Optimization Of Diesel Engine Research Articles

Thermodynamic optimization of diesel engines equipped with Shemax injection system using genetic algorithm

Thermodynamic optimization of diesel engines equipped with Shemax injection system using genetic algorithm

High altitude performance optimization of diesel engine fueled with biodiesel-methanol blends using response surface methodology

High altitude performance optimization of diesel engine fueled with biodiesel-methanol blends using response surface methodology

CFD-Based Optimization of a Diesel Engine Waste Heat Recycle System

A dedicated heat exchanger model is introduced for the optimization of heavy-duty diesel engines. The model is a prerequisite for the execution of CFD simulations, which are used to improve waste heat recovery in these systems. Several optimization methods coupled with different types of working fluids are compared in terms of exergy efficiency and heat exchanger complicity. The three considered optimization methods all lead to significant improvements in the R245fa and R1233zd systems with a comparatively low evaporation temperature. The optimal R245fa system has the highest efficiency increase (77.49%). The cyclopentane system displays the highest effi- ciency among the optimized ORC (Organic Rankine Cycle) systems, yet achieved by using a much heavier evaporator HEC (Heat Exchanging Core). In contrast, the 96.84% efficiency increase for the optimized R1233zd is achieved with only 68.96% evaporator weight.

Multi-objective-parametric optimization of diesel engine powered with fuel additive 2-ethylhexyl nitrate-algal biodiesel

The present study examined the effect of the cetane improver 2-Ethylhexyl nitrate (EHN) on the performance and emission characteristics of an engine fueled by an algal biodiesel-diesel blend. The multi-objective response surface technique (MORSM) was used in combination with the Box-Behnken design to decrease the number of trials and conserve precious resources such as human effort, resources, and time. To link the engine control parameters and outputs, analysis of variance was used to build prediction models in the form of mathematical expressions. To optimize the engine operating settings for the optimum efficiency-least emission combination, a MORSM-based desirability technique was used. The optimized engine operating settings were 23-degree crank angle before top dead center (°CA bTDC), 77.16 % engine load, and 5500 ppm EHN. Performance and combustion output were 31 % BTE, 0.28 kg/kWh BSFC, and 66.29 bar PCP at these optimal operating ranges. In terms of emissions, CO was 0.01 vol%, HC was 25.1 ppm, and NOx was 867 ppm. The present research will help researchers contemplating employing these fuels to identify the optimal values.

Fuel economy optimization of diesel engine for plug-in hybrid electric vehicle based on equivalent operating points

The plug-in hybrid electric vehicle (PHEV) has been progressively penetrated in the urban public transport system for its special advantages of energy saving and emission reduction potential. In order to improve the fuel economy of PHEV engine, an optimization study on the engine control parameters is carried out and applied on a PHEV with a rule-based energy management strategy (EMS) in this paper. Firstly, the mathematical model of diesel engine is established on GT-Power platform to accurately reflect the fuel consumption characteristics of engine. Secondly, a control parameter optimization method based on engine equivalent operating point is proposed and four key engine control parameters are optimized by genetic algorithm (GA). Thirdly, the optimization and calibration of the PHEV engine is performed under ChinaCity driving cycle. The results show that the maximum reduction of engine brake specific fuel consumption (BSFC) on the optimal operation line is 3.56%, and the equivalent fuel consumption of PHEV under ChinaCity, WVUCITY and WVUSUB driving cycles is reduced by 2.62%, 2.24% and 2.05%, respectively.

Model‐guided extremum seeking–case studies

SummaryIn practice, data‐driven control and optimization techniques are applied to address problems in engineering systems of which the model is either unavailable or so complicated that a model‐based analytic design can be hardly carried. Among them, the extremum seeking (ES) is a popular model‐free or data‐driven optimization method that has been effectively applied to provide optimal solutions to various industrial control systems. In this article, a new design philosophy, called the model‐guided ES, which is a special case of model‐guided data‐driven (MGDD) optimization, is presented and demonstrated with two successful case studies. In particular, it is shown that, in these two cases, how models of physical systems, even if imperfect or developed in a data‐driven way instead of the first‐principle based approach, could be integrated together with the conventional ES algorithm to deliver much improved and guaranteed convergence performance and the ultimate bound. It is noted that the first case is for the automotive diesel engine optimization and the second case for the automated regulation of LiDAR detection range. Both cases are successfully validated with experiments.

