A neural-network based control solution to air-fuel ratio control for automotive fuel-injection systems

Maximization of the catalyst efficiency in automotive fuel-injection engines requires the design of accurate control systems to keep the air-to-fuel ratio at the optimal stoichiometric value AF/sub S/. Unfortunately, this task is complex since the air-to-fuel ratio is very sensitive to small perturbations of the engine parameters. Some mechanisms ruling the engine and the combustion process are in fact unknown and/or show hard nonlinearities. These difficulties limit the effectiveness of traditional control approaches. In this paper, we suggest a neural based solution to the air-to-fuel ratio control in fuel injection systems. An indirect control approach has been considered which requires a preliminary modeling of the engine dynamics. The model for the engine and the final controller are based on recurrent neural networks with external feedbacks. Requirements for feasible control actions and the static precision of control have been integrated in the controller design to guide learning toward an effective control solution.     

Hybrid Model Predictive Control of Direct Injection Stratified Charge Engines

This paper illustrates the application of hybrid modeling and model predictive control techniques to the management of air-to-fuel ratio and torque in advanced technology gasoline direct-injection stratified-charge (DISC) engines. A DISC engine is an example of a constrained hybrid dynamical system, because it can operate in two distinct modes (stratified and homogeneous) and because the mode-dependent constraints on the air-to-fuel ratio and on the spark timing need to be enforced during its operation to avoid misfire, knock, and high combustion variability. In this paper, we approximate the DISC engine dynamics as a two-mode discrete-time switched affine system. Using this approximation, we tune a hybrid model predictive controller with integral action based on online mixed-integer quadratic optimization, and show the effectiveness of the approach through simulations. Then, using an offline multiparametric optimization procedure, we convert the controller into an equivalent explicit piecewise affine form that is easily implementable in an automotive microcontroller through a lookup table of linear gains.     

Adaptive and Learning Control for SI Engine Model With Uncertainties

Air--fuel ratio control is a challenging control problem for port-fuel-injected and throttle-body-fuel-injected spark ignition (SI) engines, since the dynamics of air manifold and fuel injection of the SI engines are highly nonlinear and often with unmodeled uncertainties and disturbance. This paper presents nonlinear control approaches for multi-input multi-output engine models, by developing adaptive control and learning control design methods. Theoretical proofs are established that ensure that proposed controllers are able to give asymptotical tracking performance. As a comparison, the method applying global linearizing controller can give accurate tracking for the engine model without uncertainty and disturbance, but it fails to keep tracking performance when uncertainty is incorporated into the system. Adaptive control and learning control approaches are capable of dealing with both constant uncertainty and time-varying periodic uncertainty. Simulation results illustrate the efficacy of the proposed controllers.      

车用甲醇汽油燃烧控制器

为了解决甲醇汽油燃料在汽车发动机上冷启动困难,使用范围小等问题,提出了一种带有温度检测的自适应型补偿喷油控制方法,并基于MC9S12系列单片杌完成了控制器的设计。该控制器主要通过采集发动机启动时的进气口温度和转速,实时的调整汽车ECU原始喷油信号的有效喷油时长,使发动机快速平稳的启动,最终实现多比例甲醇汽油在汽车发动机上对汽油的替代。实验应用表明,该控制器具有冷启动顺利、适应燃料多样、控制精确、运行平稳安全、节约燃料开支、节能减排的特点,达到了设计要求。     

An automotive engine calibration system using microcomputer

An automotive engine calibration system has been developed to aid in development and evaluation of a control algorithm for electronic spark advance. It consists of the programmer, controller, and measurement units. Given the spark advance and the dwell time in the form of function subroutines written in BASIC, the programmer unit makes the advance and dwell tables as a function of engine speed and load. Referring to these tables, the controller unit operates the engine under calibration. The measurement unit measures the resultant engine performance and anlayzes the control algorithm. This process is repeated until the optimum algorithm is reached. A few test examples are also presented to demonstrate the system capability. This system features an easy operation and an accurate calibration.     

