Adaptive Air-Fuel Ratio Control with MLP Network

This paper presents an application of adaptive neural network model-based predictive control (MPC) to the air-fuel ratio of an engine simulation. A multi-layer perceptron (MLP) neural network is trained using two on-line training algorithms: a back propagation algorithm and a recursive least squares (RLS) algorithm. It is used to model parameter uncertainties in the nonlinear dynamics of internal combustion (IC) engines. Based on the adaptive model, an MPC strategy for controlling air-fuel ratio is realized, and its control performance compared with that of a traditional PI controller. A reduced Hessian method, a newly developed sequential quadratic programming (SQP) method for solving nonlinear programming (NLP) problems, is implemented to speed up nonlinear optimization in the MPC. Keywords Air-fuel ratio control - IC engine - adaptive neural networks - nonlinear programming - model predictive control Shi-Wei Wang PhD student, Liverpool John Moores University; MSc in Control Systems, University of Sheffield, 2003; BEng in Automatic Technology, Jilin University, 2000; Current research interests automotive engine control, model predictive control, sliding mode control, neural networks.Ding-Li Yu obtained B.Eng from Harbin Civil Engineering College, Harbin, China in 1981, M.Sc from Jilin University of Technology, Changchun, China in 1986 and PhD from Coventry University, U.K. in 1995, all in control engineering. He is currently a Reader in Process Control at Liverpool John Moores University, U.K. His current research interests are in process control, engine control, fault detection and adaptive neural nets. He is a member of SAFEPROCESS TC in IFAC and an associate editor of the IJMIC and the IJISS.

Air flow control based on optimal oxygen excess ratio in fuel cells for vehicles

Air flow control is one of the most important control methods for maintaining the stability and reliability of a fuel cell system, which can avoid oxygen starvation or oxygen saturation. The oxygen excess ratio （OER） is often used to indicate the air flow condition. Based on a fuel cell system model for vehicles, OER performance was analyzed for different stack currents and temperatures in this paper, and the results show that the optimal OER was affected weakly by the stack temperature. In order to ensure the system working in optimal OER, a control scheme that includes an optimal OER regulator and a fuzzy control was proposed. According to the stack current, a reference value of air flow rate was obtained with the optimal OER regulator and then the air compressor motor voltage was controlled with the fuzzy controller to adjust the air flow rate provided by the air compressor. Simulation results show that the control method has good dynamic and static characteristics.

Transient Air-Fuel Ratio Control in a CNG Engine Using Fuzzy Neural Networks

The fuzzy neural networks has been used as means of precisely controlling the air-fuel ratio of a lean-burn compressed natural gas (CNG) engine. A control algorithm, without based on engine model, has been (utilized) to construct a feedforward/feedback control scheme to regulate the air-fuel ratio. Using fuzzy neural networks, a fuzzy neural hybrid controller is obtained based on PI controller. The new controller, which can adjust parameters online, has been tested in transient air-fuel ratio control of a CNG engine.

Study on a Closed-Loop Air-Fuel Control System of Gasoline Engines by Simulation

In order to study the factors that influence the air fuel ratio(A/F), the amplitude and frequency of A/F fluctuation, to reform the control strategy, and to improve the efficiency of three way catalyst(TWC), a model of closed loop control system including the engine, air fuel mixing and transportation, oxygen sensor and controller, etc., is developed. Various factors that influence the A/F control are studied by simulation. The simulation results show that the reference voltage of oxygen sensor will influence the mean value of A/F ratio, the controller parameters will influence the amplitude of A/F fluctuation, and the operating conditions of the engine determine the frequency of A/F fluctuations, the amplitude of A/F fluctuation can be reduced to within demanded values by logical selection of the signal acquisition method and controller parameters. Higher A/F fluctuation frequency under high speed and load can be reduced through software delay in the controller. The A/F closed loop control system based on the simulation results, accompanied with a rare earth element TWC, gives a better efficiency of conversion against harmful emissions.

热风炉空燃比并行协作粒子群滑模控制策略

针对热风炉燃烧控制存在的纯滞后、大惯性和强干扰等问题,提出了一种基于并行协作骨干粒子群(Parallel Cooperative Bare-Bones Particle Swarm Optimization,PCBBPSO)优化全局滑模控制(Global Sliding Mode Control,GSMC)的热风炉空燃比控制策略;为改善热风炉空燃比控制系统动态特性,引入全局滑模策略,对燃烧系统进行优化控制,以提高系统稳定性,同时,基于热风炉燃烧系统存在的强干扰特性,利用并行协作骨干粒子群对干扰补偿进行调节以减小其对系统的影响,并求取最优控制率;仿真结果表明:与普通粒子群优化全局滑模和普通粒子群优化PID相比,该控制方法达到稳定用时分别减少了26.4 s和9.3 s,能够保持没有超调量,拥有良好稳定的跟踪和抗干扰效果;将该控制策略应用于某钢铁有限公司2200 m 3高炉配套热风炉,工程数据表明:在该空燃比策略的控制下,热风炉空燃比上下波动幅度仅为8.20%,拥有波动小、稳定性好和抗干扰性强等特点,动态响应较好,能够满足热风炉工程实际应用的需要。

