Gasoline Engine Model Research Articles

Engine Calibration With Surrogate-Assisted Bilevel Evolutionary Algorithm.

Engine calibration problems are black-box optimization problems which are evaluation costly and most of them are constrained in the objective space. In these problems, decision variables may have different impacts on objectives and constraints, which could be detected by sensitivity analysis. Most existing surrogate-assisted evolutionary algorithms do not analyze variable sensitivity, thus, useless effort may be made on some less sensitive variables. This article proposes a surrogate-assisted bilevel evolutionary algorithm to solve a real-world engine calibration problem. Principal component analysis is performed to investigate the impact of variables on constraints and to divide decision variables into lower-level and upper-level variables. The lower-level aims at optimizing lower-level variables to make candidate solutions feasible, and the upper-level focuses on adjusting upper-level variables to optimize the objective. In addition, an ordinal-regression-based surrogate is adapted to estimate the ordinal landscape of solution feasibility. Computational studies on a gasoline engine model demonstrate that our algorithm is efficient in constraint handling and also achieves a smaller fuel consumption value than other state-of-the-art calibration methods.

Exhaust Gas Temperature Pulsations of a Gasoline Engine and Its Stabilization Using Thermal Energy Storage System to Reduce Emissions

Modern automotive gasoline engines have highly efficient after-treatment systems that reduce exhaust gas emissions. However, this efficiency greatly depends on the conditions of the exhaust gas, mainly the temperature and air–fuel ratio. The temperature instability during transient conditions may cause a reduction in the efficiency of the three-way catalyst (TWC). By using a thermal energy storage system before TWC, this negative effect can be suppressed. In this paper, the effects of the temperature stabilization on the efficiency of the three-way catalyst were investigated on a 1-D turbocharged gasoline engine model, with a focus on fuel consumption and emissions. The thermal energy storage system (TESS) was based on PCM materials and was built in the exhaust between the turbine and TWC to use the energy of the exhaust gas. Three different materials were picked up as possible mediums in the storage system. Based on the results, the usage of a TESS in a gasoline after-treatment system has shown great potential in improving TWC efficiency. This approach can assist the catalyst to operate under optimal conditions during the drive. In this study, it was found that facilitating the heat transfer between the PCM and the catalyst can significantly improve the emissions’ reduction performance by avoiding the catalyst to light out after the cold start. The TESS with PCM H430 proved to reduce the cumulative CO and HC emissions by 8.2% and 10.6%, respectively, during the drive. Although a TES system increases the after-treatment cost, it can result in emission reductions and fuel consumption over the vehicle’s operating life.

A Comparison of Ethanol, Methanol, and Butanol Blending with Gasoline and Its Effect on Engine Performance and Emissions Using Engine Simulation

Air pollution, especially in large cities around the world, is associated with serious problems both with people’s health and the environment. Over the past few years, there has been a particularly intensive demand for alternatives to fossil fuels, because when they are burned, substances that pollute the environment are released. In addition to the smoke from fuels burned for heating and harmful emissions that industrial installations release, the exhaust emissions of vehicles create a large share of the fossil fuel pollution. Alternative fuels, known as non-conventional and advanced fuels, are derived from resources other than fossil fuels. Because alcoholic fuels have several physical and propellant properties similar to those of gasoline, they can be considered as one of the alternative fuels. Alcoholic fuels or alcohol-blended fuels may be used in gasoline engines to reduce exhaust emissions. This study aimed to develop a gasoline engine model to predict the influence of different types of alcohol-blended fuels on performance and emissions. For the purpose of this study, the AVL Boost software was used to analyse characteristics of the gasoline engine when operating with different mixtures of ethanol, methanol, butanol, and gasoline (by volume). Results obtained from different fuel blends showed that when alcohol blends were used, brake power decreased and the brake specific fuel consumption increased compared to when using gasoline, and CO and HC concentrations decreased as the fuel blends percentage increased.

