Engine Control Parameters Research Articles

A Rule-Based Energy Management Strategy Based on Dynamic Programming for Hydraulic Hybrid Vehicles

Energy management strategy is very important for hydraulic hybrid vehicles to improve fuel economy. The rule-based energy management strategies are widely used in engineering practice due to their simplicity and practicality. However, their performances differ a lot from different parameters and control actions. A rule-based energy management strategy is designed in this paper to realize real-time control of a novel hydraulic hybrid vehicle, and a control parameter selection method based on dynamic programming is proposed to optimize its performance. Firstly, the simulation model of the hydraulic hybrid vehicle is built and validated by the data tested from prototype experimental platform. Based on the simulation model, the optimization method of dynamic programming is used to find the global optimal solution of the engine control for the UDDS drive cycle. Then, the engine control parameters of the rule-based energy management strategy are selected according to the engine control trajectory of the global optimal solution. The simulation results show that the 100 km fuel consumption of the proposed rule-based energy management strategy is 12.7L, which is very close to the global optimal value of 12.4L and is suboptimal.

Reduction of the experimental effort in engine calibration by using neural networks and 1D engine simulation

In this study, two effective methodologies are proposed to overcome some critical issues concerning the base calibration of engine control parameters. Specifically, Neural Networks and 1D CFD simulation were alternatively adopted to reliably calibrate specific ECU functions starting from a reduced number of experimental data. The calibration performance fall within acceptable limits even when significant cuts are made to the experimental data usually acquired for calibration purposes, demonstrating that the proposed methodologies can be useful to significantly reduce the dynamometer tests and their related times and costs.

Validation of a NOx estimation methodology based on the analysis of in-cylinder pressure trace

Internal combustion engines control systems are evolving rapidly in order to meet the most recent emissions standards: this process requires a deep knowledge of how the combustion process takes place, since heat-release control is crucial to manage the trade-off between engine-out emissions and best suit the tailpipe aftertreatment system operating point.Nitrogen oxides (NOx) have currently become a critical pollutant emission that needs to be limited in compression-ignited engines. Since a selective catalytic reduction (SCR) system is present in several applications, engine-out NOx concentration is a fundamental parameter to be evaluated.This work shows how an estimation of NOx concentration can be deduced from instantaneous in-cylinder pressure measurement and some of the parameters, related to the intake charge, currently available on electronic control units (ECU). A prediction model, based on Zeldovich mechanisms and Arrhenius rate of combustion is proposed, which exploits as main contributions: rate of heat release and adiabatic flame temperature. An experimental campaign (DOE) has been carried out on a diesel engine, varying the main engine control parameters, to tune the model in steady-state operating point. The predictive capability is then evaluated by feeding the model with a validation dataset in both steady state and transient condition. Finally, model response to measure uncertainties is discussed.

Experimental studies on the co-effects of engine operating parameters and fuel functional groups on the performance and emissions of a GDI engine

The distributions of molecular functional groups in gasoline have strong effects on the in-cylinder micro-combustion, macro-heat release and emission generation mechanism. It is quite difficult to study the coupling relationship between fuel functional groups and engine performance with commercial gasoline due to its complex components. In this paper, multi-components gasoline surrogates including toluene reference fuel (TRF), n-heptane/iso-octane/toluene/cyclohexane (CTRF) and n-heptane/iso-octane/toluene/cyclohexane/diisobutylene (CDTRF) were applied to study the effects of fuel functional groups and engine control parameters (spark timing, equivalence ratio) on combustion and emissions of a gasoline direct injection (GDI) engine. Amongst the results, it is worth noting that the surrogates produce 30–40% higher nitrogen oxide (NOx) emissions than gasoline and have obvious advantages in particulate matter (PM) emissions, however, at the cost of high carbon monoxide (CO) and total hydrocarbon (THC) emissions. In addition, there are obvious differences in combustion characteristics and unregulated emissions between the surrogates due to different functional groups.

Optimization of gas turbine engine control using dynamic programming

The aim of engine control optimization is to derive the optimal control law for engine operation managing during the aircraft flight. For numerical modeling a continuous flight process defined by a system of differential equations is replaced by a discrete multi-step process. Values of engine control parameters in particular step uniquely identify a system transitions from one state to another. The algorithm is based on the numerical method of dynamic programming and the Bellman optimality principle. The task is represented as a sequence of nested optimization subtasks, so that control optimization at the first step is external to all others. The optimum control function can be determined using the minimax principle of optimality. Aircraft performance calculation is performed by numerical integration of differential equations of aircraft movement.

