1,721,206 research outputs found
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
Relating Knocking Combustions Effects to Measurable Data
No full textKnocking combustions heavily influence the efficiency of Spark Ignition
engines, limiting the compression ratio and sometimes preventing
the use of Maximum Brake Torque (MBT) Spark Advance (SA). A detailed
analysis of knocking events can help in improving the engine performance
and diagnostic strategies. An effective way is to use advanced 3D
Computational Fluid Dynamics (CFD) simulation for the analysis and
prediction of the combustion process. The standard 3D CFD approach
based on RANS (Reynolds Averaged Navier Stokes) equations allows
the analysis of the average engine cycle. However, the knocking phenomenon
is heavily affected by the Cycle to Cycle Variation (CCV): the effects
of CCV on knocking combustions are then taken into account, maintaining
a RANS CFD approach, while representing a complex running condition,
where knock intensity changes from cycle to cycle. The focus of the
numerical methodology is the statistical evaluation of the local
air-to-fuel and turbulence distribution at the spark plugs and their
correlation with the variability of the initial stages of combustion.
CFD simulations have been used to reproduce knock effect on the in-cylinder
pressure trace. For this purpose, the CFD model has been validated,
proving its ability to predict the combustion evolution with respect
to SA variations, from non-knocking up to heavy knocking conditions.
The CFD model allowed relating measurable data (i.e., the simulated
cylinder pressure signal) to other factors, representative of the
phenomena actually taking place during knocking combustions: for
each cell used in the CFD simulation, information such as pressure,
heat release, etc. are available and can be traced over the angular
domain. Furthermore, the analysis refers to hundredths of engine
cycles, leading to a comprehensive correlation between standard cylinder
pressure-based knock indexes and other indexes (only available in
a simulation environment), more representative of the actual knock
intensity. Copyright © 2015 SAE International
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
Evaluation of the Effects of a Twin Spark Ignition System on Combustion Stability of a High Performance PFI Engine
No full textAbstractThe continuous demand for high performances and low emissions engines leads the engine manufactures to set the operating range of combustion devices near to their stability limit. Combustion stability is closely related to the formation of the first ignition kernel: an effective way of lowering Cycle-by-Cycle Variation (CCV) is to enhance the start of combustion by means of multiple sparks. A Ducati engine was equipped with a Twin Spark ignition system and a consistent improvement in combustion stability arised for both part load and full load conditions.At part load a sensible reduction of cycle-by-cycle variability of indicated mean effective pressure was found, while at full load condition the twin spark configuration showed an increase of power, but with higher knocking tendency. The aim of this work is to better understand the root causes of the increased level of knock and to make a critical evaluation of most used knock indexes, by means of an accurate analysis of the experimental and simulated pressure signals.The numerical methodology based on a perturbation of the initial kernel by a statistical evaluation of mixture condition at ignition location. A lagrangian ignition model developed at University of Bologna was used, here modified to take into account the statistical distribution of mixture around the spark plugs. The RANS simulations proved to be accurate in representing all the main information related to combustion efficiency and knocking events
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Enhancement of Heavy-Duty Engines Performance and Reliability Using Cylinder Pressure Information
Full text linkSustainability issues are becoming increasingly prominent in applications requiring the use of heavy-duty engines. Therefore, it is important to cut the emissions and costs of such engines to reduce the carbon footprint and keep the operating expenses under control. Even if for some applications a battery electric equipment is introduced, the diesel-equipped machinery is still popular thanks to the longer operating range. In this field, the open pit mines are a good example. In fact, the Total Cost of Ownership (TCO) of the mining equipment is highly impacted by fuel consumption (engine efficiency) and reliability (service interval and engine life). The present work is focused on efficiency enhancements achievable through the application of a combustion control strategy based on the in-cylinder pressure information. The benefits are mainly due to two factors. First, the negative effects of injectors aging can be compensated. Second, cylindrical online calibration of the control parameters enables the combustion system optimization. The article is divided into two parts. The first part describes the toolchain that is designed for the real-time application of the combustion control system, while the second part concerns the algorithm that would be implemented on the Engine Control Unit (ECU) to leverage the in-cylinder pressure information. The assessment of the potential benefits and feasibility of the combustion control algorithm is carried out in a Software in the Loop (SiL) environment, simulating both the developed control strategy and the engine behavior (Liebherr D98). Our goal is to validate the control algorithm through SiL simulations. The results of the validation process demonstrate the effectiveness of the control strategy: firstly, cylinder disparity on IMEP (+/−2.5% in reference conditions) is virtually canceled. Secondly, MFB50 is individually optimized, equalizing Pmax among the cylinders (+/−4% for the standard calibration) without exceeding the reliability threshold. In addition to this, BSFC is reduced by 1% thanks to the accurate cylinder-by-cylinder calibration. Finally, aging effects or fuel variations can be implicitly compensated, keeping optimal performance thorough the engine life
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
Statistical Analysis of Knock Intensity Probability Distribution and Development of 0-D Predictive Knock Model for a SI TC Engine
No full textKnock is a non-deterministic phenomenon and its intensity is typically defined by a non-symmetrical distribution, under fixed operating conditions. A statistical approach is therefore the correct way to study knock features. Typically, intrinsically deterministic knock models need to artificially introduce Cycle-to-Cycle Variation (CCV) of relevant combustion parameters, or of cycle initial conditions, to generate different knock intensity values for a given operating condition. Their output is limited to the percentage of knocking cycles, once the user imposes an arbitrary knock intensity threshold to define the correlation between the number of knocking events and the Spark Advance (SA). In the first part of the paper, a statistical analysis of knock intensity is carried out: for different values of SA, the probability distributions of an experimental Knock Index (KI) are self-compared, and the characteristics of some percentiles are highlighted. The innovative contribution of this work is to correlate such KI probability curves with mean combustion parameters (like maximum in-cylinder pressure or combustion phase) through an analytical function. In this way, KI distributions can be predicted by a fully deterministic combustion model, ignoring CCV. In the final part of the paper such relations are implemented in a 1-D environment and tested using a combustion model, previously calibrated via Three Pressure Analysis (TPA) for knock-free operating conditions. Validation is carried out by comparing experimental and simulated KI distributions
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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