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...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.展开更多
Thermodynamic characteristics are of great importance for the performance of a high-temperature flow-rate control valve,as high-temperature environment may bring problems,such as blocking of spool and increasing of le...Thermodynamic characteristics are of great importance for the performance of a high-temperature flow-rate control valve,as high-temperature environment may bring problems,such as blocking of spool and increasing of leakage,to the valve.In this paper,a high-temperature flow-rate control valve,pilot-controlled by a pneumatic servo system is developed to control the fuel supply for scramjet engines.After introducing the construction and working principle,the thermodynamic mathematical models of the valve are built based on the heat transfer methods inside the valve.By using different boundary conditions,different methods of simulations are carried out and compared.The steady-state and transient temperature field distribution inside the valve body are predicted and temperatures at five interested points are measured.By comparing the simulation and experimental results,a reasonable 3D finite element analysis method is suggested to predict the thermodynamic characteristics of the high-temperature flow-rate control valve.展开更多
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-l...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.展开更多
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 A...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.展开更多
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...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.展开更多
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 in...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.展开更多
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, a...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.展开更多
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 refuelin...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.展开更多
Accurate fuel injection control of aircraft engine can optimize the energy efficiency of UAV power system while meeting the propeller speed requirement. Traditional injection control method such as open-loop calibrati...Accurate fuel injection control of aircraft engine can optimize the energy efficiency of UAV power system while meeting the propeller speed requirement. Traditional injection control method such as open-loop calibration causes instability of fuel supply which brings the risk of power loss of UAV. Considering that the closed-loop control of AFR can ensure a stable fuel feeding, this paper proposes an AFR control based fuel supply strategy in order to improve the efficiency of fuel-powered UAV while obtaining the required engine speed. According to the optimum fuel injection results, we implement fuzzy-PID method to control the set AFR in different situations. Through simulation and experiment studies, the results indicate that, to begin with, the calibrated mathematical model of the aircraft engine is effective. Next, this fuel supply strategy based on AFR control can normally realize the engine speed regulation, and the applied control algorithm can eliminate the overshoot of AFR throughout all the working progress. What is more,the fuel supply strategy can averagely shorten the response time of the engine speed by about two seconds. In addition, compared with the open-loop calibration, in this work the power efficiency is improved by 9% to 33%. Last but not the least, the endurance can be improved by 30 min with a normal engine speed. This paper can be a reference for the optimization of UAV aircraft engine.展开更多
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) ...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.展开更多
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 calculatio...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.展开更多
Long departure-taxi-out time leads to significant airport surface congestion, fuel-burn costs, and excessive emissions of greenhouse gases. To reduce these undesirable effects, a Predicted taxi-out time-based Dynamic ...Long departure-taxi-out time leads to significant airport surface congestion, fuel-burn costs, and excessive emissions of greenhouse gases. To reduce these undesirable effects, a Predicted taxi-out time-based Dynamic Pushback Control(PDPC) method is proposed. The implementation of this method requires two steps: first, the taxi-out times for aircraft are predicted by the leastsquares support-vector regression approach of which the parameters are optimized by an introduced improved Firefly algorithm. Then, a dynamic pushback control model equipped with a linear gate-hold penalty function is built, along with a proposed iterative taxiway queue-threshold optimization algorithm for solving the model. A case study with data obtained from Beijing International airport(PEK) is presented. The taxi-out time prediction model achieves predictive accuracy within 3 min and 5 min by 84.71% and 95.66%, respectively. The results of the proposed pushback method show that total operation cost and fuel-burn cost achieve a 14.0% and 21.1%reduction, respectively, as compared to the traditional K-control policy.(3) From the perspective of implementation, using PDPC policy can significantly reduce the queue length in taxiway and taxi-out time. The total operation cost and fuel-burn cost can be curtailed by 37.2% and 52.1%,respectively, as compared to the non-enforcement of any pushback control mechanism. These results show that the proposed pushback control model can reduce fuel-burn costs and airport surface congestion effectively.展开更多
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） s...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.展开更多