基于转矩需求和进气量广义预测的汽车发动机空燃比神经网络控制方法

分析燃烧特性与温度值,进行汽车发动机空燃比控制,但是忽略了发动机内部喷输油过程的延迟性影响,导致控制结果空燃比与理想值偏差较大。因此,提出基于转矩需求和进气量广义预测的汽车发动机空燃比神经网络控制方法。基于转矩需求分析汽车动力系数,针对发动机喷输油过程对发动机进气量进行广义上的预测,根据预测值对喷输油延迟进行补偿,优化空燃比控制律实现控制过程。实验结果表明:本文方法应用后得出的控制结果,表现出的空燃比变化与理想的14.7空燃比十分接近,控制效果较为优质,满足了汽车发动机燃烧质量的实际需求。

Air-fuel ratio control with stochastic L_2 disturbance attenuation in gasoline engines

In this paper, the problem of stochastic L2 disturbance attenuation of the air-fuel ratio is investigated with consideration of cyclic variation of the residual gas fraction （RGF）. A stochastic robust controller is designed based on a discrete-time dynamic model in which the RGF is modeled as a stochastic process with Markovian property. Finally, the sampling process-based statistical analysis for the RGF and the validation of the proposed control law are presented through the experiments conducted on a gasoline engine test bench.

Simple adaptive air-fuel ratio control of a port injection SI engine with a cylinder pressure sensor

The problem of air-fuel ratio(AFR) control of the port injection spark ignition(SI) engine is still of considerable importance because of stringent demands on emission control. In this paper, the static AFR calculation model based on in-cylinder pressure data and on the adaptive AFR control strategy is presented. The model utilises the intake manifold pressure, engine speed, total heat release, and the rapid burn angle, as input variables for the AFR computation. The combustion parameters, total heat release,and rapid burn angle, are calculated from in-cylinder pressure data. This proposed AFR model can be applied to the virtual lambda sensor for the feedback control system. In practical applications, simple adaptive control(SAC) is applied in conjunction with the AFR model for port-injected fuel control. The experimental results show that the proposed model can estimate the AFR, and the accuracy of the estimated value is applicable to the feedback control system. Additionally, the adaptive controller with the AFR model can be applied to regulate the AFR of the port injection SI engine.

炼油装置管式加热炉燃烧控制优化

炼油装置中管式加热炉为工艺流程提供热量。加热炉主要燃烧控制目标包括维持炉出口工艺介质温度、炉内无可燃物聚集风险、安全操作、高效节能等。国外项目中,平衡抽力和强制抽力模式的加热炉燃烧设计采用“空燃比控制”方案,当炉负荷增加时,优先增大供风量,随后增大燃料量,当炉负荷较小时,优先减少燃料量,随后减少供风量,以确保炉内的燃烧变化过程始终空气过剩,避免供氧不足、发生不完全燃烧,降低可燃物聚集的安全风险。较常规控制方案,采用“空燃比控制”方案的加热炉过剩空气系数较小,烟气排放量较少,热效率、安全性有所提高,操作费用有所下降。在碳中和目标下,加热炉采用“空燃比控制”的方案是一种提高燃料效率、减少CO_(2)排放的解决方案。

某型燃气轮机起动过程中火焰缺失故障分析与处理

通过对某电站燃气轮机在起动时出现火焰缺失跳机故障检查研究,分析发现起动设备对燃气轮机发出起动指令后有延迟响应时间。现场测试了起动电机响应时间、液力变扭器卸荷阀动作响应时间,发现响应时间有延迟会引起燃料控制量自动增加以保证燃气轮机升速。重新设定了燃气轮机起动和暖机阶段燃料设定值后解决了该故障。该燃气轮机火焰缺失故障检查和处理过程可为今后故障的处理提供参考。

二级过程控制在烧结脱硝热风炉自动燃烧系统中的应用

介绍了日照钢铁烧结脱硝工艺,阐述了二级过程控制系统在烧结脱硝热风炉自动燃烧系统中的应用原理。通过OPC采集一级PLC所需数据,利用模糊控制技术对SCR入口温度进行控制,在满足脱硝入口烟温条件下,实现烧结脱硝热风炉的全自动稳定运行,确保烧结脱硝热风炉温度最佳,燃耗最低。

Application of Optimization Technology for Ratio of Air to Fuel Combining Feedforward with Feedback in Heating Furnace

The thermal characteristics of heating furnace using gas as fuel are discussed in detail in this paper. Combining the technique of fuzzy control with calorific value of feedforward and oxygen concentration of waste gas feedback, the optimization model for ratio of air to fuel is developed and utilized in practice. According to the practical operation, the model can effectively control the oxygen concentration of waste gas, enhance the quality of product and decrease the fuel consumption.

