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In the present paper, two different methodologies are adopted and critically integrated to analyze the knock behavior of a last generation small size spark ignition (SI) turbocharged VVA engine. Particularly, two full load operating points are selected, exhibiting relevant differences in terms of knock proximity. On one side, a knock investigation is carried out by means of an Auto-Regressive technique (AR model) to process experimental in-cylinder pressure signals. This mathematical procedure is used to estimate the statistical distribution of knocking cycles and provide a validation of the following 1D-3D knock investigations. On the other side, an integrated numerical approach is set up, based on the synergic use of 1D and 3D simulation tools. The 1D engine model is developed within the commercial software GT-Power™. It is used to provide time-varying boundary conditions (BCs) for the 3D code, Star-CD™.

In the present paper, a recently developed centrifugal compressor model is briefly summarized. It provides a refined geometrical schematization of the device, especially of the impeller, starting from a reduced set of linear and angular dimensions. A geometrical module reproduces the 3D geometry of the impeller and furnishes the data employed to solve the 1D flow equations inside the rotating and stationary ducts constituting the complete device. The 1D compressor model allows to predict the performance maps (pressure ratio and efficiency) with good accuracy, once the tuning of a number of parameters is realized to characterize various flow losses and heat exchange. To overcome the limitations related to the model tuning, unknown parameters are selected with reference to 5 different devices employing an optimization procedure (modeFRONTIER™).

In this paper, the results of an extensive experimental analysis regarding a twin-cylinder spark-ignition turbocharged engine are employed to build up an advanced 1D model, which includes the effects of cycle-by-cycle variations (CCVs) on the combustion process. Objective of the activity is to numerically estimate the CCV impact primarily on fuel consumption and knock behavior. To this aim, the engine is experimentally characterized in terms of average performance parameters and CCVs at high and low load operation. In particular, both a spark advance and an air-to-fuel ratio (α) sweep are actuated. Acquired pressure signals are processed to estimate the rate of heat release and the main combustion events. Moreover, the Coefficient of Variation of IMEP (CoVIMEP) and of in-cylinder peak pressure (CoVpmax) are evaluated to quantify the cyclic dispersion and identify its dependency on peak pressure position.

It is widely recognized that spatial and temporal evolution of both macro- and micro- turbulent scales inside internal combustion engines affect air-fuel mixing, combustion and pollutants formation. Particularly, in spark ignition engines, tumbling macro-structure induces the generation of a proper turbulence level to sustain the development and propagation of the flame front. As known, 3D-CFD codes are able to describe the evolution of the in-cylinder flow and turbulence fields with good accuracy, although a high computational effort is required. For this reason, only a limited set of operating conditions is usually investigated. On the other hand, thanks to a lower computational burden, 1D codes can be employed to study engine performance in the whole operating domain, despite of a less detailed description of in-cylinder processes. The integration of 1D and 3D approaches appears hence a promising path to combine the advantages of both.

In this paper, an experimental and numerical analysis of combustion process and knock occurrence in a small displacement spark-ignition engine is presented. A wide experimental campaign is preliminarily carried out in order to fully characterize the engine behavior in different operating conditions. In particular, the acquisition of a large number of consecutive pressure cycle is realized to analyze the Cyclic Variability (CV) effects in terms of Indicated Mean Effective Pressure (IMEP) Coefficient of Variation (CoV). The spark advance is also changed up to incipient knocking conditions, basing on a proper definition of a knock index. The latter is estimated through the decomposition and the FFT analysis of the instantaneous pressure cycles. Contemporary, a quasi-dimensional combustion and knock model, included within a whole engine one-dimensional (1D) modeling framework, are developed. Combustion and knock models are extended to include the CV effects, too.

In this paper, a downsized twin-cylinder turbocharged spark-ignition engine is experimentally investigated at test-bench in order to verify the potential to estimate the peak pressure value and the related crank angle position, based on vibrational data acquired by an accelerometer sensor. Purpose of the activity is to provide the ECU of additional information to establish a closed-loop control of the spark timing, on a cycle-by-cycle basis. In this way, an optimal combustion phasing can be more properly accomplished in each engine operating condition. Engine behavior is firstly characterized in terms of average thermodynamic and performance parameters and cycle-by-cycle variations (CCVs) at high-load operation. In particular, both a spark advance and an A/F ratio sweep are actuated. In-cylinder pressure data are acquired by pressure sensors flush-mounted within the combustion chamber of both cylinders.

Recently, a growing interest in the development of more accurate phenomenological turbulence models is observed, since this is a key pre-requisite to properly describe the burn rate in quasi-dimensional combustion models. The latter are increasingly utilized to predict engine performance in very different operating conditions, also including unconventional valve control strategies, such as EIVC or LIVC. Therefore, a reliable phenomenological turbulence model should be able to physically relate the actuated valve strategy to turbulence level during the engine cycle, with particular care in the angular phase when the combustion takes place.

In this work, various techniques are numerically applied to a base engine - vehicle system to estimate their potential CO2 emission reduction. The reference thermal unit is a downsized turbocharged spark-ignition Variable Valve Actuation (VVA) engine, with a Compression Ratio (CR) of 10. In order to improve its fuel consumption, preserving the original full-load torque, various technologies are considered, including an increased CR, an external low-pressure cooled EGR, and a ported Water Injection (WI). The analyses are carried out by a 1D commercial software (GT-Power™), enhanced by refined user-models for the description of in-cylinder processes, namely turbulence, combustion, heat transfer and knock. The latter were validated with reference to the base engine architecture in previous activities. To minimize the Brake Specific Fuel Consumption (BSFC) all over the engine operating plane, the control parameters of the base and modified engines are calibrated based on PID controllers.

In the present work, an Auto Regressive Moving Average (ARMA) model and a Discrete Wavelet Transform (DWT) are applied on vibrational signals, acquired by an accelerometer placed on the cylinder block of a Spark Ignition (SI) engine, for knock detection purposes. To the aim of tuning such procedures, the same analysis has been carried out by using the traditional MAPO (Maximum Amplitude of Pressure Oscillations) index and an Inverse Kinetic Model (IKM), both applied on the in-cylinder pressure signals. Vibrational and in-cylinder pressure signals have been collected on a four cylinder, four stroke engine, for different engine speeds, load conditions and spark advances. The results of the two vibrational based methods are compared and in depth discussed to the aim of highlighting the pros and cons of each methodology.