Air-fuel Ratio Control System Research Articles

Research on air-fuel ratio of rotary engines based on variable universe fuzzy control

Abstract A study on the air-fuel ratio control system for the Wankel rotary engine was conducted, where the overall model of the engine was developed in MATLAB/Simulink based on the mean value model. The variable universe fuzzy integral composite control algorithm was applied to feedback control, and the construction and simulation of the control algorithm were completed in MATLAB/Simulink. The results indicate that compared to PID control, variable universe fuzzy control reduced the engine’s fuel injection error by 60.37% and 35.7% under steady-state and transient conditions, respectively. This demonstrates the favorable control effectiveness of variable universe fuzzy control in rotary engines, providing insights and methods for future research on rotary engine control systems.

On error-driven nonlinear ESO based control design with application to air–fuel ratio control of engines

In this paper, the tracking control problem of the uncertain control system is studied in the frame of uncertainties estimation and compensation. To eliminate the influence of external disturbances and internal uncertainties on the control system, the error-driven nonlinear extended state observer (EDN-ESO), whose gain is set as an increasing function with respect to the absolute value of estimation error of the system output, is proposed to improve the estimation performance for the “total disturbance”. Next, both the estimation error of proposed ESO and the tracking error of system output are proven to be bounded by selecting the lower bound and variation range of ESO’s bandwidth. Moreover, the convergence of the estimation error as well as the tracking error to zero is proven under certain conditions. Finally, the proposed design method is applied to the air–fuel ratio control system of gasoline engines, and the experimental results show that the proposed EDN-ESO can effectively adjust the observer gain, so as to enhance the tracking performance.

Design of Active Fault-Tolerant Control System for Air-Fuel Ratio control of Internal Combustion engine using nonlinear regression-based observer model.

Internal Combustion (IC) engines are prevalent in the process sector, and maintaining sufficient Air-Fuel Ratio (AFR) regulation in their fuel system is crucial for enhanced engine performance, fuel economy, and environmental safety. Faults in the AFR system's sensors cause the engine to shut down, hence, fault tolerance is essential. In order to avoid engine shutdown, this paper offers a novel Active Fault-Tolerant Control System (AFTCS) for air-fuel ratio control of an Internal Combustion (IC) engine in a process plant. In the Fault Detection and Isolation (FDI) unit, the proposed AFTCS uses a nonlinear regression-based observer model for analytical redundancy. The suggested system was simulated in the MATLAB / Simulink environment. The proposed system was tested at two different speeds (300 r/min and 600 r/min) and the results show that the system's response is within the acceptable bound without compromising the stability. The findings also demonstrate the higher fault tolerance capability for sensor defects of the AFR control system, particularly for the MAP sensor (at 300 r/min) in terms of reduced oscillatory response in comparison to the current literature. Compared to the linear regression-based and Genetic Algorithm (GA) based model, the nonlinear regression-based model results in a more accurate estimation of the faulty sensors. The proposed model is also efficient in terms of computation power and response time.

Design of an Adaptive Control to Feed Hydrogen-Enriched Ethanol-Gasoline Blend to an Internal Combustion Engine

In this work, an internal combustion (IC) engine air-fuel ratio (AFR) control system is presented and evaluated by simulation. The control scheme aims to regulate the overall air-fuel ratio (AFRoverall) in an IC engine fueled with a hydrogen-enriched ethanol-gasoline blend (E10) as fast as possible. The control scheme designed and developed in this work considers two control laws, a feedback control law to regulate the hydrogen and adaptive nonlinear control law for controlling the E10 mass flow injection. The main contribution of this work is the reduction of the number of controllers used for controlling the overall air-fuel ratio since other control strategies use two controllers for controlling the E10 mass flow injection. Simulation results have shown the effectiveness of the new control scheme.

A Comparative Study of Design of Active Fault-Tolerant Control System for Air–Fuel Ratio Control of Internal Combustion Engine Using Particle Swarm Optimization, Genetic Algorithm, and Nonlinear Regression-Based Observer Model

In this article, three distinct strategies for designing an Active Fault-Tolerant Control System (AFTCS) for Air-Fuel Ratio (AFR) control of an Internal Combustion (IC) engine in a process plant to avoid engine shutdown, are presented. The proposed AFTCS employs a Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and a Nonlinear Regression (NLR)-based observer model in the Fault Detection and Isolation (FDI) unit for analytical redundancy. A comparison between these three proposed techniques is carried out to determine the least expensive and most accurate approach. The results show that the nonlinear regression produces highly accurate results by consuming very low computational power, and its response time is also very low as compared to GA and PSO. The results obtained show that NLR requires 99.6% and 93.1% less computational time for throttle and MAP estimation, respectively, by reducing the estimation error to as low as 0.01. The simulation of the proposed system is carried out in the MATLAB/Simulink environment. The results prove the superior fault tolerance performance for sensor faults of the AFR control system, especially for the Manifold Absolute Pressure (MAP) sensor in terms of less oscillatory response as compared to that reported in existing literature.