Parameter Change in Engine Simulation and Performance Optimization of Diesel Engine

Diesel internal combustion engines have been widely used in automobiles, ships, power generation, and other fields, laying a foundation for modern science and technology. Due to the wide application of internal combustion engines, the working efficiency and exhaust gas generated by internal combustion engines have become issues of common concern. In order to optimize the working efficiency and emissions, simulations are carried out under different conditions by using Cantera IC Engine code. Through analysis, the relationship between similar factors and their effects on emissions and thermal efficiency are shown, thus obtaining the most effective method to improve efficiency and reduce emissions. On the one hand, it is found that factors, such as the compression ratio, have a very intuitive impact on the efficiency of the engine. On the other hand, the ambient temperature and air pressure have less influence on the engine operating within the controllable range. These results provide a general idea for diesel engine optimization under certain environments.

Optimization of diesel engine operating parameters fueled with palm oil-diesel blend: Comparative evaluation between response surface methodology (RSM) and artificial neural network (ANN)

Engine performance and emission characteristics of palm oil-diesel blends tested on single-cylinder diesel engine by several engine loads and injection advances. Exhaust emissions and smoke were recorded using MRU Delta 1600L and MRU Optrans 1600 model gas analyzer, respectively. Brake thermal efficiency (BTE), exhaust gas temperature (EGT), carbon monoxide (CO), hydrocarbon (HC), smoke and nitrogen oxides (NOx) were optimized as output factors considering engine load, injection advance and palm oil percentage as input variables using response surface methodology (RSM) and artificial neural network (ANN). The developed ANN and RSM models showed superior predictive certainty with big R2 (correlation coefficient) values. The RSM models showed better performance and have higher R2 values than ANN models. The developed RSM model has R2 values over 0.90 while the R2 values of ANN model are between 0.88 and 0.95. The values of mean relative error (MRE) and root mean square error (RMSE) for all the responses were low. Optimum responses were found by 69.11%, 196.25 ppm, 0.126%, 189.764 ppm, 155.49 ℃ and 30.75%, respectively for smoke, NOx, CO, HC, EGT and BTE with optimum operating factors as 17.88% palm oil percentage, 35 °CA injection advance and 780-watt engine load. The applied models gave good results that are beneficial for estimating and optimizing the engine performance and emission characteristics.

Diesel engine optimization and exhaust thermal management by means of variable valve train strategies

Due to the need to achieve a fast warm-up of the after-treatment system in order to fulfill the pollutant emission regulations, a growing interest has arisen to adopt variable valve timing technology for automotive engines. Several variable valve timing strategies can be used to achieve an increment in the after-treatment upstream temperature by increasing the residual gas amount. In this study, a one-dimensional gas dynamics engine model has been used to carry out a simulation study comparing several exhaust variable valve actuation strategies. A steady-state analysis has been done in order to evaluate the potential of the different strategies at different operating points. Finally, the effect on the after-treatment warm-up, fuel economy and pollutant emission levels was evaluated over the worldwide harmonized light vehicles test cycle. As a conclusion, the combination of an advanced exhaust (early exhaust valve opening and early exhaust valve closing) and a delayed intake (late intake valve opening and late intake valve closing) presented the best trade-off between exhaust temperature increment and fuel consumption, which achieved a mean temperature increment during low-speed phase of the worldwide harmonized light vehicles test cycle of 27 °C with a fuel penalty of 6%. The exhaust valve re-opening technique offers a worse trade-off. However, the exhaust valve re-opening leads to lower nitrogen oxide (29% less) and carbon monoxide (11% less) pollutant emissions.

