柴油机高压共轨系统轨压模糊控制与试验

为了改善发动机的冷起动性能以及有利于各工况切换时喷油的精确控制,该文针对采用高压共轨系统的柴油机,建立了基于模型的轨压控制策略,首先分析推导其数学模型;然后利用MATLAB/Simulink建立了轨压控制模型,轨压控制设计了前馈控制加反馈控制的轨压控制器,轨压反馈控制设计了传统的增量式PID(比例-积分-微分,proportion-integration-differentiation)控制器和模糊自适应PID控制器;最后对轨压控制模型进行了离线仿真验证;在此基础上利用硬件在环系统进行发动机台架试验,比较了2种控制器的控制效果。仿真和台架试验结果表明,模糊自适应PID控制器在目标轨压突变时的响应性(响应时间小于0.3 s)和跟随性以及稳定工况下轨压的稳定性(稳态误差小于2 MPa)方面都优于传统的增量式PID控制器,从而验证了控制策略模型的正确性。该研究提出的基于模型的轨压控制策略有助于实现柴油喷油的精确控制,可为柴油机共轨技术国产化提供参考。

Fuzzy control and experiment of rail pressure for high- pressure common rail system of diesel engine

Abstract: In view of the high-pressure common rail system of diesel engine, the rail pressure control strategy was established based on the model in this paper. First, according to the electrical, magnetic and fluid flow characteristics of the main components in the common rail system, the mathematical models were built, including proportional electromagnetic valve, high-pressure pump, common rail and other major parts. The motion equation and circuit equation were established through the simplification of the stress state of the proportional solenoid valve. The continuity equations were set up respectively according to the liquid flow characteristics of the high-pressure pump and common rail pipe, and the common rail system transfer function was derived through the Laplace transform of the above equations. Second, the rail pressure control model was established based on MATLAB/Simulink, which contains the rail pressure target value calculation and rail pressure controller design. The calculation of target value of rail pressure includes two operation conditions i.e. starting and post-start. The constant value of 71 MPa is taken as the target value under the initial starting condition. After starting, the calculation of target value is based on the query of rail pressure target basic values according to engine speed and current fuel injection quantity, as well as the corrections on the other environmental parameters such as fuel temperature, coolant temperature, inlet pressure and temperature. The control strategy of rail pressure includes the open-loop control under the early starting condition and the closed-loop control at the starting process after rail pressure reaches the target value. The design of rail pressure control adopts the rail pressure controller with feedforward control and feedback control. The feedforward control mainly considers the basic value of the feedforward control according to the engine fuel injection quantity and the feedback values from the injectors and other components. The rail pressure feedback control adopts the traditional incremental PID (proportion-integration-differentiation) controller and the fuzzy adaptive PID controller. The input of PID controller is the rail pressure deviation, and the inputs of fuzzy adaptive PID controller include the rail pressure deviation and its change rate. Taking the derived transfer function of the common rail system as the control object, the response characteristics and anti-interference performances of the two control systems were simulated, and the simulated target rail pressure curve was compared with that of the bench test. The results showed that the rail pressure target value by the model calculation was close to the test value. The rail pressure dynamic response tests were conducted with the incremental PID controller and the fuzzy adaptive PID controller on the basis of the known target value of rail pressure, and their control effects were compared. With the setting of a group of PID controller parameters, under the condition of initial parameters of the fuzzy adaptive PID controller, the incremental PID controller showed a certain limitation, which could not realize ideal control during the full change range of rail pressure, and especially at the lower or higher pressure ranges, its dynamic response performance turned worse. While the fuzzy adaptive PID controller in the whole rail pressure change range had a good response and stability. On this basis, the fuzzy adaptive PID controller was tested and the response performance was analyzed on the actual rail pressure under engine starting, deceleration and full load conditions. The results of simulation and bench test showed that the fuzzy adaptive PID controller had better follow-up performance and responsiveness (response time was less than 0.3 s) to the target rail pressure, and the stability of the rail pressure under the stable working condition (steady-state error was less than 2 MPa) was superior to that of the traditional incremental PID controller. The control strategy of rail pressure proposed in the study can realize accurate control of diesel fuel injection, and also provide a reference for technology localization of common rail diesel engine.