1,721,025 research outputs found
Validation of a NOx estimation methodology based on the analysis of in-cylinder pressure trace
Full text linkInternal 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
Development of a Torsiometer for On-board Application
No full textModern combustion control strategies require accurate combustion control to meet the requirements for pollutant emissions reduction. Optimal combustion control can be achieved through a closed-loop control based on indicated quantities, such as engine torque and center of combustion, which can be directly calculated through a proper processing of in-cylinder pressure trace. However, on-board installation of in-cylinder pressure sensors is uncommon, mainly because it causes a significant increase in the cost of the whole engine management system. In order to overcome the problems related to the on-board installation of cylinder pressure sensors, this work presents a remote combustion sensing methodology based on the simultaneous processing of two crankshaft speed signals. To maximize the signal-to-noise ratio, each speed measurement has been performed at opposed ends of the crankshaft, i.e. in correspondence of flywheel and distribution wheel. Since an engine speed sensor, usually faced to the flywheel, is already present on-board for other control purposes, the presented approach requires that an additional speed sensor is installed. Proper processing of the signals coming from the installed speed sensors allows extracting information about crankshaft's torsional behavior. Then, the calculated instantaneous crankshaft torsion can be used to real-time estimate both torque delivered by the engine and combustion phasing within the cycle. The presented methodology has been developed and validated using a light-duty L4 Common-Rail Diesel engine mounted in a test cell at University of Bologna. However, the discussed approach is general, and can be applied to engines with a different number of cylinders, both CI and SI
Control-Oriented Engine Thermal Model
Full text linkThe optimization of modern internal combustion engines and vehicles led several researchers to investigate the effects of the coolant system on overall efficiency losses. Electric water pumps have been proposed as a solution to decrease the high power consumption that typically affects mechanically-driven water pumps at high engine speed. Furthermore, decoupling the coolant flow from engine speed allows achieving a better warm-up behavior. The coolant system components, however, also impact vehicle efficiency: the radiator area affects the overall aerodynamic drag coefficient, especially for race vehicles and motorcycles. A thermal model can be used to assess the effects of the components characteristics (pump size, efficiency, speed; radiator surface, fan size, etc.) both on the coolant system capability to reach and maintain the target temperature, and the power it requires. The same model-based approach can be used for optimal thermal management, to control the coolant system actuators (electric pump and valves, fan). The paper shows how the thermal behavior of the engine can be represented by means of a concentrated parameters model, taking into account the main coolant system components features. The model has been calibrated on a set of data referring to a high-performance motorcycle engine, including both idling and high vehicle speed conditions. The good agreement of the model output with experimental data both in static and dynamic conditions confirms that the model is able to catch a large part of the phenomena influencing the coolant temperature
Torque and Center of Combustion Evaluation Through a Torsional Model of the Powertrain
No full textThe continuous development of modern internal combustion engine (ICE) management systems is mainly aimed at combustion control improvement. Nowadays, performing an efficient combustion control is crucial for drivability improvement, efficiency increase (critical for spark ignited engines), and pollutant emissions reduction (critical in compression ignited engines). The most important quantities used for combustion control are engine load (indicated mean effective pressure (IMEP) or torque delivered by the engine) and center of combustion, i.e., the angular position in which 50% of fuel burned within the engine cycle is reached. Both quantities can be directly evaluated starting from in-cylinder pressure measurement, which could be performed using the newly developed piezoresistive pressure sensors for on-board applications. However, the use of additional sensors would increase the cost of the whole engine management system. Due to these reasons, over the past years, a methodology that allows evaluating both engine load and the center of combustion with no extra cost has been developed. This approach is based on engine speed fluctuation measurement, which can be performed using the same speed sensor already mounted on-board. The methodology is general and can be applied to different engine–driveline systems with different architectures and combustion orders. Furthermore, it is compatible with on-board requirements, since the evaluation of only one specific harmonic component of interest is required (depending on the engine–driveline configuration under investigation). In order to clarify all the issues related to the application of the presented approach, it has been applied to some different engines, both compression ignited and spark ignited, taking also into account the case of combustion not evenly spaced. For all the analyzed configurations, the results obtained using the estimation algorithm seemed to be adequate to feedback a closed-loop methodology for optimal combustion control
