多次喷射模式下共轨系统喷油量波动预测与补偿

Fuel Injection Quantity Fluctuation Prediction and Compensation for Multiple Injections of Common Rail System

摘要:

为了解决多次喷射模式下喷油量的精确控制问题，进行了基于波动量的预测，实现了有效的喷油补偿。首先，分析了喷油器的动态特性，并基于AMESim仿真软件建立了共轨系统喷油器仿真模型；然后，通过仿真数据分析多次喷射模式下喷油量波动的影响因素，确定了喷油压力、预喷脉宽、主喷和预喷之间的时间间隔等为主要特征参数，提出基于LM-BP模型的喷油波动量预测方法；同时，基于喷油波动量的预测结果设计喷油量补偿控制器。结果表明，基于波动量的预测可以提高喷射精度，验证了所提策略的有效性。

Abstract:

To solve the inaccurate injection quantity problem in multiple injections， in this paper， a simulation model of the electro injector is developed in the AMESim environment through dynamics analysis of injector， and the parameter matching and rationality verification of the model are also conducted. In addition， the influencing factors of fuel injection fluctuation are investigated. The results show that the change of injection pressure， pre-injection pulse width， the dwell time between the main and the pilot injection pulse can affect fuel fluctuation. Moreover， a fuel compensation control strategy based on self-learning system is constructed by using a certain sample of stimulation data to compensate for the deviation of multiple injection quantity. A self-learning system is realized by using the genetic algorithm （GA） and neural network， which can effectively improve injection control.