Spark Ignition Engine Model Research Articles

Heat Transfer Modeling of Hydrogen-Fueled Spark Ignition Engine

Currently, green hydrogen, generated through renewable energy sources, stands out as one of the best substitutes for fossil fuels in mitigating pollutant emissions and consequent global warming. Particularly, the utilization of hydrogen in spark ignition engines has undergone extensive study in recent years. Many aspects have been analyzed: the conversion of gasoline engines to hydrogen operation, the combustion duration, the heat transfer, and, in general, the engine thermal efficiency. Hydrogen combustion is characterized by a smaller quenching distance compared to traditional hydrocarbon fuels such as gasoline or natural gas and this produces a smaller thermal boundary layer and consequently higher heat transfer. This paper presents findings from experimental trials and numerical simulations conducted on a hydrogen-powered CFR (cooperative fuel research) engine, focusing specifically on heat transfer with combustion chamber walls. The engine has also been fueled with methane and isooctane (two reference fuels); both the engine compression ratio and the air/fuel ratio have been changed in a wide range in order to compare the three fuels in terms of heat transfer, combustion duration, and engine thermal efficiency in different operating conditions. A numerical model has been calibrated with experimental data in order to predict the amount of heat transfer under the best thermal efficiency operating conditions. The results show that, when operated with hydrogen, the best engine efficiency is obtained with a compression ratio of 11.9 and an excess air ratio (λ) of 2.

Theoretical Analysis of Performance Characteristics of Non- road Spark Ignition Engines

Non-road spark ignition (SI) engines play a critical role in Nigeria, particularly in agriculture, construction, and small-scale power generation. Despite their extensive use, there is limited research on how Nigeria's unique environmental and operational conditions such as high ambient temperatures, poor fuel quality, and irregular maintenance practices affect the performance of these engines. This study presents a theoretical analysis of the performance characteristics of non-road SI engines under Nigerian conditions, focusing on fuel efficiency, power output, thermal efficiency, and emissions. The effect of engine speed, engine load and equivalence ratio on the performance characteristics of non-road spark ignition engines were studied in this research. Three operating parameters (engine load, engine speed, and equivalence ratio) and eight engine performance parameters which are Brake Specific Fuel Consumption (BSFC), Brake Power (BP), Thermal Efficiency (TE), Brake Mean Effective Pressure, Exhaust Gas Temperature (EGT), carbon monoxide emission, hydrocarbon emission, and nitrogen oxide were considered in this work. Theoretical analysis was performed using a two-zone SI engine model, the resulting equations were solved with the aid of a computer program developed by the authors and implemented in MATLAB software. The effect of the operating parameters on the performance parameters was simulated using the computer code developed which was implemented in MATLAB. The results show that the engine speed of 3000 rpm gave the optimum values of 250 g/kWh, 33 kW, 1070 kPa, 28% and 720 oC for BSFC, BP, BMEP, TE, and EGT respectively. Also, all performance parameters increased with an increase in engine load. The equivalence ratio of 0.9 gave the optimum values for all the parameters considered in this work. It can be concluded that for optimum performance of non-road SI engines, it should be operated at equivalence ratio of 0.9, engine speed of 3000 rpm and low engine loads.

Artificial Neural Network-Based Modeling of Performance Spark Ignition Engine Fuelled with Bioethanol and Gasoline

Machine learning technology can distinguish the relationship between engine characteristics and performances. Therefore, the goal of the present work is to predict the performance parameters of a single-cylinder 4-stroke gasoline engine at different ignition timings using a blended mixture of gasoline and bioethanol by an artificial neural network (ANN). Experimental data for training and testing in the proposed ANN was obtained at a dynamic speed and full load condition. An ANN model was developed based on standard Back-Propagation algorithm for the spark ignition engine. Multi-layer perception network (MLP) was used for non-linear mapping between the input and output parameters. An optimizer in the family of quasi-Newton methods (lbfgs) and the rectified linear unit function were used to assess the percentage error between the desired and the predicted values. The network input parameters are engine speed, fuel, and ignition timing. Furthermore, torque, power, specific fuel consumption (SFC), thermal efficiency (ηth), and energy consumption (EC) are taken as output parameters. The results show that ANN is the proper method for predicting SIE performance because it has accurate prediction results that are very similar to experimental results. Moreover, from the observation results, the ANN model can predict the engine performance quite well with correlation coefficient (R)=0.962139 and MSE=0.003967 for data testing.