Turbogas Engines Rotational Speed Estimation Using Acoustic and Vibrational Measurements
No full textThe overall objective of this work is the development and validation of a real-time algorithm to estimate turbogas engine rotational speeds by using accelerometric or microphonic measurements. The main advantage of this method is the absence of any intrusive installation on the engine and the fact that it might be implemented, as redundant measurement, in parallel to typical tachometric instrumentation. The developed code analyses the acquired FFT spectrum in order to identify characteristic frequencies of engine rotating components and automatically track their evolution. Experimental tests have been performed on an Allison 250C18 turboshaft engine at the Propulsion Laboratory of the University of Bologna and estimated values have been compared with tachometric measurements. Preliminary results have demonstrated the feasibility of the proposed code and an appreciable accuracy of obtained estimations through both microphone and accelerometer
Machine learning assisted modeling of ignition delay in a light-duty gasoline compression ignition engine
Full text linkThis work proposes an innovative artificial neural network-based (ANN) approach to predict the ignition delay (ID) in a Gasoline Compression Ignition (GCI) engine using the information coming from standard sensors mounted on the engine. Moving toward the carbon neutrality of transport by using renewable and synthetic fuels, GCI combustion is considered a promising technology to achieve high engine efficiency and ultra-low pollutant emissions. As with other auto-ignition combustion concepts, a deep understanding of compression ignition dynamics is crucial for maintaining a stable and controllable combustion process in different operating and environmental conditions and enhancing engine performance and durability over time. Machine learning (ML) offers a promising modelling tool to lower the cost for testing control strategies compared to traditional physical or empirical approaches. An experimental campaign was conducted with 293 steady-state engine operating conditions to establish relationships between ignition delay and engine parameters, such as engine speed, load, intake and injection pressures, exhaust gas recirculation (EGR), and injection parameters, in a light-duty GCI engine. Then, an ANN-based model was trained and validated using a combination of holdout and k-fold cross-validation methods, along with a Bayesian regularization algorithm. The ignition delay estimation through the ANN-based model has shown a NRMSE percentage of 2.16 % and R2 of 0.99 on test dataset, demonstrating to be accurate enough for engine control and diagnosis purposes. This work aims at inspiring innovative ANN-based control strategies for promoting the use of advanced combustion methodologies, such as GCI combustion, as technical solution for production engines
Engine Acoustic Emission Used as a Control Input: Applications to Diesel Engines
No full textThe need for strategies that allow managing combustion in an adaptive way has recently widely increased. Especially Diesel engines aimed for clean combustion require a precise control of the combustion outputs. Acoustic emission of internal combustion engines contains a lot of information related to engine behavior and working conditions. Mechanical noise and combustion noise are usually the main contributions to the noise produced by an engine. Combustion noise in particular can be used as an indicator of the combustion that is taking place inside the combustion chamber and therefore as a reference for the control strategy. This work discusses the correlations existing between in cylinder combustion and the acoustic emission radiated by the engine and presents a possible approach to use this signal in the engine management system for control purposes. The application was tested by running several experimental tests, both in steady state and transient conditions, on a Diesel engine mounted in a test cell. Tests have been run in order to first identify the correlation existing between the different injection/combustion patterns that can be operated on the engine and the corresponding acoustic emission. Once the correlation between combustion process and engine noise has been identified it can be used to set up a closed-loop algorithm for optimal combustion control based on engine noise prediction
Automatic Combustion Control for Calibration Purposes in a GDI Turbocharged Engine
No full textCombustion phasing is crucial to achieve high performance and efficiency: for gasoline engines control variables such as Spark Advance (SA), Air-to-Fuel Ratio (AFR), Variable Valve Timing (VVT), Exhaust Gas Recirculation (EGR), Tumble Flaps (TF) can influence the way heat is released. The optimal control setting can be chosen taking into account performance indicators, such as Indicated Mean Effective Pressure (IMEP), Brake Specific Fuel Consumption (BSFC), pollutant emissions, or other indexes inherent to reliability issues, such as exhaust gas temperature, or knock intensity. Given the high number of actuations, the calibration of control parameters is becoming challenging. Many different approaches can be used to reach the best calibration settings: Design Of Experiment (DOE) is a common option when many parameters influence the results, but other methodologies are in use: some of them are based