Design And Study On Cooling And Lubrication System For Hydro-Mechanical Continuously Variable Transmission Of Heavy-duty Tractor

Hydraulic Mechanical Continuously Variable Transmission（HMCVT）,as the core technology of the intelligent heavy-duty tractors,was of great significance to the development of my country’s agricultural modernization.Heavy-duty tractors were mainly used for field work with harsh environment and high-load conditions.Problems such as clutch ablation were often appeared,which caused by poor cooling and lubrication.The method of first experience design and reverse improvement was mostly used in cooling and lubrication system of transmission in the early period.This way not only had a high initial design cost,but also lacked theoretical guidance for improvements.This paper had depth studied in the cooling and lubricating system of HMCVT,combined with theoretical mathematical models,computational fluid dynamics and experimental research methods.The study which can provide a reference for the design and optimization of the cooling lubricating oil circuit was as follows:（1）The HMCVT cooling and lubrication system was designed,and the three-dimensional model of the oil circuit was established.First,according to the HMCVT transmission principle and structural layout plan,the design of oil circulation and circuit structure and the calculate of oil volume was carried out.Then,the three-dimensional model of the oil circuit and the oil distribution ring structure was established by UG software.（2）The theoretical mathematical model of the flow field of the cooling and lubrication oil circuit was established.Based on the basic equations of fluid mechanics and certain assumptions,the oil circuit was divided into four parts:T-shaped tee,axial branch,radial outlet and end branch.The fluid model of each part was established and then integrated together.The"inverse calculation iteration"method was used to solve the problem step by step from the end outlet to the inlet.When the error between the inlet flow rate and the set value was less than 10^-6,the iteration converges,and the pressure change of the flow field was theoretically analyzed.（3）The influence of various factors on the flow field of the cooling and lubrication oil circuit was analyzed by simulation.First,with Fluent the mesh was divided,the oil parameters and boundary conditions was set,the realizable k-εturbulence model was selected and the SIMPLEC solver was used to solve it.The convergence of the result was judged by the residual error and the flow balance curve.Then the pressure and flow velocity was analyzed on the oil distribution mechanism,the segment clutch shaft oil circuit based on the CFD model.The influence of speed,oil viscosity,the main oil circuit aperture and outlet angle was deeply studied,which provided theoretical support for the optimization of the oil circuit structure.（4）A test bench for the flow distribution of the cooling and lubrication oil circuit was built,and the relevant test research was completed.The cooling and lubrication pipeline system and hydraulic system of the test bench were designed and built,and the control and data acquisition system was developed based on Lab VIEW software.On the one hand,the correctness of the CFD simulation model was verified.On the other hand,the orthogonal experiment was designed to study the oil distribution when the outlet diameter changed by ANOVA and range analysis,which provided test support.（5）The optimization study of the oil distribution of the cooling and lubrication oil circuit was carried out.The oil outlet diameter was chosen as the design variable in the optimization process based on the simulation and test.The sample data was obtained by the Latin hypercube sampling and the CFD model and flow-aperture function relationship was set respectively by response surface method,BP neural network and the RBF neural network.Among them,the proxy model fitted by the RBF neural network had the highest accuracy.The coefficient of determination was above 0.95,and the relative root mean square error was less than 0.1.The optimal mathematical model of the flow distribution was built with the RBF neural network,the penalty function method was used to improve the optimization model and the genetic algorithm was selected to solve it.After the optimization of the flow channel,the distribution of the cooling lubricating oil was more reasonable,and the error between the target flow value with the solution was within 5%,which verified the feasibility of the optimization method.