Genetic algorithm based active fault-tolerant control system for air fuel ratio control of internal combustion engines

Internal Combustion (IC) engines are commonly used in the process industry, and proper Air-Fuel Ratio (AFR) regulation in their fuel system is essential for improved engine performance, fuel efficiency, and environmental protection. Since faults in the sensors of the AFR system cause the engine to shut down, fault tolerance is essentially required for them. In this paper, an advanced Active Fault-Tolerant Control System (AFTCS) for AFR control of an IC engine is proposed to prevent the engine shutdown. For analytical redundancy, the proposed AFTCS uses the Genetic Algorithm (GA) based observer model in the Fault Detection and Isolation (FDI) unit to generate estimated value for the faulty sensors using the values of other healthy sensors. The proposed framework was simulated in the MATLAB/Simulink environment to verify its effectiveness. In comparison to previous literature works, the results show that the AFR control system has superior fault tolerance output for sensor faults, especially for the MAP sensor, in terms of less oscillatory response. Finally, a comparison of the proposed GA-based AFTCS was carried out with the existing literature works and its superior performance was elaborated.

Design of active fault-tolerant control system for Air-fuel ratio control of internal combustion engines using fuzzy logic controller.

Fault-Tolerant Control Systems (FTCS) are used in critical and safety applications to improve performance and stability despite failure modes. As a result, costly production losses related to unusual and unplanned shutdowns can be prevented by incorporating these systems in the critical process plant machines. The Internal Combustion (IC) engines are highly used process plant machines and faults in their sensors will cause their shutdown instigating the need to install FTCS in them. In this paper, an Active Fault-Tolerant Control System (AFTCS) based on a Fuzzy Logic Controller (FLC) is suggested to improve the reliability of the Air-Fuel Ratio (AFR) control system of an IC engine. For analytical redundancy, a nonlinear Fuzzy Logic (FL) based observer is implemented in the proposed system for the Fault Detection and Isolation (FDI) unit for nonlinear sensors of the AFR system. Lyapunov stability analysis was used for designing a stable system in both faulty and normal conditions. To evaluate its performance, this system was developed in the MATLAB/Simulink platform. The simulation results show that the developed system is robust under sensor fault conditions, retaining stability with a minimum decrease of AFR. This study's comparison with the existing literature demonstrates that the proposed system is effective for maintaining the AFR in IC engines during sensor faulty conditions thus reducing shutdown of engine and production loss for increased profits.

Robust Passive Fault Tolerant Control for Air Fuel Ratio Control of Internal Combustion Gasoline Engine for Sensor and Actuator Faults

This paper presents a novel Passive Fault Tolerant Control System (PFTCS) for Air Fuel Ratio (AFR) control system of the Internal Combustion (IC) gasoline engine to prevent its shutdown. A Proportional plus Integral (PI) controller with high feedback gain is implemented to control AFR by introducing a fuel throttle valve in the fuel line of the engine. The salient feature of the proposed controller is its less complex structure due to the absence of Analytical Redundancy (AR). Dual redundancy in the hardware is suggested for the sensors to prevent tripping in case of coincident faults in multiple sensors and for the actuator assembly to confiscate a single point of failure. The robustness of the proposed PFTCS is tested by introducing noise in the sensor measurements. MATLAB / Simulink environment simulation results demonstrate that the proposed PFTCS is robust to faults in normal as well as noisy conditions of the sensors without any degradation of AFR. The stability analysis of the proposed controller is performed by determining the poles of the closed-loop system. The reliability analysis of the proposed controller has been performed by calculating the probabilistic reliability function of the model. The comparison of the proposed model with the existing models has also been carried out to elaborate its effectiveness.

Design of Active Fault Tolerant Control System for Air Fuel Ratio Control of Internal Combustion Engines Using Artificial Neural Networks

Fault tolerant control systems can be used in the process machines such as Internal Combustion (IC) engines to achieve greater reliability and stability in the fault conditions. Thus, costly loss of production due to the unusual and unexpected shutdown of these machines can be avoided. The Air Fuel Ratio (AFR) control system is an important system in IC engines and faults in the sensors of this system will cause its shutdown creating costly production loss, therefore, fault tolerance is necessary for them. In this paper, an Active Fault Tolerant Control System (AFTCS) based on Artificial Neural Networks (ANN) has been proposed for the AFR control system of a Spark Ignition (SI) IC engine to increase its reliability. In the proposed AFTCS, a nonlinear ANN-based observer is used in the Fault Detection and Isolation (FDI) unit for the highly nonlinear sensors of the AFR system for analytical redundancy. The Lyapunov stability analysis has been utilized to design a stable system in normal and faulty conditions. The system has been implemented in MATLAB/Simulink environment to test its performance. The simulation experimental results demonstrate that the suggested system stays reliable maintaining the stability well in the fault conditions of sensors with little degradation in AFR. A comparison with the existing works demonstrates the superior performance of the proposed AFTCS for the highly nonlinear sensors of the AFR control system. The technique suggested is very effective in terms of fault robustness and is more specifically based on the nonlinear behavior of the MAP sensor compared to the existing works.