Influence of Hydrogen Enrichment Strategy on Performance Characteristics, Combustion and Emissions of a Rotary Engine for Unmanned Aerial Vehicles (UAVs)

In recent years, there has been great interest in Wankel-type rotary engines, which are one of the most suitable power sources for unmanned aerial vehicle (UAV) applications due to their high power-to-size and power-to-weight ratios. The purpose of the present study was to investigate the potential of a hydrogen enrichment strategy for the improvement of the performance and reduction of the emissions of Wankel engines. The main motivation behind this study was to make Wankel engines, which are already very advantageous for UAV applications, even more advantageous by applying the hydrogen enrichment technique. In this study, hydrogen addition was implemented in a spark-ignition rotary engine model operating at a constant engine speed of 6000 rpm. The mass fraction of hydrogen in the intake gradually increased from 0% to 10%. Simulation results revealed that addition of hydrogen to the fuel accelerated the flame propagation and increased the burning speed of the fuel, the combustion temperature and the peak pressure in the working chamber. These phenomena had a very positive effect on the performance and emissions of the Wankel engine. The indicated mean effective pressure (IMEP) increased by 8.18% and 9.68% and the indicated torque increased by 6.15% and 7.99% for the 5% and 10% hydrogen mass fraction cases, respectively, compared to those obtained with neat gasoline. In contrast, CO emissions were reduced by 33.35% and 46.21% and soot emissions by 11.92% and 20.06% for 5% and 10% hydrogen additions, respectively. NOx emissions increased with the application of the hydrogen enrichment strategy for the Wankel engine.

Altitude Performance and Fuel Consumption Modelling of Aircraft Piston Engine Rotax 912 S/ULS

Rotax 912 spark-ignition (SI) naturally aspirated aircraft piston engine is one of the most popular prime movers for the ultra-light weight aircrafts used for short and moderate range flights. SI engines operate at stoichiometric combustion and at high altitude conditions atmospheric pressure is lower than sea level reducing mass of air intake to the engine. At these conditions engine power degrades significantly from sea level, affecting flight parameters such as range and endurance. In order to optimize these parameters, engine power modelling is of vital importance. Within the scope of this study, a thermodynamic SI engine model with performance parameters (break torque and power) and fuel consumption estimation developed in MATLAB/Simulink software. Model tuning is realised using data extracted from Rotax engine operating manual at sea level and high altitude conditions. Model inputs are set as altitude, throttle lever and engine speed. Pressure drop at the intake port is modelled as a function of mass air flow using engine operating manual pressure data at various engine speed points. Mass air flow is determined via employing a volumetric efficiency map based on intake port pressure and engine speed inputs, calibrated using engine operating manual fuel data considering stoichiometric combustion. Compression and expansion strokes area modelled as isentropic events and combustion is modelled as constant volume heat input at top dead centre (TDC). However a combustion efficiency map based on engine speed and fuel flow is employed for the heat input in order to tune the work output of the engine and heat loss to the coolant and exhaust. Pumping loss is calculated based on friction mean effective pressure data. Introduced approach provides high accuracy performance and fuel consumption modelling based on engine operating manual data and can be used for flight parameters optimization studies.