Diesel engine performance mapping using a parametrized mixing time model

A numerical platform is presented for diesel engine performance mapping. The platform employs a zero-dimensional stochastic reactor model for the simulation of engine in-cylinder processes. n-Heptane is used as diesel surrogate for the modeling of fuel oxidation and emission formation. The overall simulation process is carried out in an automated manner using a genetic algorithm. The probability density function formulation of the stochastic reactor model enables an insight into the locality of turbulence–chemistry interactions that characterize the combustion process in diesel engines. The interactions are accounted for by the modeling of representative mixing time. The mixing time is parametrized with known engine operating parameters such as load, speed and fuel injection strategy. The detailed chemistry consideration and mixing time parametrization enable the extrapolation of engine performance parameters beyond the operating points used for model training. The results show that the model responds correctly to the changes of engine control parameters such as fuel injection timing and exhaust gas recirculation rate. It is demonstrated that the method developed can be applied to the prediction of engine load–speed maps for exhaust NOx, indicated mean effective pressure and fuel consumption. The maps can be derived from the limited experimental data available for model calibration. Significant speedup of the simulations process can be achieved using tabulated chemistry. Overall, the method presented can be considered as a bridge between the experimental works and the development of mean value engine models for engine control applications.

Experimental investigation on a Common Rail Diesel engine partially fuelled by syngas

The high efficiency, reliability and flexibility of modern passenger car Diesel engines makes these power units quite attractive for steady power plants totally or partially running on fuels derived from biomass, in particular on syngas. The engine cost, which is obviously higher than that of current industrial engines, may not be a big obstacle, provided that the re-engineering work is limited and that performance and efficiency are enhanced. The goal of this work is to explore the potential of a current automotive turbocharged Diesel engine running on both Diesel fuel and syngas, by means of a comprehensive experimental investigation focused on the combustion process. The engine is operated at the most typical speed employed in steady power plants (3000rpm), considering three different loads (50–100–300Nm/16–31–94kW). For each operating condition, the syngas rate is progressively increased until it provides a maximum heating power of 85kW, while contemporarily reducing the amount of injected Diesel oil. Maximum care is applied to guarantee a constant quality of the syngas flow throughout the tests, as well as to maintain the same engine control parameters, in particular the boost pressure.It is found that in-cylinder pressure traces do not change very much, even when drastically reducing the amount of Diesel fuel: this is a very encouraging result, because it demonstrates that there is no need to radically modify the standard stock engine design. Another promising outcome is the slight but consistent enhancement of the engine brake efficiency: the use of syngas not only reduces the consumption of Diesel oil, but it also improves the combustion quality.The authors acknowledge that this study is only a starting basis: further investigation is required to cover all the aspects related to the industrial application of this syngas-Diesel combustion concept, in particular the impact on pollutant emission and on engine durability.

Correlation-powered information engines and the thermodynamics of self-correction.

Information engines can use structured environments as a resource to generate work by randomizing ordered inputs and leveraging the increased Shannon entropy to transfer energy from a thermal reservoir to a work reservoir. We give a broadly applicable expression for the work production of an information engine, generally modeled as a memoryful channel that communicates inputs to outputs as it interacts with an evolving environment. The expression establishes that an information engine must have more than one memory state in order to leverage input environment correlations. To emphasize this functioning, we designed an information engine powered solely by temporal correlations and not by statistical biases, as employed by previous engines. Key to this is the engine's ability to synchronize-the engine automatically returns to a desired dynamical phase when thrown into an unwanted, dissipative phase by corruptions in the input-that is, by unanticipated environmental fluctuations. This self-correcting mechanism is robust up to a critical level of corruption, beyond which the system fails to act as an engine. We give explicit analytical expressions for both work and critical corruption level and summarize engine performance via a thermodynamic-function phase diagram over engine control parameters. The results reveal a thermodynamic mechanism based on nonergodicity that underlies error correction as it operates to support resilient engineered and biological systems.