Enhanced intelligent proportional-integral-like fuzzy knowledge–based controller using chaos-enhanced accelerated particle swarm optimization algorithm for transient calibration of air–fuel ratio control system

The self-adaptive and highly robust proportional-integral-like fuzzy knowledge–based controller has been developed to regulate air–fuel ratio for gasoline direct injection engines, in order to improve the transient response behaviour and reduce the effort to be spent on calibration of parameter settings. However, even though the proportional-integral-like fuzzy knowledge–based controller can automatically correct the initially calibrated proportional and integral parameters, a more appropriate selection of controller parameter settings will lead to better transient performance. Thus, this article proposes an enhanced intelligent proportional-integral-like fuzzy knowledge–based controller using chaos-enhanced accelerated particle swarm optimization algorithm to automatically define the most optimal parameter settings. An alternative time-domain objective function is applied for the transient calibration programme without the need for prior selection of the search-domain. The real-time transient performance of the enhanced controller is investigated on the air–fuel ratio control system of a gasoline direct injection engine. The experimental results show that the enhanced proportional-integral-like fuzzy knowledge–based controller based on chaos-enhanced accelerated particle swarm optimization is able to damp out the oscillations with less settling time (up to 75% reduction) and less integral of absolute error (up to 64.07% reduction) compared with the conventional self-adaptive proportional-integral-like fuzzy knowledge–based controller. Repeatability tests indicate that the chaos-enhanced accelerated particle swarm optimization algorithm–based proportional-integral-like fuzzy knowledge–based controller is also able to reduce the mean value of objective function by up to 10.61% reduction and the standard deviation of the objective function by up to 28.29% reduction, compared with the conventional accelerated particle swarm optimization algorithm–based proportional-integral-like fuzzy knowledge–based controller.

Improved scheme of membership function optimisation for fuzzy air‐fuel ratio control of GDI engines

This study researches an improved scheme of membership function optimisation (MFO) for fuzzy air–fuel ratio (AFR) control of gasoline direct injection (GDI) engines based on correspondence analysis (CA). This proportional–integral-like fuzzy knowledge-based controller (FKBC) optimised by the proposed scheme can further optimise AFR control performance while maximising conversion efficiency of the three-way catalyst to eliminate the exhaust emissions in real time. Different from the conventional experience-based membership function (MF) design method for an FKBC, the proposed MFO scheme uses CA approach and can visualise the relationship between engine step gain scenarios and designed MF patterns to precisely determine its scalar parameters for AFR regulation of GDI engines. Within this context: (i) specialised MFs for self-adaptive AFR control system of a GDI engine are designed with weight distribution; (ii) based on designed scalar parameters, the CA model with taxonomic dimensions is built for acquiring a customised MF to counter transient scenario changes more effectively; (iii) the engine controller with the proposed scheme is real time validated in a production V6 GDI engine, and its advantage in terms of engine transient control performance is further demonstrated by comparing with a benchmark controller designed based on experience.

Comparative Research Transient Air-Fuel Ratio Control Strategy Based on Fuzzy Control and Neural Network

Due to engine performance, fuel economy and emission performance are closely related with its transient air-fuel ratio, so the research of the engine air-fuel ratio control strategy is particularly important. The control strategies for neural network control, fuzzy control are introduced systemically, which can be well applied to the complicated nonlinear control system. The analysis compares the different control strategies in the role of air-fuel ratio control system, the transient air-fuel ratio control for the future to provide certain reference basis.

Functional testing of measurement-based control systems: An application to automotive

The number of measurement-based embedded systems increases continuously in automotive, avionic, defense, and communication industries. In order to ensure the system’s compliance with requirements, adequate solutions for functional testing are needed. The paper describes an original approach for the functional validation of measurement-based complex control systems. The main focus is on the automatic generation of realistic continuous data sets (test stimuli) within the operational ranges of the measurement system under test, by applying enhanced statistical techniques, which are able to reproduce both timing and data dependencies. A thorough case study using an air fuel ratio control system from the automotive domain is performed to assess the approach. Results indicate that the proposed method is suitable for automated functional testing of embedded control systems within a Software-in-the-Loop test environment.