A new strategy for traction control in turning via engine modeling

The driving stability is affected by driven wheel slip, which can be controlled by the driven wheel torque. In a vehicle powered by an internal combustion engine, the torque can be controlled by an engine management system. The sliding mode algorithm is the mechanism behind the design of the traction control system (TCS). The longitudinal slip is controlled by the position of the throttle valve. The vehicle model used has seven degrees of freedom and a two-state engine model, i.e., the mass of air in the intake manifold and the engine speed. Time-delay transport is considered in the engine model used. A nonlinear tire model for combined slip is used for tire force computation. Due to the nonlinear dynamic of the tire, vehicle, and engine, the control method of sliding mode is used for its robustness. A controller is designed based on the dynamic surface control, for which two first-order surfaces are defined. The effectiveness of the controller is demonstrated with simulation results for different maneuvers. Results show that for different road conditions, the acceleration performance, directional stability, and steerability of a vehicle equipped with TCS is improved. The reason is that the slip is controlled by keeping it in a desired range     

Fuzzy Gain-Scheduling Proportional–Integral Control for Improving Engine Power and Speed Behavior in a Hybrid Electric Vehicle

With the increased emphasis on improving fuel economy and reducing emissions, hybrid electric vehicles (HEVs) have emerged as very strong candidates to achieve these goals. The power-split hybrid system, which is a complex hybrid powertrain, exhibits great potential to improve fuel economy by determining the most efficient regions for engine operation and thereby high-voltage (HV) battery operation to achieve overall vehicle efficiency optimization. To control and maintain the actual HV battery power, a sophisticated control system is essential, which controls engine power and thereby engine speed to achieve the desired HV battery maintenance power. Conventional approaches use proportional-integral (PI) control systems to control the actual HV battery power in power-split HEV, which can sometimes result in either overshoots of engine speed and power or degraded response and settling times due to the nonlinearity of the power-split hybrid system. We have developed a novel approach to intelligently controlling engine power and speed behavior in a power-split HEV using the fuzzy control paradigm for better performances. To the best of our knowledge, this is the first reported use of the fuzzy control method to control engine power and speed of a power-split HEV in the applied automotive field. Our approach uses fuzzy gain scheduling to determine appropriate gains for the PI controller based on the system's operating conditions. The improvements include elimination of the overshoots as well as approximate 50% faster response and settling times in comparison with the conventional linear PI control approach. The improved performances are demonstrated through simulations and field experiments using a ford escape hybrid vehicle.     

Engine performance evaluation using a combustion probe signal analyzer

A two-channel combustion probe signal analyzer to detect variations in the combustion quality in spark ignition engines was built and its performance investigated. The combustion probe signal was obtained by applying a small positive bias to the center electrode of the spark plug of interest. This was accomplished by the insertion of an adaptor between the distributor cap and the spark plug wire. Use of the adapter showed no apparent effect on engine operating characteristics. Experiments investigating the correlation between several engine operating parameters and the combustion quality parameters "impaired combustion" and "slow combustion" were carried out. The parameters varied were A/F (air to fuel ratio), spark advance, engine speed, nonenriched cold start, and NOxand hydrocarbon concentrations in the exhaust. Dynamometer mounted 400 CID production engine was used. Good agreement was found to exist between the variation in the combustion probe signal analyzer's counts and progressively induced impairments of the combustion process.     

高功率微波车辆迫停的作用机理及效应试验

通过定量测定车辆电子控制单元喷油控制和点火信号的变化规律,揭示了微波导致发动机熄火的作用机理。试验结果表明,车辆在强电磁脉冲辐射条件下,电子控制单元喷油输出信号发生紊乱,点火信号意外丢失,发动机气缸内混入过量汽油造成火花塞无法点燃油气混合物,导致发动机被迫熄火。     

基于电磁驱动气门的气动发动机转速控制研究

分析了活塞式空气动力发动机的工作原理与过程。针对进、排气量对发动机转速的影响,采用电磁直接驱动进、排气门的方式控制工作气缸的气量,提出了一种新的转速控制策略实现对发动机转速控制。建立了空气动力发动机控制系统实验模型,对控制效果进行实验研究和验证。实验结果表明,在转速变化时,控制系统具有良好的实时跟踪和响应特性,在转速变化不大时,优于传统的控制方式。为进一步的深入研究,针对实验中遇到的问题,也提出了对实验方法和控制策略的一些改进措施。     

基于AT Tiny13的智能点火控制器设计

本文介绍以AT Tiny13单片机为核心设计了小型汽油发动机使用的低成本的点火控制器,并进行硬件及软件结合设计,达到精确地控制点火提前角.此系统解决了无触点磁电机电容放电点火系统(CDI)和无触点蓄电池式晶体管点火系统低速断火和高速失火问题,并且具有降低油耗、降低成本优点.     