A review of phenomenological spray penetration modeling for diesel engines with advanced injection strategy

Driven by the increasingly remarkable problems of environmental pollution and energy crisis, the combustion optimization of diesel engine seems to be more urgent than ever, therefore, advanced injection strategies are gradually proposed and employed in modern diesel engines. Phenomenological model, which serves as an effective tool to conduct the parametric study on the spray penetration, needs to be improved to fit the intensified injection condition. Since that there are no attempts to review the spray penetration model developments, in order to help to build a comprehensive understanding of diesel spray propagation, this article briefly summarized the early history and introduced the widely used classical and improved phenomenological spray penetration models. Besides, to provide a helpful reference for selection of suitable models, the modeling methods were analyzed and features and simulation of various models were discussed and compared. After that, the trend of modeling methods and promising directions for future spray modeling were suggested.

Improving PM-NOx trade-off with paraffinic fuels: A study towards diesel engine optimization with HVO

The current work investigates the impact of a paraffinic fuel on combustion and emissions of a diesel engine, examining alternative injection strategies for the full exploitation of the fuel characteristics. The paraffinic fuel used was the HVO (Hydrotreated Vegetable Oil) produced by Neste Oil with the brand name NEXBTL. The study was conducted on a light-duty turbocharged and aftercooled common-rail diesel engine, with both HVO and a conventional diesel fuel. Four steady-state operating points were examined, at low and medium engine speeds (1500 and 3000 rpm) and loads (35 and 100 Nm), typical of daily driving of a passenger car. The key contribution of the study is a comprehensive analysis of the phenomena influencing the crank angle resolved in-cylinder parameters, as well as interlinking the effects of different variations of injection pressure (default and 300 bar higher), pilot injection timing (default and ± 5°CA) and main injection timing (default and ± 2°CA) on gaseous emissions and particulate matter (PM). The findings have shown that at default engine settings the use of HVO results in up to 40% reduction of engine-out PM and HC emissions without appreciable changes in NOx emissions. The significant reduction of engine-out PM levels, facilitates the adoption of measures for NOx emissions limitation. The latter are reduced by up to 20% when the main injection timing is retarded (by 2° CA in the present study), while PM emissions are still kept well below the respective diesel fuel levels.

Constrained multivariable extremum-seeking for online fuel-efficiency optimization of Diesel engines

This work presents a new method for online fuel-efficiency optimization of Diesel engines, using constrained extremum-seeking. A two-input optimization problem, which is suitable for extremum-seeking, is integrated into a tracking control system. As a result, both air-path and fuel-path actuators are used for tracking and extremum-seeking. A key element of the proposed method is a cost function based on real-time BSFC estimation. Moreover, an existing constrained extremum-seeking method is extended to multiple output constraints. Experiments on a Euro-VI heavy-duty Diesel engine demonstrate the constraint handling, robustness with respect to real-world disturbances, and the fuel saving potential of the control design.

Optimization of compression ignition engine fueled with diesel - chaulmoogra oil - diethyl ether blend with engine parameters and exhaust gas recirculation

This study investigates the performance, combustion and emission characteristics of diesel (D)/straight vegetable oil (SVO)/diethyl ether (DEE) blend in a variable compression ratio engine (VCR), variable engine speed direct injection compression ignition (CI) engine. The compression ratio (CR), speed (N), and load (L) were taken as input factors for the diesel engine optimization. This investigation is done through a combination of experimental data analysis and artificial neural network (ANN) modeling. The response surface methodology (RSM) optimization concerned to minimize the engine emissions and maximize the engine performance. Three optimization works were conducted for 65% D+25% SVO+10% DEE blend, in optimization-1 (opti-1) considered 0% exhaust gas recirculation (EGR), Opti-2 considered 5% EGR and Opti-3 considered 10% EGR. Compared to diesel, carbon monoxide (CO), oxides of nitrogen (NOx), and hydrocarbon (HC) were reduced by 12.8%, 4.19% and 9.61% respectively for blend fuel in opti-2.

