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.

The Possibility of Active Attitude Control for Fuel Spray

The internal combustion engine (ICE) is an attractive power source for automobiles, with its superior storability, transportability, and suppliability of liquid fuel with high energy density. Compact ICEs with high performance and a low environmental load are greatly needed. In the future, smart active control of combustion by means of fuel spray injection must be considered as a breakthrough technology to address serious issues related to conventional ICEs, such as emissions. A designed fuel injection rate and spray pattern during the injection period have been technically developed, and combustion can be partially controlled in the conventional ICE. However, spatial fuel distribution is not progressing as desired in the field of combustion;thus, new and effective active control technologies for fuel spray are very necessary for the smart control of combustion. Cavitation, flash boiling, spray-to-spray interaction, spray-to-wall interaction, and air flow have potential as a basis for active attitude control of fuel spray. This article uses evidence from the literature to discuss the possibility of active spray attitude control for future fuel spray combustion technology in a smart compact ICE.

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.

Output Tracking Control of a Hydrogen-air PEM Fuel Cell

Hydrogen-air proton exchange membrane(PEM)fuel cell is a promising clean energy. However, the stack output tracking control is still a challenging problem due to the soft characteristic of the stack. Both over-and less-control will cause the stack flooding or oxygen lacking which dramatically decreases the life of stacks. Traditional control methods rely on the accurate model of the fuel cell system, which is a high-order nonlinear system, and involve a complex controller design process. This paper combines the data-based fuzzy cluster modeling technology with the sliding mode control and the integral actions. The sliding mode controller tracks the dynamic changes of the fuel cell system and the integral controller eliminates the steady-state errors. Simulation results demonstrate good performance of the proposed control method.

Influence of Pre-injection Control Parameters on Main-injection Fuel Quantity for an Electronically Controlled Double-valve Fuel Injection System of Diesel Engine

一个模拟模型一电子地控制了二个螺线管阀门燃料注射系统因为一台柴油机引擎在 AMESim 环境被建立。模型的精确性与试验性的数据通过比较被验证。在不同控制模式下面的主要注射的数量上的注射前控制参数的影响被分析。在喷洒控制阀门模式，主要注射的燃料数量逐渐地减少然后因为多注射居住时间的增加，到达稳定的水平。在针控制阀门模式，主要注射的燃料数量与升起的多注射居住时间增加；这效果在高速度的革命和大主要注射的脉搏宽度变得更明显。注射前脉搏宽度没在二个控制模式下面在主要注射的数量上有明显的影响；在主要注射的数量的变化在 1 mm3 的范围。

Development of fuzzy control of a fuel cell generation system using FPGA

Afuzzy controller based oni mproved Generalized-Membership-Function(GMF) algorithmfor afuel cell generationsys-tem wasintroduced.Under the demands on control in application of the converter,a Field Programmable Gate Array(FPGA) re-alization method to manage the power flow was given.This control systembased onthe proposed modified GMF was proved to bea universal approxi mation systemin theory.The fuzzy control technique was combined with Eletronic Design Automatic(EDA)technique and a paralleling fuzzy controller was i mplemented in FPGA.Paralleling fuzzy controller based oni mproved GMF algo-rithm wasi mplemented on a Cyclone FPGA.The result of si mulation based on QuartusII confirmed the validity of the proposed method.

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.

Intelligent Control for Improvements in PEM Fuel Cell Flow Performance

The performance of fuel cells and the vehicle applications they are embedded into depends on a delicate balance of the correct temperature, humidity, reactant pressure, purity and flow rate. This paper successfully investigates the problem related to flow control with implementation on a single cell membrane electrode assembly （MEA）. This paper presents a systematic approach for performing system identification using recursive least squares identification to account for the non-linear parameters of the fuel cell. Then, it presents a fuzzy controller with a simplified rule base validated against real time results with the existing flow controller which calculates the flow required from the stoichiometry value.

Structure and Control Strategies of Fuel Cell Vehicle

The structure and kinds of the fuel cell vehicle (FCV) and the mathematical model of the fuel cell processor are discussed in detail. FCV includes many parts: the fuel cell thermal and water management, fuel supply, air supply and distribution, AC motor drive, main and auxiliary power management, and overall vehicle control system. So it requires different kinds of control strategies, such as the PID method, zero-pole method, optimal control method, fuzzy control and neural network control. Along with the progress of control method, the fuel cell vehicle's stability and reliability is up-and-up. Experiment results show FCV has high energy efficiency.

Control-oriented dynamic fuzzy model and predictive control for proton exchange membrane fuel cell stack

Proton exchange membrane fuel cell (PEMFC) stack temperature and cathode stoichiometric oxygen are very important control parameters. The performance and lifespan of PEMFC stack are greatly dependent on the parameters. So, in order to improve the performance index, tight control of two parameters within a given range and reducing their fluctuation are indispensable. However, control-oriented models and control strategies are very weak junctures in the PEMFC development. A predictive control algorithm was presented based on their model established by input-output data and operating experiences. It adjusts the operating temperature to 80 ℃. At the same time, the optimized region of stoichiometric oxygen is kept between 1.8?2.2. Furthermore, the control algorithm adjusts the variants quickly to the destination value and makes the fluctuation of the variants the least. According to the test results, compared with traditional fuzzy and PID controllers, the designed controller shows much better performance.

ESO-based robust predictive control of lunar module with fuel sloshing dynamics

An extended-state-observer(ESO) based predictive control scheme is proposed for the autopilot of lunar landing.The slosh fuel masses exert forces and torques on the rigid body of lunar module(LM),such disturbances will dramatically undermine the stability of autopilot system.The fuel sloshing dynamics and uncertainties due to the time-varying parameters are considered as a generalized disturbance which is estimated by an ESO from the measured attitude signals and the control input signals.Then a continuous-time predictive controller driven by the estimated states and disturbances is designed to obtain the virtual control input,which is allocated to the real control actuators according to a deadband logic.The 6-DOF simulation results reveal the effectiveness of the proposed method when dealing with the fuel sloshing dynamics and parameter perturbations.

