as the research object.

This paper defines the shifting quality evaluation index in detail for DCT (Dual Clutch Transmission) from the perspective of control. The vehicle model for DCT is built using MATLAB / Simulink tools, including the models of driver, load, controller, engine, clutch, transmission (synchronizer), actuators, and vehicle dynamics model. And then a control quality evaluation system is designed. The AHP (Analytic Hierarchy Process) is used to determine weights of the control quality evaluation index and the shifting quality control objectives through the co-simulation of vehicle system model and evaluation system, namely expected control range of each evaluation index, which provides reference and guidance for shifting control strategy and control algorithm of DCT.

Improvement of shift quality evaluation has become more prevalent over the past few years in the development of automatic transmission electronic control system. For the problems of the subjective shift quality evaluation that subjectivity is too strong, the standard cannot be unified and the definition of the objective evaluation index is not clear at present, this paper studies on the methods of objective evaluation of shift quality based on the multi-hierarchical grey relational analysis. Firstly, objective evaluation index system is constructed based on physical quantities, such as the engine speed, the longitudinal acceleration of the vehicle and so on, which broadens the scope of the traditional objective evaluation index further.

According to the low efficiency of vehicle equipped with automotive transmission (AT) at launching conditions, the TCCs slip and lock up control technology was proposed and a TCC simulation model was established. The vehicle dynamics, torque fluctuation and efficiency were analyzed. Simulation results were obtained when taking the constant engine speed as the control target. The three-dimensional transient heat conduction finite element model using CFX was built. The slipping power was calculated and was converted to heat flux on the surface of TCCs friction plate model. The temperature of TCCs friction plate was obtained at different ATF oil temperature. Simulation results show that the TCCs slip and lock-up control technology at launching conditions can effectively solve the vehicles low efficiency problems caused by torque converter (TC). The maximum temperature rise of TCCs friction plate was 20°C.

In the electro-pneumatic automated mechanical transmission (AMT) system, the manufacturing, assembly, wear, replacement and other issues often lead to gear position change and some differences in various gears of transmission, which reduces the success rate and even results in abnormally working. To solve these problems, based on the intelligent control theories of fuzzy PI control, this research developed an intelligent self-learning system for the AMT gear position. This system contains the position initialization module after assembling (offline module) and the position correction module in use (online module). The system can automatically recognize gear position deviation and actively correct it, which improves the robustness of shift actuator. The precise control of shift actuator is the key of this self-learning system.

Starting control has become a troublesome issue in the developing field of the control system for heavy-duty trucks, due to the complexity of vehicle driving and the variability of driver's intention. The too fast clutch engagement may result in serious impact, influence on the comfort and fatigue life, and even the engine flameout, while the too slow clutch engagement may lead to long time of friction, the increased temperature, and accelerated wear of friction pair, as well as influence on the power performance and fatigue life[1]. Therefore, the key technique of starting control is clutch engagement control, for which the fuzzy PID based optimization of starting control for AMT clutch is proposed, with the pneumatic AMT clutch of heavy-duty trucks as the research object.

In order to improve the trajectory tracking accuracy and yaw stability of vehicles under extreme conditions such as high speed and low adhesion, a coordinated control method of trajectory tracking and yaw stability is proposed based on four-wheel-independent-driving vehicles with four-wheel-steering. The hierarchical structure includes the trajectory tracking control layer, the lateral stability control decision layer, and the four-wheel angle and torque distribution layer. Firstly, the upper layer establishes a three-degree-of-freedom vehicle dynamics model as the controller prediction model, the front wheel steering controller is designed to realize the lateral path tracking based on adaptive model predictive control algorithm and the longitudinal speed controller is designed to realize the longitudinal speed tracking based on PID control algorithm.