Pebble bed reactors use cycling scheme of spherical fuel elements relying on fuel elements cycling system (FECS). The structure and control logic of FECS are very complex. Each control link has strict requirements on ...Pebble bed reactors use cycling scheme of spherical fuel elements relying on fuel elements cycling system (FECS). The structure and control logic of FECS are very complex. Each control link has strict requirements on time and sequence. This increases the difficulties of description and analysis. In this paper, timed places control Petri nets (TPCPN) is applied for the modeling of FECS. On this basis the simulation of two important processes, namely uploading fuel elements into the core for the first time and emptying the core is finished by simulation software Arena. The results show that as TPCPN is able to describe different kinds of logic relationship and has time properties and control properties, it’s very suitable for the modeling and analysis of FECS.展开更多
This paper describes a research project that uses embedded systems design principles to construct and simulate an Engine Control Unit （ECU） for a hybrid car. The ECU is designed to select a fuel type based on the st...This paper describes a research project that uses embedded systems design principles to construct and simulate an Engine Control Unit （ECU） for a hybrid car. The ECU is designed to select a fuel type based on the stress level of the simulated engine. The primary goal of the project was to use a robotics kit, connected to sensors, to simulate a hybrid car under certain stress conditions such as hill climbing or full throttle. The project uses the LEGO~ Mindstorms~ NXT robotics kit combined with a Java-based firmware, a pressure sensor to simulate a gas pedal, and a tilt sensor to determine when the car is traveling uphill or downhill. The objective was to develop, through simulation, a framework for adjusting the ratios/proportions of fuel types and mixture under the stress conditions. The expected result was to establish a basis for determining the ideal/optimal fuel-mix-stress ratios on the hybrid car＇s performance. Using the NXT robotics kit abstracted the low level details of the embedded system design, which allowed a focus on the high level design details of the research. Also, using the NXJ Java-based firmware allowed the incorporation of object oriented design principles into the project. The paper outlines the evolution and the compromises made in the choice of hardware and software components, and describes the computations and methodologies used in the project.展开更多
针对P1P3构型混联式混合动力汽车(hybrid electric vehicles,HEVs)的能量管理问题,本文提出一种基于模型预测控制(model predictive control,MPC)的能量管理策略。首先,根据控制算法构建系统预测模型,使用二次规划算法优化求解车辆最小...针对P1P3构型混联式混合动力汽车(hybrid electric vehicles,HEVs)的能量管理问题,本文提出一种基于模型预测控制(model predictive control,MPC)的能量管理策略。首先,根据控制算法构建系统预测模型,使用二次规划算法优化求解车辆最小化油耗的优化问题;然后,利用MATLAB/Simulink仿真平台,在2种标准循环工况下对本文所提出的能量管理控制策略进行仿真验证,并与基于规则的能量管理控制策略进行了对比分析。结果表明,相对于基于规则的控制策略,采用基于MPC的控制策略在2种循环工况下的车辆百公里油耗分别降低了5.6%和5.2%,可有效提升燃油经济性。展开更多
文摘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.
文摘Thermodynamic characteristics are of great importance for the performance of a high-temperature flow-rate control valve,as high-temperature environment may bring problems,such as blocking of spool and increasing of leakage,to the valve.In this paper,a high-temperature flow-rate control valve,pilot-controlled by a pneumatic servo system is developed to control the fuel supply for scramjet engines.After introducing the construction and working principle,the thermodynamic mathematical models of the valve are built based on the heat transfer methods inside the valve.By using different boundary conditions,different methods of simulations are carried out and compared.The steady-state and transient temperature field distribution inside the valve body are predicted and temperatures at five interested points are measured.By comparing the simulation and experimental results,a reasonable 3D finite element analysis method is suggested to predict the thermodynamic characteristics of the high-temperature flow-rate control valve.
文摘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.
文摘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.
基金supported by the National Natural Science Foundation of China (No. 51177138)the Research Fund for the Doctoral Program of High Education of China (No.20100184110015)Sichuan Province International Technology Cooperation and Exchange Program (No. 2012HH0007)
文摘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.
文摘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.
文摘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.
文摘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.
基金financially supported by the National Natural Science Foundation of China (No. 51605013)the Pneumatic and Thermodynamic Energy Storage and Supply Beijing Key Laboratory
文摘Accurate fuel injection control of aircraft engine can optimize the energy efficiency of UAV power system while meeting the propeller speed requirement. Traditional injection control method such as open-loop calibration causes instability of fuel supply which brings the risk of power loss of UAV. Considering that the closed-loop control of AFR can ensure a stable fuel feeding, this paper proposes an AFR control based fuel supply strategy in order to improve the efficiency of fuel-powered UAV while obtaining the required engine speed. According to the optimum fuel injection results, we implement fuzzy-PID method to control the set AFR in different situations. Through simulation and experiment studies, the results indicate that, to begin with, the calibrated mathematical model of the aircraft engine is effective. Next, this fuel supply strategy based on AFR control can normally realize the engine speed regulation, and the applied control algorithm can eliminate the overshoot of AFR throughout all the working progress. What is more,the fuel supply strategy can averagely shorten the response time of the engine speed by about two seconds. In addition, compared with the open-loop calibration, in this work the power efficiency is improved by 9% to 33%. Last but not the least, the endurance can be improved by 30 min with a normal engine speed. This paper can be a reference for the optimization of UAV aircraft engine.