Prime sensors for electronic automotive-engine control

Sensors faithfully transduce automotive control parameters into electric signals suitable for transmission to the electronic controls. Two parameters key to engine control are crankshaft position and manifold absolute pressure, which are used in both fuel and ignition control systems. This paper describes a variety of sensor concepts for each of the two parameters, and provides guidelines for expediting screening tests. The case for including sensor selection as an integral part of system trade-off studies is also argued.     

缸内直喷航空活塞发动机试验ECU平台设计

目前航空活塞发动机依然是无人机的主要动力来源,为了追求更好的动力及续航能力,缸内直喷技术成为众多改进方案的首选。为了研究缸内直喷发动机的喷射规律和控制策略,设计了基于DSP的电子控制系统硬件平台。控制系统由TMS320F28335数字信号处理器、电源模块、正时模块、控制量及修正模块、驱动模块和通信模块组成。实物在回路仿真试验和台架试验表明:该控制系统能够实时监测发动机工作状态,任意调整喷油、喷气及点火的各项参数,有效控制发动机的输出功率,满足了系统设计的需要。     

The application of neural networks to fuel processors for fuel-cellvehicles

Passenger vehicles fueled by hydrocarbons or alcohols and powered by proton exchange membrane (PEM) fuel cells address world air quality and fuel supply concerns while avoiding hydrogen infrastructure and on-board storage problems. Reduction of the carbon monoxide concentration in the on-board fuel processor's hydrogen-rich gas by the preferential oxidizer (PrOx) under dynamic conditions is crucial to avoid poisoning of the PEM fuel cell's anode catalyst and thus malfunction of the fuel-cell vehicle. A dynamic control scheme is proposed for a single-stage tubular cooled PrOx that performs better than, but retains the reliability and ease of use of, conventional industrial controllers. The proposed hybrid control system contains a cerebellar model articulation controller artificial neural network in parallel with a conventional proportional-integral-derivative (PID) controller. A computer simulation of the preferential oxidation reactor was used to assess the abilities of the proposed controller and compare its performance to the performance of conventional controllers. Realistic input patterns were generated for the PrOx by using models of vehicle power demand and upstream fuel-processor components to convert the speed sequences in the Federal Urban Driving Schedule to PrOx inlet temperatures, concentrations, and flow rates. The proposed hybrid controller generalizes well to novel driving sequences after being trained on other driving sequences with similar or slower transients. Although it is similar to the PID in terms of software requirements and design effort, the hybrid controller performs significantly better than the PID in terms of hydrogen conversion setpoint regulation and PrOx outlet carbon monoxide reduction     

Adaptive sliding controller with self-tuning fuzzy compensation for vehicle suspension control

Since the hydraulic actuating suspension system has nonlinear and time-varying behavior, it is difficult to establish an accurate dynamic model for a model-based sliding mode control design. Here, a novel model-free adaptive sliding controller is proposed to suppress the position oscillation of the sprung mass in response to road surface variation. This control strategy employs the functional approximation technique to establish the unknown function for releasing the model-based requirement. In addition, a fuzzy scheme with online learning ability is introduced to compensate the functional approximation error for improving the control performance and reducing the implementation difficulty. The important advantages of this approach are to achieve the sliding mode controller design without the system dynamic model requirement and release the trial-and-error work of selecting approximation function. The update laws for the coefficients of the Fourier series functions and the fuzzy tuning parameters are derived from a Lyapunov function to guarantee the control system stability. The experimental results show that the proposed control scheme effectively suppresses the oscillation amplitude of the vehicle sprung mass corresponding to the road surface variation and external uncertainties, and the control performance is better than that of a traditional model-based sliding mode controller.     