Design and Simulation of Air-Fuel Ratio Control System for Distributorless CNG Engine

This paper puts forward one kind of air-fuel ratio control method with PI controller. With the help of MATLAB/SIMULINK software, the mathematical model of air-fuel ratio control system for distributorless CNG engine is constructed. The objective is to maintain cylinder-to-cylinder air-fuel ratio at a prescribed set point, determined primarily by the state of the ThreeWay-Catalyst (TWC), so that the pollutants in the exhaust are removed with the highest efficiency. The concurrent control of airfuel under transient conditions could be implemented by Proportional and Integral (PI) controller. The simulation result indicates that the control methods can easily eliminate the air/fuel maldistribution and maintain the air/fuel ratio at the stochiometry within minimum engine events. Keywords— Distributorless CNG Engine, Mathematical Model of Air-fuel control, MATLAB/SIMULINK, PI controller

Development of a New Model Based Air-Fuel Ratio Control System

Development of a New Model Based Air-Fuel Ratio Control System

Two-Step Design Method of Engine Control System Based on Generalized Predictive Control

Conservation of the environment has become critical to the automotive industry. Recently, requirements for on-board diagnostic and engine control systems have been strictly enforced. In the present paper, in order to meet the requirements for a low-emissions vehicle, a novel construction method of the air-fuel ratio (A/F) control system is proposed. The construction method of the system is divided into two steps. The first step is to design the A/F control system for the engine based on an open loop design. The second step is to design the A/F control system for the catalyst system. The design method is based on the generalized predictive control in order to satisfy the robustness to open loop control as well as model uncertainty. The effectiveness of the proposed A/F control system is verified through experiments using full-scale products.

AFR Control System Using TWC Outlet Oxygen Sensor

The utilisation of the oxygen storage capacity of TWC is recently focused on for the improvement of emission purification and the purification of an engine exhaust gas is achieved fairly high level. However, the control system is seemed to be complicated to use such ability. For the simple utilisation of this ability, a new air fuel ratio control system and algorithm was investigated. The fuel injection mass was modulated periodically and the air excess ratio was detected at the TWC outlet by an oxygen sensor. As the output signal of an oxygen sensor was switching type, the signal value was filtered by a moving average method for translation to an analog value and the moving average value was used for the periodic modulation control as the control value. Furthermore, the two feed forward control system were equipped for fast response and stability of the fuel control. This simple control system was operated at transient state in many driving conditions, and compared with other control systems. The proposed control system can cut the emissions of NOx and THC concurrently and the reduced amount were larger than other control system.

Air–fuel ratio control system using pulse width and amplitude modulation at transient state

The conventional air–fuel ratio (AFR) control system for the exhaust gases of an internal combustion engine is equipped with feedback and feedforward control systems in order to maintain the AFR within the range of high conversion efficiency even if the engine is in a transient state or if the engine parameters change. However, it is difficult to maintain the AFR within this window at all operating conditions because of the nonlinear characteristics of an internal combustion engine. Thus, in order to avoid increments in the emission level if the AFR moves outside the window, the algorithm of AFR pulse width and amplitude modulation at transient states was proposed. This algorithm was applied to the conventional AFR control system and investigated experimentally.

5426937 Dual-sensor type air-fuel ratio control system for internal combustion engine and catalytic converter diagnosis apparatus for the same: Ohuchi Hirofumi; Fujimoto Shinya Himeji, Japan Assigned to Mitsubishi Denki Kabushiki Kaisha

Mitsubishi Kasei and Mitsubishi Petrochemical merged to become Mitsubishi Chemical in 1994 making it the largest chemical company in Japan. This allows two original companies’ production sites, especially for those are physically built next to each other, to improve themselves by multi-site integration. Mitsubishi Yokkaichi production plant site is one of the typical examples, which consists of three individual plant sites in the old company structure. Each plant site contains a utility plant to generate steam and electricity for chemical production. After the company merge, connecting steam and electricity among plant sites have been carried out for better flexibility, efficiency as well as capability of the utility systems. Besides these, there are still many other improvement alternatives. A site-model, which includes all three utility plants and production units, was then developed to explore further opportunities. In this paper, applications at Mitsubishi Yokkaichi production site are presented to illustrate the features of the site-model.

5426935 Air-fuel ratio control system for internal combustion engines: Ogawa Ken; Ehara Yasunori Wako, Japan Assigned to Honda Giken Kogyo Kabushiki Kaisha

5426935 Air-fuel ratio control system for internal combustion engines: Ogawa Ken; Ehara Yasunori Wako, Japan Assigned to Honda Giken Kogyo Kabushiki Kaisha