Design and calibration of intake model for electric supercharged gasoline engine

The electric supercharger can significantly increase the transient intake air charge of the engine, thus increasing the power output of the engine under heavy load conditions. However, the traditional in-cylinder intake air charge calculation model has heavy calibration workload and low portability, and is not suitable for the intake air charge calculation of the electric supercharged gasoline engine. In order to reduce the difficulty of in-cylinder intake air calibration and improve the accuracy of intake air estimation, based on an electric supercharged gasoline engine, this paper simplifies the actual intake process into valve overlap period and free intake period, and proposes an in-cylinder intake air charge estimation model with intake pressure sensor as the main load sensor based on the mean value engine model. Three unknown coefficients, i.e., residual exhaust gas correction coefficient ɑ1, heat transfer coefficient ɑ2 between manifold and fresh gas, and effective flow area ɑ3 in valve overlap period, are calibrated by using the simulation data of the numerical model of electric supercharged gasoline engine. Compared with the numerical simulation results, the air intake model established in this paper can accurately estimate the actual in-cylinder air intake of electric supercharged gasoline engine under the external characteristic condition, and the calculation error is within 5%, which can provide theoretical reference for the in-cylinder air intake estimation of electric supercharged gasoline engine

A PI(4,5)P2-derived “gasoline engine model” for the sustained B cell receptor activation

Abstract To efficiently initiate activation responses against rare ligands in the microenvironment, lymphocytes employ sophisticated mechanisms involving signaling amplification. Recently, a signaling amplification mechanism initiated from phosphatidylinositol (PI) 4, 5-biphosphate [PI(4,5)P2] hydrolysis and synthesis for sustained B cell activation has been reported. Antigen and B cell receptor (BCR) recognition triggered the prompt reduction of PI(4,5)P2 density within the BCR microclusters, which led to the positive feedback for the synthesis of PI(4,5)P2 outside of the BCR microclusters. At single molecule level, the diffusion of PI(4,5)P2 was slow, allowing for the maintenance of a PI(4,5)P2 density gradient between the inside and outside of the BCR microclusters and the persistent supply of PI(4,5)P2 from outside to inside of the BCR microclusters. Here, we review studies that have contributed to uncovering the molecular mechanisms of PI(4,5)P2-derived signaling amplification model. Based on these studies, our recent work supported a “gasoline engine model” in which the activation of B cell signaling inside the microclusters is similar to the working principle of burning gasoline within the engine chamber of a gasoline engine.

Comparison of metallic (FeCrAl) and Ceramic Catalytic Converter (CATCO) in reducing exhaust gas emission of gasoline engine fuelled by RON 95 to develop health environment

Environmental and human health problemscaused by high air pollutant which contributed by transportation sector become main issue in the world. There are someair pollutants from gasoline engine such as Carbon Monoxide (CO), Nitrogen Oxide (NOx) and Hydro-Carbon (HC). Therefore, the objective is to investigate the effectiveness of catalytic converter (CATCO) as pollutant converter in reducing harmful exhaust gas and improving the conversion efficiency. The exhaust emission analysis is conducted by gasoline engine model Mitsubishi4G93 in various engine load of 10%, 20% and 30% and various speed of 1000, 2000 and 3000 rpm fuelled by RON 95. The result shows that the ceramic material more effective to reduce the CO and HC as compared to metallic material with maximum conversion is 99.02% at speed of 1000 rpm in engine load of 20% and 97.66% at speed of 1000 rpm and 10%engine load. Meanwhile, Metallic CATCO shows the lower NOx emission as compared to ceramic with the lowest NOx is 128.27 ppm which shown by speed of 1000 rpm and 10%engine load. The lowest emission mostly at speed of 1000 rpm and at lower engine load. It caused by engine load and speed increased as CO, NOx and HC increased as well.