Integrated methodology for state and parameter estimation of spark-ignition engines

To develop an effective control and monitoring scheme for automotive engines, a precise knowledge of the parameters and unmeasurable states of the nonlinear model capturing the overall dynamics of engines is of utmost importance. For a new vehicle out of the assembly line, the nonlinear model has constant parameters. However, in the long run, due to regular wear-and-tear, and for other unpredictable disturbances, they may change. The main challenges are how to obtain the information of parameters and states under the influence of process noise and measurement noise. To address these challenges, we present a new integrated state and parameter estimation algorithm in this paper for spark ignition (SI) engines based on the constrained unscented Kalman filter and the improved recursive least square technique. The system under consideration is a highly nonlinear mean value SI engine model consisting of the throttle, intake manifold, engine speed dynamics, and fuel system. The performance of the proposed algorithm in terms of root-mean-square-error and robustness with regards to initial conditions and random noises is analysed through exhaustive simulation scenarios considering constant, and time-varying parameters. In addition, the performance of other state-of-the-art estimation algorithms is also compared with that of the developed integrated algorithm.

Knock detection in a quasi-dimensional SI combustion simulation using ignition delay and knock combustion modeling

In spark ignition (SI) engines, knock suppression is essential to improve fuel economy. Integrating new technologies into already complex downsized turbocharged engines increases the number of design and control variables substantially and requires extensive engine testing. Utilizing simulation-based study in an engine development process is crucial to reduce expensive and time-consuming engine tests. A quasi-dimensional (quasi-D) two-zone SI engine model is typically used in SI engine simulations. However, the usefulness of quasi-D-based simulation tools is often limited by the predictive capability of knock models. In this study, a novel knock model intended to be implemented in quasi-D SI engine simulation was developed. The model comprises a two-stage ignition delay model, a knock combustion model, and a knock index model. The knock model simulates the heat release spike during a knock combustion, which can be observed from the apparent heat release rate generated with the low-pass filtered cylinder pressure data. The model was calibrated and validated against engine experimental data. Its capability of knock detection and knock-limited spark timing estimation was demonstrated under various conditions of octane numbers, air–fuel equivalence ratios, and coolant temperatures with toluene primary reference fuel (TRPF). The knock model was also able to capture different knock characteristics between TPRF and primary reference fuel (PRF) in modern downsized turbocharged SI engines. The proposed methodology represents a useful tool to be employed during the development phase of an engine to reduce the experimental efforts while improving the engine performance at knock borderline.

A Novel State and Parameter Estimation Algorithm for Spark Ignition Engine

The engine control and estimation problem is an important area of research in the automotive industry. Researchers have been working to make the vehicles more efficient and economically friendly while producing lesser pollutants. To reduce emissions, the air-fuel ratio must be controlled to a specific value. The requirement of air-fuel ratio improvement has increased the need for the investigation of engine dynamical models and their parameter estimation. Some of the main parameters affecting the air-fuel ratio are the throttle discharge coefficient, thermal efficiency and volumetric efficiency. The precise values of these parameters are essential for accurate control of the air-fuel ratio of the engine. Under steady state, these parameters are constant but in the long run due to wear and tear of the engine and various uncertainties, their value may change. The main challenges are how to obtain the information of parameters and that of the states under the influence of process noise, measurement noise and parameter uncertainty, which are essential elements to develop an effective control strategy. In this work, the problem of physical parameter estimation of the nonlinear system comprising a throttle, intake manifold, engine speed dynamics and fuel system altogether with unknown states have been considered. A novel method with a unique combination of Unscented Kalman Filter and Recursive Least Squares with forgetting factor for estimation of parameters and states of spark ignition engines has been developed. Simulation results are provided for state and parameter estimation for spark ignition engine model.

State and Parameter Estimation for Spark Ignition Engine

In order to monitor the health of an internal combustion engine, there is a need to check the engine parameters from time to time. These parameters are further used in control and calibration. In this work, mean value engine dynamics of spark ignition model are taken and parameter estimation is done using Recursive Least Squares with forgetting factor. To get the information of unknown states, Unscented Kalman Filter is used for state estimation. Nonlinearity of the system is transferred by distributions. The parameters are estimated as time varying signals without having to define their dynamic behavior or as a function of other variables. This work explores a new combination of Unscented Kalman Filter and Recursive Least Squares with forgetting factor to estimate the physics based model parameters of spark ignition engine. This methodology outperforms many other methodologies by the fact that it does not require huge training data, parameter equations and restores the system nonlinearity. Simulation results are provided for Spark Ignition engine model with constant and time varying parameters. Comparison with Unscented Kalman Filter for the joint engine state and parameter estimation is done.