文摘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.
基金supported by the Science and Technology Program of Beijing Municipal Education Commission(KM201611417009)the Project of Beijing Municipal Natural Science Foundation(4142018)the Importation and Development of High-Caliber Talents Project of Beijing Municipal Institutions(CIT&TCD20150314)
文摘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.
基金partially supported by the National Natural Science Foundation of China-Civil Aviation Joint Fund(Nos.U1533203,U1233124.)
文摘Long departure-taxi-out time leads to significant airport surface congestion, fuel-burn costs, and excessive emissions of greenhouse gases. To reduce these undesirable effects, a Predicted taxi-out time-based Dynamic Pushback Control(PDPC) method is proposed. The implementation of this method requires two steps: first, the taxi-out times for aircraft are predicted by the leastsquares support-vector regression approach of which the parameters are optimized by an introduced improved Firefly algorithm. Then, a dynamic pushback control model equipped with a linear gate-hold penalty function is built, along with a proposed iterative taxiway queue-threshold optimization algorithm for solving the model. A case study with data obtained from Beijing International airport(PEK) is presented. The taxi-out time prediction model achieves predictive accuracy within 3 min and 5 min by 84.71% and 95.66%, respectively. The results of the proposed pushback method show that total operation cost and fuel-burn cost achieve a 14.0% and 21.1%reduction, respectively, as compared to the traditional K-control policy.(3) From the perspective of implementation, using PDPC policy can significantly reduce the queue length in taxiway and taxi-out time. The total operation cost and fuel-burn cost can be curtailed by 37.2% and 52.1%,respectively, as compared to the non-enforcement of any pushback control mechanism. These results show that the proposed pushback control model can reduce fuel-burn costs and airport surface congestion effectively.
基金Project supported by the National Natural Science Foundation of China (Grant No.20576071)the Natural Science Foundation of Shanghai Municipality (Grant No.08ZR1409800)
文摘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.
文摘Pebble bed reactors use cycling scheme of spherical fuel elements relying on fuel elements cycling system (FECS). The structure and control logic of FECS are very complex. Each control link has strict requirements on time and sequence. This increases the difficulties of description and analysis. In this paper, timed places control Petri nets (TPCPN) is applied for the modeling of FECS. On this basis the simulation of two important processes, namely uploading fuel elements into the core for the first time and emptying the core is finished by simulation software Arena. The results show that as TPCPN is able to describe different kinds of logic relationship and has time properties and control properties, it’s very suitable for the modeling and analysis of FECS.
文摘This paper describes a research project that uses embedded systems design principles to construct and simulate an Engine Control Unit （ECU） for a hybrid car. The ECU is designed to select a fuel type based on the stress level of the simulated engine. The primary goal of the project was to use a robotics kit, connected to sensors, to simulate a hybrid car under certain stress conditions such as hill climbing or full throttle. The project uses the LEGO~ Mindstorms~ NXT robotics kit combined with a Java-based firmware, a pressure sensor to simulate a gas pedal, and a tilt sensor to determine when the car is traveling uphill or downhill. The objective was to develop, through simulation, a framework for adjusting the ratios/proportions of fuel types and mixture under the stress conditions. The expected result was to establish a basis for determining the ideal/optimal fuel-mix-stress ratios on the hybrid car＇s performance. Using the NXT robotics kit abstracted the low level details of the embedded system design, which allowed a focus on the high level design details of the research. Also, using the NXJ Java-based firmware allowed the incorporation of object oriented design principles into the project. The paper outlines the evolution and the compromises made in the choice of hardware and software components, and describes the computations and methodologies used in the project.
文摘针对P1P3构型混联式混合动力汽车(hybrid electric vehicles,HEVs)的能量管理问题,本文提出一种基于模型预测控制(model predictive control,MPC)的能量管理策略。首先,根据控制算法构建系统预测模型,使用二次规划算法优化求解车辆最小化油耗的优化问题;然后,利用MATLAB/Simulink仿真平台,在2种标准循环工况下对本文所提出的能量管理控制策略进行仿真验证,并与基于规则的能量管理控制策略进行了对比分析。结果表明,相对于基于规则的控制策略,采用基于MPC的控制策略在2种循环工况下的车辆百公里油耗分别降低了5.6%和5.2%,可有效提升燃油经济性。