Development of On-board Polytropic Index Prediction Model for Injection Timing Optimization of Diesel Engines

Diesel engines are required to reduce exhaust emissions during real-world operations. In this regard, a new control concept called model-based control has been explored. Unlike the conventional method of relying on steady-state measurements, model-based control allows cycle-by-cycle optimization of control inputs based on physical principles. Existing models for combustion control have been using empirical equations to predict polytropic index for the compression stroke for estimation of in-cylinder pressure and temperature at fuel injection. Therefore, in this study, a polytropic index prediction model was developed in MATLAB to maintain the engine performance under transient conditions and to reduce the required number of experiments. The model includes a heat loss model and a gas flow model to consider the effect of wall heat transfer and gas flows inside the cylinder. The computational load of the model was reduced through discretization of a single engine cycle into several calculation points. The model was validated against numerical simulation results under steady conditions first, and then applied to transient conditions for more realistic operational conditions. The model estimated the polytropic index with average errors under steady and transient conditions with 0.22% and 0.37%, respectively. Finally, the calculation time of the model was evaluated to be 50.6 μs. It was concluded the model can be implemented on a model-based controller in the future.

Volumetric properties of binary mixtures of methanol with ethyl caprylate, ethyl caprate, and ethyl laurate from 283.15 to 318.15 K

Density and viscosity for mixtures of alkyl esters with alcohols is essential not only for simulation and optimization of diesel engine but also for the understanding of the interactions between them. The new densities of binary mixtures of methanol with three fatty acid ethyl esters (ethyl caprylate, ethyl caprate, and ethyl laurate) were measured at the atmospheric pressure for the temperatures ranging from (283.15 to 318.15) K over the entire composition range using an Anton Paar digital vibrating U-tube densimeter (model DMA 5000 M). A Redlich–Kister type equation was correlated using the excess molar volumes calculated with the experimental values and used to represent the densities of the liquid mixtures as a function of temperature and concentration.

Robust fuel consumption estimation for on-line optimization of diesel engines

Accurate estimation of Brake Specific Fuel Consumption (BSFC) is required to enable on-line optimization of real-world fuel efficiency of diesel engines. This work aims to develop a BSFC estimation method which is accurate enough for an adaptive controller for on-line engine optimization, e.g., using Extremum Seeking. In this paper two different BSFC estimation methods are evaluated: A heat-release based method using in-cylinder pressure sensors and an approach based on injector opening time. Analysis of the two approaches shows that the injector opening time approach yields the highest accuracy. This method together with an adaptive controller is validated experimentally on a Euro-VI diesel engine. Experimental results show that the BSFC estimation is robust against variations in combustion phasing and scavenging losses. The estimated location, in terms of combustion phasing and scavenging losses, of the BSFC minimum remains within 0.1% relative error with respect to the measured BSFC minimum.

Taguchi-based combined grey relational and principal component analyses for multi-response optimization of diesel engines

PurposeDiesel engine can produce power more efficiently with lower exhaust emissions when operated at optimum input parameter settings. To achieve this goal, the purpose of this paper is to optimize the input parameters of diesel engine which will lead to optimum performance and exhaust emissions.Design/methodology/approachTo achieve the goal of improving diesel engine performance and exhaust emissions, four input parameters were considered in the study. Five different levels of each input parameter were taken. Four response variables under no load, half load and full load conditions were recorded. Experiments were performed in random manner according to selected Taguchi L25 orthogonal array. The data were analyzed using grey relational analysis coupled with principal component analysis. Analysis of S/N ratio was performed to obtain the optimum combination of input parameters. The grey relational grade at optimum setting of the input parameters was obtained by regression analysis.FindingsResults of the current research work give the optimum input parameter settings for no load, half load and full load conditions of diesel engine. Engine produces power more efficiently with low exhaust emissions when operated at these optimum settings.Practical implicationsIn view of the compliance to the stringent air pollution norms of the nations and fast depleting fossil fuels, it is of the utmost importance to design and operate the engine in the optimum range of its input parameters so that it produces more power with low exhaust emissions. This paper aims at optimizing input parameters of diesel engine to improve performance and exhaust emissions. Results of the study presented in this paper are significantly useful for diesel engine-related researchers and professionals.Originality/valueFrom the literature review, it appears that only few researchers have conducted studies pertaining to the optimization of the input parameters of diesel engine to improve performance or exhaust emissions. Although few studies related to the optimization of compression ratio, fuel injection timing, fuel injection pressure and air pressure have been reported, no work related to optimization of temperature and pressure of turbocharged air has been reported. Therefore, the main focus of the current research work is on optimizing the charge air temperature and pressure with respect to performance and exhaust emissions.