Estimation of operational parameters for a direct injection turbocharged spark ignition engine by using regression analysis and artificial neural network

This study was aimed at estimating the variation of several engine control parameters within the rotational speed-load map, using regression analysis and artificial neural network techniques. Duration of injection, specific fuel consumption, exhaust gas at turbine inlet, and within the catalytic converter brick were chosen as the output parameters for the models, while engine speed and brake mean effective pressure were selected as independent variables for prediction. Measurements were performed on a turbocharged direct injection spark ignition engine fueled with gasoline. A three-layer feed-forward structure and back-propagation algorithm was used for training the artificial neural network. It was concluded that this technique is capable of predicting engine parameters with better accuracy than linear and non-linear regression techniques.

Numerical analysis of a downsized spark-ignition engine fueled by butanol/gasoline blends at part-load operation

In this paper, the performance of a turbocharged SI engine, firing with butanol/gasoline blends, has been investigated by means of numerical simulations of the engine behavior. When engine fueling is switched from gasoline to alcohol/gasoline mixture, engine control parameters must be adapted. The main necessary modifications in the Electronic Control Unit have been highlighted in the paper.Numerical analyses have been carried out at partial load operation and at two different engine speeds (3000 and 4000rpm). Several n-butanol/gasoline mixtures, differing for the alcohol contents, have been analyzed.Such engine performances as torque and indicated efficiency have been evaluated. Both these characteristics decrease with the alcohol contents within the mixtures. On the contrary, when the engine is fueled by neat n-butanol, torque and efficiency reach values about 2% higher than those obtained with neat gasoline.Furthermore, the optimal spark timing, for alcohol/gasoline mixture operation, must be retarded (up to 13%) in comparison with the correspondent values of the gasoline operation.In general, engine performance and operation undergo little variations when fuel supplying is switched from gasoline to alcohol/gasoline blends.

Thermophysical effects of water driven copper nanoparticles on MHD axisymmetric permeable shrinking sheet: Dual-nature study.

The present study is dedicated to analyze the dual-nature solutions of the axisymmetric flow of a magneto-hydrodynamics (MHD) nanofluid over a permeable shrinking sheet. In those phenomena where the fluid flow is due to the shrinking surface, some reverse behaviors of the flow arise because of vorticity effects. Despite of heat transfer analysis, the main purpose of the present study is to attain the solutions of the complex nature problem that appear in reverse flow phenomena. Thermophysical properties of both base fluid (water) and nanoparticles (copper) are also taken into account. By means of similarity transformation, partial differential equations are converted into a system of coupled nonlinear ordinary differential equations and then solved via the Runge-Kutta method. These results are divided separately into two cases: the first one is the unidirectional shrinking along the surface (m = 1) and the other one is for axisymmetric shrinking phenomena (m = 2) . To enhance the thermal conductivity of base fluid, nanoparticle volume fractions (0≤φ ≤ 0.2)) are incorporated within the base fluid. The numerical investigation explores the condition of existence, non-existence and the duality of similarity solution depends upon the range of suction parameter (S) and Hartmann number (M). The reduced skin friction coefficient and local Nusselt number are plotted to analyze the fluid flow and heat transfer at the surface of the shrinking sheet. Streamlines and isotherms are also plotted against the engineering control parameters to analyze the flow behavior and heat transfer within the whole domain. Throughout this analysis it is found that both nanoparticle volume fraction and Hartmann number are increasing functions of both skin friction coefficient and Nusselt number.

Review of Sensing Methodologies for Estimation of Combustion Metrics

For reduction of engine-out emissions and improvement of fuel economy, closed-loop control of the combustion process has been explored and documented by many researchers. In the closed-loop control, the engine control parameters are optimized according to the estimated instantaneous combustion metrics provided by the combustion sensing process. Combustion sensing process is primarily composed of two aspects: combustion response signal acquisition and response signal processing. As a number of different signals have been employed as the response signal and the signal processing techniques can be different, this paper did a review work concerning the two aspects: combustion response signals and signal processing techniques. In-cylinder pressure signal was not investigated as one of the response signals in this paper since it has been studied and documented in many publications and also due to its high cost and inconvenience in the application.

Modeling engine fuel consumption and NOx with RBF neural network and MOPSO algorithm

In this study, artificial neural network (ANN) modeling is used to predict the fuel consumption and NOx emission of a four stroke spark ignition (SI) engine. Calibration engineers frequently want to know the responses of an engine for the entire range of operating conditions in order to change engine control parameters in the electronic control unit (ECU), to improve performance and reduce emissions. However, testing the engine for the complete range of operating conditions is a very time and labor consuming task. As alternative, ANN is used in order to predict fuel consumption and NOx emission. In the proposed approach, the multi-objective particle swarm optimization (MOPSO) is used to determine weights of radial basis function (RBF) neural networks. The goal is to minimize performance criteria as root mean square error (RMSE) and model complexity. A sensitivity analysis is performed on MOPSO parameters in order to provide better solutions along the optimal Pareto front. In order to select a compromised solution among the obtained Pareto solutions, a fuzzy decision maker is employed. The correlation coefficient R2 is used to compare the engine responses with the obtained by the proposed approach.