车用汽油发动机电子控制系统研究现状与展望

发动机电子控制系统是高性能、高可靠性发动机开发的核心研究内容,是保证发动机动力性、经济性和排放性的重要因素之一.针对车用汽油发动机,本文首先分析了典型的车用汽油发动机电子控制系统结构,然后围绕电子节气门控制系统、燃油喷射控制系统、点火控制系统、空燃比控制系统、怠速控制系统、涡轮增压控制系统、爆震检测与控制系统以及汽油机先进燃烧模式控制这8项关键问题展开论述,并着重介绍了近年来国内外的研究内容和研究成果.最后对车用汽油发动机电子控制系统的发展前景和发展方向进行了展望.

车用汽油机过渡工况空燃比的神经网络控制研究

针对车用汽油机过渡工况空燃比难于精确控制的特点,提出了一种空燃比的神经网络复合控制策略。控制系统通过神经网络控制和常规PI控制实现前馈反馈控制,常规PI控制器利用氧传感器信号实现反馈控制,保证系统的稳定性,且抑制扰动;神经网络控制实现前馈控制,提高控制系统过渡工况时的响应能力。神经网络采用径向基神经网络,其输入为影响汽油机进气量的两个主要因素发动机转速与节气门开度。通过在线学习常规PI控制输出,使系统的总控制输出由神经网络产生,系统具有较高的自适应功能,有效避免目前过渡工况空燃比控制需进行大量标定的不足。仿真结果表明该控制方法是有效的。

基于神经网络的汽油HCCI发动机空燃比控制策略

均质压缩燃烧(HCCI)在控制上存在难点,其中关键是基于循环的空燃比实时控制。HCCI汽油机没有能直接表征发动机每循环进气量的参数,因此,采用动态递归神经网络(Elman网络)预测HCCI发动机每循环的进气量。通过氧传感器闭环和瞬态工况中的油膜补偿,实现对HCCI发动机的稳态及瞬态工况下空燃比的精确控制。试验表明:汽油HCCI发动机神经网络预测模型及空燃比控制策略能满足HCCI发动机实时控制的需求。

瞬态空燃比控制策略研究及智能控制的应用

介绍了基于平均值模型的汽油发动机瞬态空燃比控制策略,及人工智能和神经网络技术在模型参数辨识中的应用。

航空活塞式发动机瞬态空燃比控制与实验研究

针对航空活塞式直喷发动机瞬态空燃比难以精确控制、动态超调大等问题,采用PID神经网络控制策略对发动机瞬态工况空燃比进行控制.PID神经网络用于瞬态空燃比控制具有易于实现、较强自适应能力等优点.该策略包含前馈控制和反馈控制,并由前馈控制确定基本喷油量,PID神经网络作为反馈控制,实现瞬态工况的燃油补偿.在一台航空活塞式单缸机上进行了发动机瞬态空燃比控制实验,结果表明,瞬态工况下,相比于PID控制,PID神经网络控制下的过量空气系数超调量可以减小25%左右;节气门开度在5%~30%,之间以不同开度变化速率变化时,PID神经网络也能实现良好的控制效果.

氧传感器响应变慢自适应空燃比闭环控制方法研究

分析了汽油发动机空燃比闭环PI控制器的数学模型,提出了自适应空燃比闭环控制算法,研究了阶跃型氧传感器响应变慢对汽油机空燃比和排放的影响。研究结果表明:当氧传感器信号从稀到浓变慢时,过量空气系数相对于正常值会减小,同时HC和CO排放浓度会增大;当氧传感器信号从浓到稀变慢时,过量空气系数相对于正常值会增大,同时氨氧化物(NOx)排放浓度会增大。试验结果表明:设计的自适应空燃比PI控制器减小了在氧传感器响应变慢时过量空气系数偏离正常值的幅度,能够减少有害气体排放。

神经网络在汽油机瞬态空燃比控制中的应用

为了对稀薄燃烧汽油机的瞬态空燃比进行精确控制,提出了一个稀燃汽油机空燃比神经网络-滑模控制方案,该方案采用神经网络实现对瞬态过程中实际进入气缸内进气量的精确预测和进气管内油膜动态特性的前馈补偿.在一台稀燃发动机上进行了瞬态空燃比实验,节气门急速变化时的空燃比超调最大为1个空燃比单位,最小为0.2个空燃比单位;空燃比调整时间一般在3 s以内,最快可达到1 s.控制结果达到了对稀燃发动机瞬态空燃比的精确控制。

利用离子信号进行发动机空燃比控制方法的研究

直接利用燃烧中所产生的离子信号进行了空燃比控制方法的研究。试验表明,燃烧中的离子信号在火焰前锋与后区存在两个峰值,其峰值以及分别到达该峰值的时间均与空燃比有关,但其关系并非单值,在相对空燃比等于1附近信号峰值达极大值,而到达峰值时间达极小值。通过增加少量供油量,并对其油量变化前后信号时间大小的计算,提出了一种能有效判断混合气是处于浓或稀混合区的软件识别法。当空燃比在控制范围外采用分段法根据公式直接计算出所需的燃料,而当空燃比已经在控制范围内,则采用定值法,并选取较小的供油量,以同时满足控制效率和精度的要求。