Modeling pre-spark heat release and low temperature chemistry of iso-octane in a boosted spark-ignition engine

Recent trends among automotive manufacturers towards downsized, boosted engines make it imperative to understand specific fuel chemistry interactions encountered in this new operating regime. At these elevated pressure conditions a phenomenon called pre-spark heat release has recently been discovered, and is characterized by kinetically controlled heat release before spark, with resultant changes in end-gas thermodynamic state and composition. These reactions typically occur in the end-gas during normal operation, but are obscured by the deflagration heat release and therefore cannot be easily studied. A 2-zone spark-ignition engine model was utilized to determine whether chemical kinetic mechanisms are able to predict this phenomenon, and whether they accurately capture end-gas thermodynamic history. Experimental engine data at a range of boosted operating conditions demonstrating pre-spark heat release were compared with simulations using mechanisms representing the latest developments in gasoline kinetic modeling. The results demonstrated significant discrepancies between mechanisms, and between experimental and simulated results in terms of low-temperature heat release magnitude, end-gas thermodynamic state, and autoignition propensity. The results highlight shortcomings in low-temperature reaction pathways, and indicate the necessity of simultaneously matching first-stage ignition delay and heat release magnitude, in addition to second-stage ignition delay, in order to accurately predict end-gas thermodynamics and autoignition.

ROBUST FUZZY CONTROL DESIGN USING GENETIC ALGORITHM OPTIMIZATION APPROACH: CASE STUDY OF SPARK IGNITION ENGINE TORQUE CONTROL

In the case of widely-uncertain non-linear system control design, it was very difficult to design a single controller to overcome control design specifications in all of its dynamical characteristics uncertainties. To resolve these problems, a new design method of robust fuzzy control proposed. The solution offered was by creating multiple soft-switching with Takagi-Sugeno fuzzy model for optimal solution control at all operating points that generate uncertainties. Optimal solution control at each operating point was calculated using genetic algorithm. A case study of engine torque control of spark ignition engine model was used to prove this new method of robust fuzzy control design. From the simulation results, it can be concluded that the controller operates very well for a wide uncertainty.

ADRC‐based transient air/fuel ratio control with time‐varying transport delay consideration for gasoline engines

This paper presents a fuel injection controller based on the modified active disturbance rejection control (ADRC) algorithm to maintain the air/fuel ratio (AFR) at the stoichiometric value in the presence of a transport time delay. The factors affecting the dynamics of the AFR include the variations of the intake manifold pressure, engine speed, and load torque, as well as uncertain parameters existing in the fuel film evaporation and the oxygen sensor aging, which are viewed as the 'total disturbance' to the AFR system and estimated by the extended state observer (ESO). Thus, based on the Lyapunov–Krasovskii functional stability theory, the ADRC fuel injection controller is designed with the gain matrices of the controller and observer and solved by employing linear matrix inequalities. Considering the time‐varying transport delay, a time delay block is added to the ESO. By synchronizing the input signals of the ESO, the performance in terms of the timely compensation for the disturbance is improved. The effectiveness of the proposed control strategy is validated through simulation of a V6 spark ignition engine model developed by the Society of Instrument and Control Engineers (SICE) Research Committee on Advanced Powertrain Control Theory. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Performance evaluation of gasoline alternatives using a thermodynamic spark-ignition engine model

In light of climate change and the fact that surface transportation heavily relies on internal combustion engines, many different alternatives to gasoline have been proposed.