The Research on Anaerobic Bio-Hydrogen Production Using UASB Reactor from Molasses Wastewater

The principle and engineering control parameters of anaerobic bio-hydrogen in an up-flow anaerobic sludge blanket reactor are introduced, especially on the research situation and development trend of this technology. Many theoretical achievements of bio-hydrogen production using UASB reactor have been made, but the large scale industrialization of this technology has not been realized because there are still some difficulties in start-up and operation of the UASB reactor. Finally, some strategies and suggestions are proposed as guidance for further research.

실험계획법에 의한 가솔린 GDI+MPI 엔진의 연비 및 성능향상 관점에서의 운전영역별 연료분사 전략에 관한 연구

The gasoline direct injection (GDI) system is considerably spreading in automotive market due to its advantages. Nevertheless, since GDI system emit higher particle matter (PM) due to its combustion characteristics, it is difficult to meet strengthened emission regulation in near future. For this reason, a combined GDI with MPI system, so-called, dual injection (DUI) system is being investigated as a supplemental measure for the GDI system. This paper focused on power and fuel consumption effect by injection mode strategy of DUI system in part load and idle engine operating condition. In this study, port fuel injectors are installed on 2.4 liters GDI production engine in order to realize DUI system. And, at each injection mode, DOE (design of experiment) method is used to optimize engine control parameters such as dual injection ratio, start of injection timing, end of injection timing, CAM position and so on. As a consequence, DUI mode shows slightly better or equivalent fuel efficiency compared to conventional GDI engine on 9 points fuel economy mode as well as MPI mode shows less fuel consumption than GDI mode during idle operation. Furthermore, DUI system shows improvement potential of maximum 2.0% fuel consumption and 1.1% performance compared to GDI system in WOT operating condition.

Mobile source air toxic emissions from direct injection spark ignition gasoline and LPG passenger car under various in-use vehicle driving modes in Korea

Mobile source air toxic (MSAT) emissions from a direct injection spark ignition (DISI) passenger vehicle fueled with gasoline and liquid phase liquefied petroleum gas (LPG) were compared using a chassis dynamometer under several in-use vehicle driving conditions. For operation of a dedicated LPG-DI engine, low-pressure fuel systems were specially installed and various engine control parameters were recalibrated considering different chemical properties of LPG. A series of the National Institute of Environmental Research (NIER) modes for determining the emission factors of in-use vehicles in Korea were chosen to quantify not only the regulated emissions with particles but also the unregulated emissions of carbonyls, BTEX, and PAHs from a DISI light-duty vehicle (LDV) with gasoline and LPG. The regulated and particle emissions of LPG-DI vehicles showed strong reduction, and the proportions of sub-23nm particles were 32–35% in gasoline and 50–65% in LPG. The results revealed that the levels of the MSAT emissions from a DISI engine were closely related to the driving patterns and the fuel properties. A substantial reduction of regulated emissions, particulates, BTEX, and particle-bound PAH emissions was achieved from a LPG-DI vehicle in real driving conditions. Carbonyl compounds acetaldehyde and acrolein showed significant increment from a LPG-DI vehicle.

Investigation into the trade-off between the part-load fuel efficiency and the transient response for a highly boosted downsized gasoline engine with a supercharger driven through a continuously variable transmission