on the knowledge of the controlled system behavior, by means of models that are identified during the calibration process. The paper shows how the calibration can be managed using a different concept, based on the Extremum Seeking (ES) approach. The main idea consists in changing the values of each control parameter at the same time, identifying its effect on a cost or merit function (target function), allowing to shift automatically the control setting towards the optimum solution throughout the calibration procedure. The function is evaluated cycle by cycle, based on combustion analysis. Due to the control parameters continuous variations the target function values change: the ES objective is to drive the variations towards the setting minimizing the cost function. The methodology has been applied to data referring to a GDI turbocharged engine, trying to maximize IMEP or minimize BSFC, while limiting the knock intensity and exhaust gas temperature, using SA, AFR and VVT as control variables. Experimental data referring to the considered engine have been used to feed a combustion model, allowing to test the calibration approach: results show that the ES-based calibration is able to automatically change SA, lambda and VVT values, taking into account all the constraints, and finally reaching the optimal control setting, independently of the starting setting. Copyright © 2014 SAE International
Model Based Control of Intake Air Temperature and Humidity on the Test Bench
Full text linkEngine test benches are crucial instruments to perform tests on internal combustion engines. Possible purposes of these tests are to detect the engine performance, check the reliability of the components or make a proper calibration of engine control systems managing the actuations. Since many factors affect tests results in terms of performance, emissions and components durability, an engine test bench is equipped with several conditioning systems (oil, water and air temperature, air humidity, etc.). One of the most important systems is the HVAC (Heating, Ventilating and Air Conditioning), that is essential to control the conditions of the intake air. Intake air temperature, pressure and humidity should be controllable test parameters, because they play a key role on the combustion development. In fact, they can heavily affect the performance detected, such as power and specific consumption, and, in some cases, they may promote knock occurrence. This work presents an HVAC model-based control methodology, where each component of the air treatment system (humidifier, pre-heating and post-heating resistors, chiller and fan) is managed coupling open-loop and closed-loop controls. Each branch of the control model is composed of two parts, the first one to evaluate the target for the given HVAC component, based on the system physical model, the second one is a PID controller based on the difference between the set-point and the feedback values. The control methodology has been validated on an engine test bench where the automation system has been developed on an open software Real-Time compatible platform, allowing the integration of the HVAC control with all other functionalities concerning the test management. The paper shows the plant layout, details the control strategy and finally analyzes experimental results obtained on the test bench, highlighting the benefits of the proposed HVAC management approach
Hybrid solar and hydrogen energy system 0-D model for off-grid sustainable power system: A case in Italy
Full text linkOff-grid solar systems are one of the most promising solutions for achieving complete grid independence. Off-grid solar systems are one of the most promising solutions for achieving complete grid independence. However, the storage of large amounts of energy produced in the summer through solar panels becomes crucial However, the storage of large amounts of energy produced in the summer through solar panels becomes crucial to reach this goal and hydrogen, as a zero-CO2 energy carrier, could play a pivotal role. This paper presents a to reach this goal and hydrogen, as a zero-CO2 energy carrier, could play a pivotal role. This paper presents a case study on the integration and simulation of solar energy and hydrogen technologies in an off-grid energy case study on the integration and simulation of solar energy and hydrogen technologies in an off-grid energy plant for a teaching buildings complex in Italy. A 0-D virtual energy plant model has been developed aimed at plant for a teaching buildings complex in Italy. A 0-D virtual energy plant model has been developed aimed at estimating the net energy production and hydrogen consumption/production rates using different inputs of estimating the net energy production and hydrogen consumption/production rates using different inputs of irradiance (monthly average, daily) and energy demand (constant and variable daily consumption levels) in the irradiance (monthly average, daily) and energy demand (constant and variable daily consumption levels) in the buildings. The outcome of the analysis identifies the most convenient configuration of the plant in terms of sizing buildings. The outcome of the analysis identifies the most convenient configuration of the plant in terms of sizing and device interactions for achieving complete grid independence, and the impact of different inputs on the plant and device interactions for achieving complete grid independence, and the impact of different inputs on the plant performance. performance
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