Research On Hydraulic Performance Of Automotive Cooling Pump Based On Multi-objective Genetic Algorithm

Automotive cooling water pumps are the core components in the water cooling system of automobile engines.The working stability and hydraulic performance of the automobile directly affect the working efficiency of the engine.With the development of society,the performance of car engines has increased,and the hydraulic performance requirements of automobile cooling water pumps have become higher and higher.It is of great significance to research and optimize the hydraulic performance of automobile cooling water pumps.In this paper,the genetic algorithm optimization method is applied to the hydraulic performance optimization of automobile cooling water pump for the first time.The main research contents are as follows:Firstly,based on the performance requirements of the automobile cooling water pump required by an automobile manufacturer,the original water pump model was determined using traditional design methods,and the three-dimensional assembly model was implemented in ProE software,which was imported into the ANSYS workbench software using the finite element method to static analysis the original water pump.The test results show that the stress of each component in the working state is within 80% of the material yield limit,and it is verified that the material strength meets the design requirements.Secondly,the computational domain of the original water pump was extracted,and CFD simulation analysis was performed in the pumplinx software.Determine the optimization goal is to increase the head and improve the efficiency without destroying the working stability of the cooling water pump.Three sub-objective functions are determined for the optimization goal: the energy loss sub-function in the pump,the pump theoretical head sub-function,and the hump function of the pump’s operating characteristic curve.Apply the evaluation function method to determine the weight coefficient,consider the constraints inside and outside the system to set constraints on design variables,and unify the overall optimization mathematical model.MATLAB software was used to program the genetic algorithm code to iteratively calculate the overall optimization function to obtain the optimized structural parameters of the impeller of the cooling water pump.Thirdly,the optimization results of the genetic algorithm were used to model the impellerparameters,and the CFD numerical simulation is performed again.The comparison of the simulation results of the hydraulic performance of the model before and after the optimization shows that the efficiency has increased by 6%,the head has increased by 5.618 m,the pump characteristic curve is smoother,and the hump phenomenon has been significantly improved.The feasibility of the genetic algorithm method for optimizing the hydraulic performance of cooling water pumps was verified.The genetic algorithm optimization results are compared with the orthogonal experiment optimization results,which proves that the genetic algorithm optimization method is more superior.Finally,manual samples were produced based on the optimized impeller parameters,and external characteristic tests were performed in the factory laboratory.Comparing the simulation data with the test data,it was found that the characteristic curve trend was consistent and the error was controlled within 10%,which verified the accuracy of the CFD simulation method.At the same time,the good performance of the optimized model is proved,and the feasibility of the genetic algorithm optimization method is verified.For the future research on the hydraulic performance optimization of automotive engine cooling water pumps,a new idea combining genetic algorithm optimization method and CFD simulation calculation is provided.