Throttle-control algorithm for improving engine response based on air-intake model and throttle-response model

An electric-throttle-control actuator (ETC) is a device for control of the air mass flow to an engine cylinder. As adaptive-cruise-control and direct-fuel-injection systems become popular, the market of ETC has become larger. The ETC is controlled so that the engine torque follows the target value. Between the change of the control signal to the ETC and the engine-torque response, two delays exist-the delay in the throttle response and manifold filling. These delays must be compensated to improve the engine response. In this paper, a throttle-control algorithm for improving engine response is proposed. This algorithm compensates these two delays based on the response model. The response of the manifold pressure was experimented in two cases, when the ETC was controlled by a step input and when the throttle was controlled by the developed algorithm. The experimental results show that the rise time of the manifold pressure response decreased to one-tenth by the developed algorithm. Because the engine torque is proportional to the manifold pressure, it can be concluded that the torque response improved by compensating the two delay factors.     

Reference feedforward in the idle speed control of a direct-injection spark-ignition engine

The direct-injection spark-ignition engine has emerged as a focus of research in improving fuel economy and controlling emissions. This engine can operate in multiple modes, including a stratified charge mode with an air-fuel ratio as large as 50:1. Operating in stratified mode results in improved fuel economy and reduced CO/sub 2/ emissions. The stratified charge mode is employed during low speed and load conditions, such as during engine idle. The idle speed control problem is cast as a two-input-two-output control problem and a baseline feedback controller is developed based on an existing topology from the literature. Significant delays, however, inhibit our ability to improve the transient response via feedback alone. An improved scheme employing reference feedforward is proposed and several potential topologies are presented. A reference feedforward algorithm is derived and nonlinear simulation results are shown in which the system transient responses are improved considerably.     

内燃机激光多点点火技术研究进展

稀薄燃烧能够提高内燃机的热效率并降低污染物的排放, 但稀薄燃烧的火焰传播速度慢且在高压下易出现局部淬火现象。激光诱导火花点火能够有效解决燃料在低当量比和高压下燃烧遇到的问题，此外激光点火能够实现多点点火从而缩短燃烧时间并增大燃烧室压力, 相较于传统的电火花塞点火技术具有很大优势。锥形腔、衍射透镜、空间光调制器和达曼光栅均已被用于实现多点激光诱导火花点火。归纳了多点激光诱导火花点火的几种技术途径，讨论了内燃机多点激光诱导火花点火的研究状况和最新成果。对实现多点激光诱导火花点火的几种方法进行了评价，并指出了每种方法在多点激光诱导火花点火中的优势和需要解决的问题。在此基础上，对内燃机激光多点点火技术的研究前景进行了展望。     

基于Dahlin算法变风量空调自校正PID控制

变风量空调具有时变、延时、非线性等特点,在此类系统中传统的PID控制算法难以取得最佳的控制效果.基于广义预测自校正的控制算法,控制精度高,具有较强的跟踪性能,但是以增大的计算量和频繁的调节系统参数为代价的.文中提出一种基于改进的Dahlin参数整定方法的自校正PID控制器,该算法在理论建模的基础上,采用在线的带遗忘因子最小二乘法,实现传递函数的参数估计,建立了系统PID参数之间的关系式,实现变风量空调系统的末端控制.算法仿真运算及实验表明,与传统PID及广义预测自校正控制方法相比,文中方法控制精度高于传统PID,同时计算复杂度低于通常广义预测自校正控制.     

Design and control of a brushless DC limited-angle torque motor with its application to fuel control of small-scale gas turbine engines

This paper presents techniques for design and control of a brushless direct-current (DC) limited-angle torque motor (LATM) with its application to fuel control of gas turbine engines. Given the desired specifications, a two-pole brushless DC LATM with a toroidally wound armature is designed using selected ferromagnetic material and rare-earth permanent magnets; its electromagnetic characteristics is then computationally found and well tuned using the finite element method (FEM) in order to ensure whether the design meets the performance specifications. To achieve the simple and inexpensive semi-closed-loop fuel control, a robust position controller (including a proportional-integral-derivative (PID) controller with a prefilter) is synthesized for providing the required positioning performance for the developed motor, thereby achieving an inexpensive semi-closed-loop fuel control. A closed-loop fuel controller associated with the proposed position controller and a flow meter is then proposed based on multi-loop control structure in order to achieve required linear input–output relationship. All the proposed fuel control laws were implemented using a stand-alone single-chip digital signal processor (DSP). Experimental results are conducted to show the efficacy and usefulness of the developed limited-angle torque motor with its application to an experimental gas turbine fuel control test platform.