Understanding the effect of external-EGR on anti-knock characteristics of various ethanol reference fuel with RON 100 by using rapid compression machine

In this study, the effect of external-exhaust-gas-recirculation (EGR) on anti-knock characteristics of ethanol reference fuels (ERFs) with research octane number (RON) 100 was analyzed by measuring the ignition delay of the simulated end gas from a representative spark ignition (SI) engine operation, i.e. ASTM RON test condition. An in-house SI engine model was used to derive temperature and pressure profiles of the end gas with and without external-EGR for various ERFs, and then the ignition delay was measured by using a rapid compression machine along the derived temperature-pressure paths. The effect of external-EGR on the ignition delay of the simulated end gas was divided into two effects affecting the auto-ignition behavior: composition effect and temperature effect, then each effect was evaluated separately. As a result, the composition effect by adding external-EGR was maximized when the fuel is ERF10. With a regression analysis, it was found that there is the correlation between the amount of composition effect and the amount of pre-heat release in the end gas during a flame propagation; therefore, it is understood that ERF10 shows the most sensitive composition effect due to its pre-heat release characteristic. On the other hand, ERF with higher ethanol content was more sensitive to temperature effect by external-EGR on the ignition delay. It is found out that the amount of temperature effect depends mainly on latent heat of fuel; therefore, high latent heat of ethanol in ERF leads to its being influenced more by temperature effect. Consequently, ERF10 has the highest external-EGR sensitivity in anti-knock behavior at RON test condition, and it is further discussed that the optimum ERF for external-EGR strategy could vary from ERF0 to ERF10 according to different engine operating conditions.

Availability analysis of using iso-octane/n-butanol blends in spark-ignition engines

The current work presents a detailed energy and exergy analysis of an iso-octane/n-butanol blend-fueled spark-ignition (SI) engine to investigate exergy loss mechanisms and understand how the exergy destruction changes with different iso-octane/n-butanol blend fuels. Energy and exergy analysis was applied to a quasi-dimensional two-zone SI engine model, including Wiebe function to model the actual combustion process based on fuel types and operating conditions. Results were obtained for an SI engine at 3000 rpm by changing spark timing, volume fraction of n-butanol, and load. When sweeping spark timing, it was found that the location of maximum first and second-law efficiency appear at around −31 °CA ATDC for iso-octane, BU10, BU20 and BU30, and approximately −28 °CA ATDC for n-butanol. Increasing butanol fraction in the blends increases the percentage of total irreversibility in total availability at either MBT or constant spark timing, while has slight influence on availability transferred by heat transfer. At the MBT spark timing and WOT condition, the first-law efficiency increases slightly with increase of n-butanol, while the second-law efficiency for blended fuel decreases slightly. However, with decreasing engine load, the percentages of total irreversibility and availability transferred by heat transfer increase, the first and second-law efficiencies both decrease.

Quasi-dimensional modeling of a fast-burn combustion dual-plug spark-ignition engine with complex combustion chamber geometries

This study builds on a previous parametric investigation using a thermodynamic-based quasi-dimensional (QD) cycle simulation of a spark-ignition (SI) engine with dual-spark plugs. The previous work examined the effects of plug-number and location on some performance parameters considering an engine with a simple cylindrical disc-shaped combustion chamber. In order to provide QD thermodynamic models applicable to complex combustion chamber geometries, a novel approach is considered here: flame-maps, which utilizes a computer aided design (CAD) software (SolidWorks). Flame maps are produced by the CAD software, which comprise all the possible flame radiuses with an increment of one-mm between them, according to the spark plug positions, spark timing, and piston position near the top dead center. The data are tabulated and stored as matrices. Then, these tabulated data are adapted to the previously reported cycle simulation. After testing for simple disc-shaped chamber geometries, the simulation is applied to a real production automobile (Honda-Fit) engine to perform the parametric study.