Development and application of empirical models to optimize the control of an internal combustion engine

Introduction. The quality of the engine control units software (SW) significantly determines the output performance of the internal combustion engine (ICE). An important component of the software development process is its adaptation or calibration, which includes a large amount of work to select specific values of control actions to improve the performance of the internal combustion engine operating cycle under toxicity restrictions. The purpose of the work was to reduce time and material costs during the initial calibration work. Methodology and research methods . To achieve the goal the application of the calibration technique to the gasoline engine control system was proposed which was to be carried out by using empirical (obtained experimentally) ICE models. The main tool used in the work was the ASCMO software, which was used with ETAS technical support. The calibration process presented in the article was divided into stages: development of an experiment plan, testing (carried out on a gasoline engine model), analysis and processing of the results with the construction of an empirical ICE model, optimization of controlled influences and preparation of calibration maps taking into account the restrictions of harmful emissions during car cycle testing. Scientific novelty and results . The technique of initial ICE calibration based on the use of an empirical engine model has been formulated. The presented results were obtained without taking into account the statutory norms and rules, the imposed restrictions were formed in an arbitrary way. Practical significance . The presented method is of practical importance, since it allows to optimize labor costs for carrying out calibration work. A brief assessment of the effectiveness and applications of the technique is provided in the publication.

A PI(4,5)P2-derived "gasoline engine model" for the sustained B cell receptor activation.

To efficiently initiate activation responses against rare ligands in the microenvironment, lymphocytes employ sophisticated mechanisms involving signaling amplification. Recently, a signaling amplification mechanism initiated from phosphatidylinositol (PI) 4, 5-biphosphate [PI(4,5)P2] hydrolysis and synthesis for sustained B cell activation has been reported. Antigen and B cell receptor (BCR) recognition triggered the prompt reduction of PI(4,5)P2 density within the BCR microclusters, which led to the positive feedback for the synthesis of PI(4,5)P2 outside of the BCR microclusters. At single molecule level, the diffusion of PI(4,5)P2 was slow, allowing for the maintenance of a PI(4,5)P2 density gradient between the inside and outside of the BCR microclusters and the persistent supply of PI(4,5)P2 from outside to inside of the BCR microclusters. Here, we review studies that have contributed to uncovering the molecular mechanisms of PI(4,5)P2-derived signaling amplification model. Based on these studies, we proposed a "gasoline engine model" in which the activation of B cell signaling inside the microclusters is similar to the working principle of burning gasoline within the engine chamber of a gasoline engine. We also discuss the evidences showing the potential universality of this model and future prospects.

First Principle Based Control Oriented Gasoline Engine Model Including Lumped Cylinder Dynamics

A novel first principle based control oriented model of a gasoline engine is proposed which also carries diagnostic capabilities. Unlike existing control oriented models, the formulated model reflects dynamics of the faultless as well as faulty engine with high fidelity. In the proposed model, the torque production subsystem is obtained by integration of further two subsystems that is model of a single cylinder torque producing mechanism and an analytical gasoline engine cylinder pressure model. Model of a single cylinder torque producing mechanism is derived using constrained equation of motion (EOM) in Lagrangian mechanics. While cylinder pressure is evaluated using a closed form parametric analytical gasoline engine cylinder pressure model. Novel attributes of the proposed model include minimal usage of empirical relations and relatively wider region of model validity. Additionally, the model provides model based description of crankshaft angular speed fluctuations and tension in the rigid bodies. Capacity of the model to describe the system dynamics under fault conditions is elaborated with case study of an intermittent misfire condition. Model attains new capabilities based on the said novel attributes. The model is successfully validated against experimental data.

First principle based control oriented model of a gasoline engine including multi-cylinder dynamics

The growing complexity of vehicle powertrain systems and stringent emissions requirements placed on these systems has necessitated the introduction of accurate and generalizable engine models that will be suitable for control and diagnostics. A first principle based control oriented model of a multi-cylinder gasoline engine is developed and shown to be also suitable for fault diagnosis. This model takes into cylinder-to-cylinder behavior and spatial orientation while maintaining a simple structure suitable for real time control. A model of the torque production mechanism is coupled with an analytical cylinder pressure model to capture the engine torque. The model of the torque production mechanism is derived using the Constrained Lagrangian Equation of Motion and simplified to a form suitable for integration in an overall engine model. The analytical cylinder pressure model is taken from literature and extended to a four cylinder engine. While it is common to model torque production subsystem as a continuously operating volumetric pump, the methods used in this work allow details including angular speed fluctuations of the crankshaft to be captured. In addition, the engine model is able to describe the dynamics of the system under faultless as well as faulty conditions, which is demonstrated for misfire. The proposed model is also leveraged for a novel fault tolerant control framework and is tuned and successfully validated for a 1.3L four cylinder gasoline engine.

