Intelligent Management Of Engine Cooling Water Based On Electronic Water Pump

With the gradual strengthening of the awareness of environmental protection,the world’s emission requirements for vehicles are becoming increasingly strict,so it is very important to develop high-performance and low emission engines.As an essential subsystem of the engine,the main function of the cooling system is to ensure that the engine operates at a suitable temperature.Water pump is an important part of the cooling system.At present,most of the engines use mechanical water pump,which can not actively regulate the cooling water flow under different working conditions,which will cause the increase of fuel consumption and emissions of the whole vehicle.The electronic water pump is not affected by the engine speed,and can actively adjust the speed of the electronic water pump,which can not only reduce the fuel consumption and emissions of the vehicle,but also make the coolant temperature change more stable,prevent the engine from overheating and supercooling,and increase the service life of the vehicle.At present,there are few control algorithms for the electronic water pump,so it is very important to develop intelligent cooling water management control strategy to regulate the cooling water flow under different working conditions for the cooling system.Based on this,this paper designs an optimization algorithm model for cooling water management of the cooling system.The specific research work and results are as follows:(1)Based on GT suite software,the simulation model of the whole vehicle cooling system is built and verified with the test results;based on the simulation results,t he engine electronic water pump speed prediction model based on BP neural network is built,and the accuracy of the neural network model is verified by untrained data,the average error of the model is 1.65%,and the prediction model has a high accuracy.(2)Based on MATLAB software platform,the optimization model of energy consumption of electronic water pump based on genetic algorithm and particle swarm optimization algorithm is established;on this basis,the fuzzy control model of thermostat opening is developed,and the fuzzy controller is optimized by using genetic algorithm;the optimized model obviously reduces the fluctuation of coolant temperature and realizes the purpose of improving the fluctuation of coolant temperature.(3)The optimization model based on genetic algorithm and particle swarm optimization is established and coupled with GT suite simulation model to carry out the joint simulation of engine cooling system performance.The results show that the optimization algorithm can reduce the fl uctuation of coolant,fuel consumption and energy consumption of electronic water pump,and the fuel consumption is reduced by 1.1% and 1.5% respectively after the optimization of the two algorithms,achieving better energy saving effect.The research results show that using Simulink to build the appropriate optimization algorithm can optimize the GT suite cooling system model,not only can improve the engine performance,but also can improve the economy of the vehicle to achieve the purpose of energy saving.