Acausal powertrain modelling with cycle-by-cycle spark ignition engine model

Due to more stringent emission limits and demand to improve fuel consumption, automotive researchers have been trying to develop detailed physics-based powertrain models for fuel consumption and emission control purposes. This paper presents an acausal powertrain model including vehicle longitudinal dynamics. The developed cycle-by-cycle spark ignition (SI) engine model is connected to a physics-based dynamic torque converter model, and the torque converter is connected to the rest of the powertrain (gear box, differential, tyres and chassis model) through acausal mechanical port connections. The SI engine speed and load are variable during the many-cycle powertrain simulation. The cycle-by-cycle four-stroke engine is based on a two-zone combustion modelling approach which assumes the engine speed is kept constant during a cycle. The SI engine and dynamic torque converter models are cross-validated with the GT-Power software and experimental data. The developed powertrain model in MapleSim is a suitable plant model that can be used for control applications due to the fast simulation time (faster than real time).

Math-based spark ignition engine modelling including emission prediction for control applications

A complete spark ignition (SI) engine model is a multi-domain model including fluid dynamics, thermodynamics, combustion, electrical, and mechanical sub-models. The complexity of these models depends on the type of analysis used for model development, which may vary from highly detailed computational fluid dynamics (CFD) analysis (multi-dimensional model) to simpler data-based analysis in which the data is obtained from experiments (zero-dimensional model). The main objective of our research is to develop a math-based SI engine model for control application and real time simulation. The model must be accurate enough to capture the combustion characteristics (e.g., combustion temperature) and predict emission gases, while being fast enough for real time simulation purposes. In this paper, a physics-based model of an SI engine is presented which consists of different sub-models including: throttle body and manifold model, four-stroke quasi-dimensional thermodynamic model of gas exchange and power cycles, two-zone combustion and flame propagation model, emission gases model based on the chemical kinetics equations, and mechanical torque model. Moreover, part of the simulation results is validated against the GT-Power simulation results. The math-based model is created in the MapleSim environment. The symbolic nature of MapleSim significantly shortens the simulation time and also enables parametric sensitivity analysis.

An objective analysis of drivability for two wheeler powertrain with control oriented dynamic model

The objective of this work is to estimate drivability characteristics parameters of two wheeler powertrain with control oriented powertrain model. The evaluation is essential for defining drivability characteristics for a future electric variable transmission (EVT) powertrain. The mathematical model for the complete powertrain is developed using suitable modeling approaches for the different sub-modules of the complete system. The Spark Ignition (SI) engine model used for this work is developed from mean value model approach and experimentally validated with test data from TVS Motor Company, India. The model is integrated with two types of transmission models, Continuous Variable Transmission (CVT) and Manual Transmission (MT). It simulates dynamic power-flow from the engine to wheel for analyzing longitudinal drivability of the vehicle for both powertrain configurations. It is proposed that the drivability can be measured with certain parameters which show good correlation with subjective assessments for vehicle launch as well as tip in condition. The objective assessment of both types of powertrains is performed using the above mentioned powertrain models. The results of the simulation for drivability tests are discussed in this paper.

High-precision, real-world modeling of a semi-automatic powertrain

In a mechatronical approach, the design of a highly detailed, physically based model of a semi-automatic powertrain suitable for supervision has been explicated. In each part of the powertrain system, ultimately developed dynamical models have been exploited to make sure the whole model is up-to-date and is close to a real system. Advanced dynamical equations of an engine, a clutch, a gearbox and a driveline as well as a tire and a vehicle dynamic model for analyzing longitudinal performance have been considered. A well-suited automated manual transmission (AMT) along with a mean value transient spark-ignition (SI) engine model has been inserted to complete the solution. In order to simulate a real vehicle, the nonlinearities of the powertrain system mainly generated in the engine and clutch have drawn attention. Transient behavior of the system is a key parameter for design; hence, both steady-state and transient modeling such as of the gear shift procedure were considered. All parts of the model have been verified against experimental data. Finally, an overall simulation of the powertrain and vehicle in an in-city Economic Commission for Europe (ECE) cycle and a complete involved simulation of a gear shift process using Simulink have been performed to examine the level of the modeled dynamics. Lastly, it will be clear that use of nonlinear and real-world models can enhance the modeling and make it comparable to a real system.