Safe Controlled Storage of SVBR-100 Spent Nuclear Fuel in the Extended-Range Future

Experience of operating reactor facilities (RF) with lead-bismuth coolant (LBC) has revealed that it is possible to perform safe refueling in short terms if the whole core is replaced and a kit of the special refueling equipment is used. However, comparing with RFs of nuclear submarines (NS), in which at the moment of performance of refueling the residual heat release is small, at RF SVBR-100 in a month after the reactor has been shut down, at the moment of performance of refueling the residual heat release is about 500 kW. Therefore, it is required to place the spent removable unit (SRU) with spent fuel subassemblies (SFSA) into the temporal storage tank (TST) filled with liquid LBC, in which the conditions for coolant natural circulation (NC) and heat removal via the tank vessel to the water cooling system are provided. After the residual heat release has been lowered to the level allowing transportation of the TST with SRU in the transporting-package container (TPC), it is proposed to consider a variant of TPCs transportation to the special site. On that site after the SRU has been reloaded into the long storage tank (LST) filled with quickly solidifying liquid lead, the TPCs can be stored during the necessary period. Thus, the controlled storage of LSTs is realized during several decades untill the time when SNF reprocessing and NFC closing are becoming economically expedient. On that storage, the four safety barriers are formed on the way of the release of radioactive products into the environment, namely: fuel matrix, fuel element cladding, solid lead and steel casing of the LST.

Hybrid Dynamic Modeling and Control of Molten Carbonate Fuel Cell Stack Shutdown

A hybrid automaton modeling approach that incorporates state space partitioning, phase dynamic modeling and control law synthesis by control strategy is utilized to develop a hybrid automaton model of molten carbonate fuel cell (MCFC) stack shutdown. The shutdown operation is divided into several phases and their boundaries are decided according to a control strategy, which is a set of specifications about the dynamics of MCFC stack during shutdown. According to the control strategy, the specification of increasing stack temperature is satisfied in a phase that can be modeled accurately. The model for phase that has complex dynamic is approximated. The duration of this kind of phase is decreased to minimize the error caused by model approximation.

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.

Dynamic Thermal Model and Temperature Control of Proton Exchange Membrane Fuel Cell Stack

A dynamic thermal transfer model of a proton exchange membrane fuel cell (PEMFC) stack is developed based on energy conservation in order to reach better temperature control of PEMFC stack. Considering its uncertain parameters and disturbance, we propose a robust adaptive controller based on backstepping algorithm of Lyaponov function. Numerical simulations indicate the validity of the proposed controller.

Control system design of hybrid fuel cell city bus

This paper introduced the design of the hybrid powertrain of the Fuel Cell City Bus demonstrated in 2008 Beijing Olympic Games. The configuration of the hybrid fuel cell powertrain was introduced. The safety of hydrogen storage and delivery system, the hydrogen leakage alarm system were developed. The real-time distributed control and diagnosis system based on the Time Trigger Controller Area Network (TTCAN) with 10 ms basic control period was developed. The concept and implementation of processor (or controller) monitor and process (or task) monitor technique based on the TTCAN were applied in this paper. The fault tolerant control algorithm of the fuel cell engine and the battery management system were considered. The demonstration experience verified that the fault tolerant control was very important for the fuel cell city bus.

Particle Swarm Optimization based predictive control of Proton Exchange Membrane Fuel Cell (PEMFC)

Proton Exchange Membrane Fuel Cells (PEMFCs) are the main focus of their current development as power sources because they are capable of higher power density and faster start-up than other fuel cells. The humidification system and output performance of PEMFC stack are briefly analyzed. Predictive control of PEMFC based on Support Vector Regression Machine (SVRM) is presented and the SVRM is constructed. The processing plant is modelled on SVRM and the predictive control law is obtained by using Particle Swarm Optimization (PSO). The simulation and the results showed that the SVRM and the PSO re-ceding optimization applied to the PEMFC predictive control yielded good performance.

Adaptive inverse control of air supply flow for proton exchange membrane fuel cell systems

To prevent the oxygen starvation and improve the system output performance, an adaptive inverse control （AIC） strategy is developed to regulate the air supply flow of a proton exchange membrane fuel cell （PEMFC） system in this paper. The PEMFC stack and the air supply system including a compressor and a supply manifold are modeled for the purpose of performance analysis and controller design. A recurrent fuzzy neural network （RFNN） is utilized to identify the inverse model of the controlled system and generates a suitable control input during the abrupt step change of external disturbances. Compared with the PI controller, numerical simulations are performed to validate the effectiveness and advantages of the proposed AIC strategy.

航空发动机燃油控制装置可靠性研究综述

航空发动机燃油控制装置是航空发动机的核心控制单元,长期服役在高温、高压、强振的恶劣环境,在航空发动机外场使用中故障率占比高,产品的寿命及可靠性是当前制约我国装备能力提升的短板。本文总结了当前燃油控制装置的典型故障类型,对比分析了国内外在燃油控制装置可靠性设计与分析技术、可靠性优化技术、寿命试验技术及可靠性评估技术方面的研究进展;剖析了我国燃油控制装置可靠性技术研究及应用方面的不足及原因,同时结合航空发动机正向研发体系建设需要,指出了航空发动机自主创新设计中燃油控制装置性能及可靠性一体化设计所面临的技术难点和挑战,并立足于现有国内设计水平及工业基础,给出了夯实我国航空燃油控制装置设计能力需开展的基础性研究建议。