First Principle-Based Control Oriented Model of a Gasoline Engine

A first principle based-control oriented gasoline engine model is proposed that is based on the mathematical model of the actual piston and crankshaft mechanism. Unlike conventional mean value engine models (MVEMs), which involve approximating the torque production mechanism with a volumetric pump, the proposed model obviates this rather over-simplistic assumption. The alleviation of this assumption leads to the additional features in the model such as crankshaft speed fluctuations and tension in bodies forming the mechanism. The torque production dynamics are derived through Lagrangian mechanics. The derived equations are reduced to a suitable form that can be easily used in the control-oriented model. As a result, the abstraction level is greatly reduced between the engine system and the mathematical model. The proposed model is validated successfully against a commercially available 1.3 L gasoline engine. Being a transparent and more capable model, the proposed model can offer better insight into the engine dynamics, improved control design and diagnosis solutions, and that too, in a unified framework.

Finite Element Analysis of EA 113 Gasoline Engine Connecting Rod

For the Santana EA 113 gasoline engine connecting rod, the motion law of connecting rod and stresses in movement were analyzed using the theory knowledge of kinematics and dynamics. Based on the finite element method, the three-dimensional model of four-cylinder four-stroke gasoline engine connecting rod was established and then the stiffness and stress distribution and strain condition of connecting rod under different working conditions were analyzed. In modal analysis and transient dynamic analysis, the frequencies of rod in resonance and the stress, displacement and velocity of connecting rod at each moment were obtained, which provide the basis for the optimal design of connecting rod.

Composite Adaptive Internal Model Control and Its Application to Boost Pressure Control of a Turbocharged Gasoline Engine

Internal model control (IMC) explicitly incorporates the plant model and its approximate inverse and offers an intuitive controller structure and calibration procedure. In the presence of plant-model uncertainty, combining the IMC structure with parameter estimation through the certainty equivalence principle leads to adaptive IMC (AIMC), where either the plant model or its inverse is identified. This paper proposes a composite AIMC (CAIMC) that explores the IMC structure and simultaneous plant dynamics and inverse dynamics identification to achieve improved performance of AIMC. A toy plant is used to illustrate the feasibility and potential of CAIMC. The advantages of CAIMC are later demonstrated on the boost-pressure control problem of a turbocharged gasoline engine. The design of the CAIMC assumes that the plant model and its inverse are represented by the first-order linear dynamics. The unmodeled dynamics and uncertainties due to linearization and variations in operating conditions are compensated through adaptation. The resulting CAIMC is first applied to a physics-based high-order and nonlinear proprietary turbocharged gasoline engine model, and then validated on a turbocharged 2-L four-cylinder gasoline engine on a vehicle with vacuum-actuated wastegate. Both the simulation and experimental results show that the CAIMC cannot only effectively compensate for uncertainties but also auto-tune the IMC controller for the best performance.

Estimation of Within Cycle Dynamics of an SI Gasoline Engine Using Equivalent Cycle Reconstruction

In this paper, a novel method is presented for estimating the repetitive high frequency within cycle dynamics of spark ignition (SI) gasoline engines using equivalent cycles of data reconstructed from low rate uniformly time-sampled measurements. The process of equivalent cycle reconstruction using phase information of samples obviates the need for extra sampling hardware, usually associated with equivalent time sampling in digital oscilloscope applications. The reconstructed equivalent cycle measurements, obtained from low rate sampled data can be used in a state estimator, which uses high frequency within cycle SI gasoline engine model. Results of estimation based on engine data using an industry standard simulator confirm that it is possible to faithfully track states evolving under the within cycle dynamics, which are repetitive using data initially acquired at sampling rate well below Nyquist rates. To the best of the authors' knowledge, this is the first report in the literature on estimation of the within cycle dynamics of automobile engines using engine measurements, acquired at a low frequency well below the Nyquist rates.

