Application Research On The Idle Control Strategy Of Gasoline Engine

Idle condition is an important condition of gasoline engine, which is directly related to passenger comfort, fuel economy and the environmental indicators of the vehicle. In the idle condition, the gasoline engine speed is needed to maintain its own operation, and on the other hand it should be able to provide enough energy for the vehicle load. Therefore, a reasonable value of the idling speed is required. While a gasoline engine load is changed, its rotational speed need to achieve a smooth transition. Because of the complex structure, strong nonlinear, time-varying and hysteresis, it is difficult to control the idling speed of the gasoline engine.A gasoline engine contains multiple subsystems. It has a complex structure and several undetermined parameters. And in the process of engine operation, the parameter will be perturbed. So it is difficult to establish a accurate mathematical model. In this work, the control objectives and control principles idle condition were considered to establish a transfer function model from its external characteristics with the input and output data.A PID controller has a excellent performance, stability and reliability. It is also very easy to implement.Two modified PID control strategy were used to control the gasoline engine idle speed condition based on the mathematical model establishedFirstly, chaos search strategy was added in the particle swarm optimization algorithm to enhance the global optimization capability of standard particle swarm optimization. It can reduce the probability of falling into local optima of standard particle swarm optimization algorithm. Chaos particle swarm optimization algorithm was used to tune the parameters of PID controller in the case of off-line. It can tune the parameters of PID controller offline and call it online in real-time. In order to verify the effectiveness of the algorithm, the simulation tests were conducted based on MATLAB environment. The results shows that the introduction of the chaos search strategy base on the standard particle swarm algorithm can improve the convergence speed and optimizing of particle swarm optimization. With the parameters tuned by chaos particle swarm optimization, a PID controller has a good ability to regulate the error.Fuzzy control methods break the shackles of traditional control theory. It can implement complex control law and widely used in various fields of industrial control. In this paper, fuzzy control method is used to tune the parameters of PID controllers.While the PID controller is working in the closed-loop system, there is a contradiction between dynamic performance and steady-state performance of the system. Only to find a balance between the two kinds of performances. To alleviate this problem, this work introduced a feedback mechanism of immune algorithm on the basis of fuzzy PID controller, which used the fuzzy immune adaptive PID control strategy to control the idle condition. In this control strategy, use immune algorithm to tune the proportional parameter P of the PID controller and use fuzzy algorithm to tune the integral parameter I of PID controller. In the simulation experiment based on MATLAB, the fuzzy immune adaptive PID control algorithm perform better than the chaos particle swarm PID algorithm in the terms of control accuracy.With the coordination of two control strategies, it can further improve the accuracy and robustness the PID controller. It also does not need to spend a lot of energy to draw the PID controller parameter table. Through comparative analysis, fuzzy immune adaptive PID algorithm is more suitable for engineering practice.The software part of fuzzy immune adaptive PID algorithm was designed in this work based on μc/OS-Ⅱ. In the computer control system, incremental digital PID algorithm was used in this paper.Fuzzy immune adaptive PID control strategy working process was divided into several tasks. The program of each task was designed in this work.