Downsizing is an established trend in the development of passenger car engines. However, the benefits of an improved fuel economy are often obtained at the expense of the engine’s dynamic response (owing to increasing demands on the boosting system) and, consequently, the vehicle driveability. The use of a continuously variable transmission in the supercharger driveline offers increased control flexibility over the air path, which could allow more suitable calibrations to be developed. This paper gives details of a co-simulation-based investigation into the trade-off between the steady-state part-load fuel efficiency and the resulting tip-in transient response for a highly boosted downsized gasoline engine. The engine was a 2.0 l in-line four-cylinder unit, designed to replace a 5.0 l, naturally aspirated V8, equipped with a positive-displacement supercharger in a sequential series arrangement with a fixed-geometry turbocharger with an external wastegate. The supercharger can be de-clutched and bypassed, and therefore three separate supercharger engagement regimes were investigated for part-load operation, defined as follows: with the supercharger disengaged and bypassed; with the supercharger engaged with a fixed drive ratio; with the supercharger engaged using a variable ratio (i.e. through a continuously variable transmission). For each of these supercharger engagement regimes, design-of-experiments and optimisation techniques were used to find the best settings for the key engine control parameters such as the intake and exhaust valve timings and the exhaust gas recirculation rate. Using these calibrations as a starting point, the transient performance was then assessed in fixed-speed tip-in simulations. The trade-off situation was found to be highly complex; identifying the best overall balance of the steady-state efficiency and the dynamic performance requires a subjective assessment. However, the continuously variable transmission does provide the best potential for dynamic response combined with a satisfactory fuel economy. It is suggested that the most suitable solution would be to have multiple user-selectable calibrations, such as the ‘economy’ and ‘sport’ modes used on many modern vehicles.

The Research Progress of Particulate Emissions from Vehicles with Gasoline Direct Injection Engines

The objective of this research is to introduce the main gasoline direct injection vehicle particulate emissions characteristics researches in the world. Many investigations of particulate sizing and number count from gasoline direct injection (GDI) vehicles at different driving cycles were performed. Lots of particulate emissions are measured for FTP-75, NEDC, HWTET, SC03, and US06 cycles and these cycles can reflect different aspects of the particulate emissions. In some papers, both engine-out and tailpipe emissions were measured. Some investigation showed high sensitivity of the particulate number or size distribution to changes with the engine control parameters including A/F, ignition timing, EOI and so on.On the whole, the particulate number during different Driving Cycle is shown along with further analysis of the transient particulate emissions. The cold start process obviously affects particulate formation. Even beyond cold start, the particulate number emissions decrease as the test progresses. The results coming from the particulate measurement system sampling directly from the exhaust showed very rapid increases in particulate emissions during engine transients.

Modeling of diesel oxidation catalysts for calibration and control purpose

An approach to the analysis of the performance of the diesel oxidation catalysts is presented in this article. A modeling methodology is proposed, whose main characteristics are the usage of a limited set of input data for the execution of the simulations, the minimal effort required for the preliminary calibration of the models and the reduced computational time. The developed diesel oxidation catalyst model structure is described, and its predictive capability is shown by means of a comparison with experimental measurements. The model is based on quasi-zero-dimensional and quasi-steady-state approaches, which ensure a reasonable compromise between practicality of usage (including faster than real-time computational time) and quality of the results. Thanks to the quick execution and the accuracy of the results, the proposed modeling approach can be used not only for the development of the diesel powertrains but also for the optimization of the related control and calibration strategies. This process is particularly effective when the models for the aftertreatment systems are coupled with models for the prediction of the engine-out quantities and with software tools for the virtual calibration of the main engine and exhaust system control parameters. A specific example of the effectiveness of this kind of analysis is also given in this article, with focus on the assessment of the system robustness.

Computer-aided conversion of an engine from diesel to methane

The paper proposes an analytical methodology that uses empirical based models and CFD simulations to efficiently evaluate design alternatives in the conversion of a diesel engine to either CNG dedicated or dual fuel engines. The procedure is performed in five steps. Firstly, a database of different combustion chambers that can be obtained from the original piston is obtained. The chambers in the database differ for the shape of the bowl, the value of the compression ratio, the offset of the bowl and the size of the squish region. The second step of the procedure is the selection, from the first database, of the combustion chambers able to resist to the mechanical stresses due to the pressure and temperature distribution at full load. For each combination of suitable combustion chamber shape and engine control parameters (ignition/injection crank angle, EGR, etc.), a CFD simulation is used to evaluate the combustion performance of the engine. Then, a post-processing procedure is used to evaluate the detonation tendency and intensity of each combination. All the tools developed for the application of the method have been linked in the ModeFrontier optimization environment in order to perform the final choice of the combustion chamber.The overall process requires not more of a week of computation on the four processor servers considered for the optimization. Moreover, the selected chambers can be obtained from the original piston of the engine. Therefore, the conversion cost of the engine is quite small compared with the case of a completely new piston. The paper also describes the application of the procedure to two different engines.