Harmonic analysis and optimization of the intake system of a gasoline engine using GT-power

In order to improve the power and reduce the emission of a naturally aspirated gasoline engine at the same time, the effect of different intake structure parameters on the engine performance is investigated in details based on harmonic analysis and an optimization is carried out. First a full-scale gasoline engine model is set up using GT-power, which is calibrated by comparing the experimental data. Then the harmonic effect of the intake system is studied through spectrum analysis of pressure wave. The effects of different intake parameters on engine performance are investigated. At last the intake pipe is optimized using response surface model. The study shows that harmonic effect has big impact on the gasoline engine. The dynamic performance of the engine can be improved at all speeds by optimization the intake system parameters, and an increase of the maximum torque up to 7% is indicated.

Study on LPG Air Fuel Ratio Based on Improved Subtractive Clustering RBF Neural Networks

The paper refers to the mathematical model of gasoline engine, and builds liquid-jet LPG(Liquefied Petroleum Gas) engine model. Based on the model, when the specific of the parameters distribution of operating engine are known, RBF neural network can estimate center value and the number of hidden layers precisely, and control engine A/F in fine range. But the parameter features of operating engine are unknown in advance. The paper provides a improved subtractive clustering - RBF neural Networks algorithm to control A/F of LPG engine. Simulation shows, improved subtractive clustering can precisely determine the number of neuron of RBF neural network hidden layers under unknown operation parameters, and the precision is higher, and self-study and adaptive adjusting is better than before.

Analysis on Mean Value Model of Gasoline Engine in HEV Applications

A mean value model of the 1.5L gasoline engine was established. It mainly consists of fuel film model, transient fuel film compensation model and dynamic output model. After the validation of steady state, the power and economic performances were analyzed with NEDC drive cycle. Together with engine operating points, special attention was such key parameters as paid to engine speed, engine torque and fuel consumption. The dynamic model is validated. The air-fuel ratio fluctuation was studied to validate the fuel film model.

Online Identification and Stochastic Control for Autonomous Internal Combustion Engines

Advanced internal combustion engine technologies have afforded an increase in the number of controllable variables and the ability to optimize engine operation. Values for these variables are determined during engine calibration by means of a tabular static correlation between the controllable variables and the corresponding steady-state engine operating points to achieve desirable engine performance, for example, in fuel economy, pollutant emissions, and engine acceleration. In engine use, table values are interpolated to match actual operating points. State-of-the-art calibration methods cannot guarantee continuously the optimal engine operation for the entire operating domain, especially in transient cases encountered in the driving styles of different drivers. This article presents brief theory and algorithmic implementation that make the engine an autonomous intelligent system capable of learning the required values of controllable variables in real time while operating a vehicle. The engine controller progressively perceives the driver’s driving style and eventually learns to operate in a manner that optimizes specified performance criteria. A gasoline engine model, which learns to optimize fuel economy with respect to spark ignition timing, demonstrates the approach.

A Neural Network Perspective to Extended Luenberger Observers

In this paper we investigate the use of adaptive extended Luenberger state estimators for general nonlinear and possibly time-varying systems. We identify the connection between the extended Luenberger observer and Grossberg's additive model for dynamic neural networks. The association between dynamic neural networks and the Luenberger observer leads to an obvious modification on the proposed observer scheme that would allow handling state estimation for those systems whose dynamic equations are partially known or not known at all. The performance of the adaptive observer is demonstrated on a number of systems including an LTI system, the Van der Pol oscillator, the Lorenz attractor and a realistic partial gasoline engine model.

Spark ignition engines and pollution emission: New approaches in modelling and control

A new nonlinear discrete model of a spark ignited gasoline engine is designed. With good accuracy in a large field, it predicts the engine dynamical behaviour in terms of intake manifold pressure, fuel–air ratio, torque, speed and pollutants concentrations in the exhaust gas as response of throttle opening, spark advance and injection time strategies. A new approach to study fuel economy and pollutants emission minimization is worked out.