Research On Optimization Strategy Of Clamping Force Of CVT Based On Model Predictive Control

As an ideal vehicle transmission device,Continuously Variable Transmission(CVT)has been widely concerned by the market because of its continuous change of ratio,compact structure,smooth power output.In theory,CVT can achieve the best match with the engine,so that the engine can be maintained in the optimal working area under any conditions,and effectively improve the power and economy of the vehicle.However,the advantages of CVT have not been fully reflected due to technical limitations,matching,calibration and other factors.Clamping force is the key to realize torque transmission and ratio change of CVT.Whether the change is accurate and reasonable will directly affect the CVT transmission efficiency.In order to ensure that CVT has a good reliability of torque transmission under any conditions,the safety factor method is widely used to control and adjust the clamping force.The deficiency is that excessive clamping force means higher oil cylinder pressure,resulting in additional overflow and friction loss of the system,and reducing the service life of CVT.Therefore,in order to effectively improve the CVT transmission efficiency and fuel economy of the vehicle,it is necessary to optimize the clamping force through more reasonable control strategies according to the actual driving requirements of the vehicle.This paper takes the metal belt CVT as the research object,proposes the CVT optimization control strategy based on the Model Predictive Control(MPC),and carries out the simulation and the vehicle test.The main work includes the following four aspects:(1)Based on the analysis of the mechanical structure and working principle of CVT,the CVT dynamic mathematical model is established.At the same time,in order to facilitate the follow-up study of the clamping force,the clamping force test bench is built,the working characteristics of the engine are analyzed,and the optimal power performance and economic working curve of the vehicle is given.(2)A driving intention recognition system is designed based on fuzzy control strategy,and the simulation verification and analysis are carried out.The results show that by analyzing and processing the input variable accelerator pedal opening and its rate of change,the driver’s driving intention can be accurately obtained,and the CVT target ratio at the corresponding time can be deduced.According to the difference between the target ratio and the actual ratio,ratio control can be achieved based on the PID control strategy.(3)The traditional clamping force control strategy is introduced,the impact of unreasonable clamping force on CVT is described,the dynamic slip mathematical model is established,and the optimal slip rate curve is determined.For the optimization of clamping force,under the premise of fully considering the CVT slip characteristics and related constraints,with the slip rate as the optimization goal,a clamping force controller based on model predictive control is designed to achieve real-time optimization adjustment of the clamping force,so as to improve the transmission efficiency and fuel economy.(4)To verify the actual control effect of the controller,a comprehensive simulation model was established based on MATLAB/Simulink and AMESim simulation software.The effectiveness and robustness of the controller are verified and analyzed with the clamping force test bench,and the controller is simulated under the NEDC cycle condition.Finally,the drum test is carried out on the vehicle equipped with the controller under three different conditions.