Performance optimization of diesel engine fueled with diesel–jatropha curcas biodiesel blend using response surface methodology

The present work is aimed at unfolding the effect of fuel supply parameters such as Fuel injection pressure (FIP), Start of injection timing (SOI), Pilot-main injection intervals (PMII) on performance and emission characteristics of 20 % blend of Jatropha curcas biodiesel (J20) under light load operation of a diesel engine. The experiments were designed using design of experiments based on the fractional factorial design of Response surface methodology (RSM). Multiple regression models developed using RSM for measured responses like nitrogen oxides (NOX), SOOT, hydrocarbon (HC), Brake specific fuel consumption (BSFC) and Brake thermal efficiency (BTE), were found to be statistically significant by Analysis of variance (ANOVA). Interactive effects among FIP, SOI and PMII were analyzed using response surface graphs that were fitted using developed RSM models. Optimization was performed using the desirability approach of the RSM for lesser emissions and BSFC simultaneously with superior BTE. A FIP of 134.11 MPa, SOI of 6.4 BTDC, and PMII of 5.8 CA were found to be optimal values for J20 in the test engine of 21 kW at 1800 rpm. The results of this study show that at optimal input parameters, the values of the NOX, SOOT, HC, BSFC and BTE with a high desirability of 96.7 % are 603.44 ppm, 0.037 FSN, 12.73 ppm, 233.26 g/kW h and 37.31 %, respectively.

Multi-response optimization of diesel engine operating parameters running with water-in-diesel emulsion fuel

Water-in-diesel emulsion fuel is a promising alternative diesel fuel, which has the potential to promote better performance and emission characteristics in an existing Diesel engine without engine modification and added cost. The key factor that has to be focused with the introduction of such fuel in existing Diesel engine is desired engine-operating conditions. The present study attempts to address the previous issue with two-phases of experiments. In the first phase, stable water-in-diesel emulsion fuels (5, 10, 15, and 20 water-in-diesel) are prepared and their stability period and physico-chemical properties are measured. In the second phase, experiments are conducted in a single cylinder, 4-stroke Diesel engine with pre-pared water-in-diesel emulsion fuel blends based on L16 orthogonal array suggested in Taguchi?s quality control concept to record the output responses (perormance and emission levels). Based on signal-to-noise ratio and grey relational analysis, optimal level of operating factors are determined to obtain better response and verified through confirmation experiments. A statistical analysis of variance is applied to measure the significance of individual operating parameters on overall engine performance. Results indicate that the emulsion fuel prepared by Sorbitan monolaurate surfactant at high stirrer speed endows with better emulsion stability and acceptable variation in physicochemical properties. Results of this study also reveal that the optimal parametric setting effectively improves the combustion, performance, and emission characteristics of Diesel engine.

An Adaptive Particle Swarm Optimization for Engine Parameter Optimization

An adaptive particle swarm optimization is proposed to improve the fuel efficiency and reduce exhaust emissions in diesel engine. The proposed algorithm introduces an adaptive inertia weight and modified mutation mechanism for velocity and particle update when the global best particle falls into possible local optima. The proposed PSO has been evaluated on 8 benchmark functions, together with other adaptive PSO algorithms. The results show the proposed algorithm has faster convergence, better solution accuracy and reliability in comparison with other algorithms. Diesel engine must meet the increasing demands for higher efficiency and cleaner exhaust gases, which is a multi-objective optimization problem. In the paper, diesel engine optimization problem is firstly converted to single objective optimization problem, and then the proposed PSO is adopted to find optimal engine operation parameters. Results demonstrate potential of future application in car.