Research On Injection Quantity Control Of High Pressure Common Rail System

In order to comply with the increasingly stringent worldwide requirements of automobile emissions and fuel economy,and further achieve the goal of low pollution and fuel consumption of diesel engines,a series of new diesel engine technologies emerged at the historic moment.High pressure common rail system,with its high injection pressure and multiple injections technology,ensures the better mixing of oil and gas in the combustion process.It helps improve the engine performance.However,the unstable injection pressure caused by the constant opening and closing of high-pressure pumps and injectors,which directly affects the accurate quantity of fuel injection.In the process of multiple injections,the water hammer effect during the closing of the previous injection needle valve will inevitably lead to deviation in the calculation of fuel quantity for the next injection,thus directly causing the change of mixture ratio,insufficient combustion and decline diesel engine performance.In view of the above problems,it is the key and core to achieve accurate fuel injection quantity in multiple injections with perfect and effective control strategy.For this reason,this subject takes the high pressure common rail system as the controlled object,and designs reasonable and effective control strategy to precisely control the fuel quantity in multiple injections.The composition and dynamics of the system are analyzed,and the corresponding system model is built on the simulation platform.Sliding mode control theory is selected to design the injection pressure controller with Lyapunov stability,which ensures a high and stable injection pressure and lays a foundation for the realization of subsequent multiple injections and the compensation of injection volume.Then,the influence factors of multiple injections volume fluctuation are analyzed,and a self-learning system of injection pulse width correction value is constructed through a certain sample of stimulation data,so as to compensate the deviation of multiple injection volume.The selflearning system is implemented by gradient descent method BP neural network method.However,the traditional BP neural network design of fuel injection compensation algorithm has the shortcomings of slow convergence speed and easy to fall into the local optimal solution.In order to ensure a better compensation effect for fuel injection fluctuation when input parameters increase,a series of improvements are made to the fuel injection compensation algorithm.Firstly,the back propagation algorithm is designed by using the LM algorithm with quadratic convergence effect to accelerate the convergence speed of the algorithm.In order to improve the fitting and prediction accuracy of the network,the genetic algorithm is used to optimize the LM-BP neural network globally.Finally,the improved algorithm of fuel injection fluctuation compensation is put into the overall framework,which verifies that the designed injection quantity control strategy has better suppression effect on fuel injection fluctuation.In order to control the injection quantity accurately in multiple injections process,this paper provides a design idea for injection quantity control in the high pressure common rail system.Although the overall fuel injection control effect is verified in the simulation platform,there is still work to be done.For example,the realization of the physical platform of the controller will be further studied around its engineering implementation.