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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™.

The easiest way to identify knock conditions during the operation of a SI engine is represented by the knowledge of the in-cylinder pressure. Traditional techniques like MAPO (Maximum Amplitude Pressure Oscillation) based method rely on the frequency domain processing of the pressure data. This technique may present uncertainties due to the correct specification of some model parameters, like the band-pass frequency range and the crank angle window of interest. In this paper two innovative techniques for knock detection, which make use of the in-cylinder pressure, are explained in detail, and the results are compared with those coming from the MAPO method. The first procedure is based on the use of statistical analysis by applying an Auto Regressive (AR) technique, while the second technique makes use of the Discrete Wavelet Transform (DWT). The data useful for the analysis have been acquired on a high compression ratio four cylinder, spark ignition engine.

Accurate prediction of in-vehicle powertrain bounce mode is necessary to ensure optimum responses are achieved at driver’s touch points during 4post shake or rough road shake events. But, during the early stages of vehicle development, building a detailed vehicle finite element (FE) model is not possible and often powertrain bounce modes are computed assuming the powertrain to be a stand-alone unit. Studies conducted on FE models of a large SUV with body on frame architecture showed that the stand-alone approach overestimates the powertrain bounce mode. Consequently, there is a need for a simplified version of vehicle model which can be built early on to compute powertrain modes. Previously, representing all the major components as rigid entities, simplified unibody vehicle models have been built to compute powertrain modes. But such an approach would be inaccurate here, for a vehicle with body on frame architecture due to the flexible nature of the frame (even at low frequencies).

In the recent years, the interest in heavy-duty engines fueled with Compressed Natural Gas (CNG) is increasing due to the necessity to comply with the stringent CO2 limitation imposed by national and international regulations. Indeed, the reduced number of carbon atoms of the NG molecule allows to reduce the CO2 emissions compared to a conventional fuel. The possibility to produce synthetic methane from renewable energy sources, or bio-methane from agricultural biomass and/or animal waste, contributes to support the switch from conventional fuel to CNG. To drive the engine development and reduce the time-to-market, the employment of numerical analysis is mandatory. This requires a continuous improvement of the simulation models toward real predictive analyses able to reduce the experimental R&D efforts. In this framework, 1D numerical codes are fundamental tools for system design, energy management optimization, and so on.

Idle shake is an important NVH attribute. Vehicles with good NVH characteristics are designed to perform excellent in IDLE and SHAKE conditions. Typically, tactile vibrations at idle are measured at the driver seat and steering wheel. Vibrations caused by engine excitation at idle are passed through several paths to the body structure. The dominant paths being the engine mounts and the half-shafts, either one of them or both can be a major factor influencing the perceived idle vibration in a vehicle. In the past, modeling the half-shafts accurately has been a challenge and often time has been ignored because of modeling complexity. This has led to idle CAE predictions not correlating with test data. The aim of this paper is to describe a finite element modeling method of half-shaft to predict idle vibrations levels.

In Automotive and Aerospace industries, sound package has an important role to control vehicle noise in order to improve passenger comfort and reduce environmental noise pollution. The most known approaches used to model the sound package are the Transfer Matrix Method (TMM) combined with Statistical Energy Analysis (SEA). The Transfer Matrix Method based approach is extensively used and well-validated for predicting the transmission loss and other vibro-acoustic indicators of multi-layer structures. However, to the best of our knowledge, the equivalent damping due to the multilayer has not been addressed yet in the literature, and it's a novel approach. In this paper, simplified formulations using TMM to compute the equivalent damping will be recalled, and an experimental study will be conducted to assess the add-on damping by sound package for different configurations.

In this paper, a high performance V12 spark-ignition engine is experimentally investigated at test-bench in order to fully characterize its behavior in terms of both average parameters, cycle-by-cycle variations and knock tendency, for different operating conditions. In particular, for each considered operating point, a spark advance sweep is actuated, starting from a knock-free calibration, up to intense knock operation. Sequences of 300 consecutive pressure cycles are measured for each cylinder, together with the main overall engine performance, including fuel flow, torque, and fuel consumption. Acquired data are statistically analyzed to derive the distributions of main indicated parameters, in order to find proper correlations with ensemble-averaged quantities. In particular, the Coefficient of Variation (CoV) of IMEP and of the in-cylinder peak pressure (pmax) are correlated to the average combustion phasing and duration (MFB50 and Δθb), with a good coefficient of determination.

Automobiles have a high degree of mechanical and electrical complexity. However, product complexity has the accompanying effect of requiring high levels of design and process oversight. The net result is a product creation process which is prone to creating failures. These failures typically have their origin in an overall lack of complete understanding of the system in terms of materials, geometries and energy flows. Despite all of the engineering intentions, failures are inevitable, common, and must be dealt with accordingly. In the worst case, if a failure manifests itself into an observable failure the customer may have a negative experience. Therefore, it is imperative that design engineers, suppliers along with reliability professionals be able to assess the design risk. One approach to assess risk is the use of degradation analysis. Degradation analysis often provides more information than failure time data for assessing reliability and predicting the remnant life of a system.

Multiaxial loading on mechanical products is very common in the automotive industry, and how to design and analyze these products for durability becomes an important, urgent task for the engineering community. Due to the complex nature of the fatigue damage mechanism for a product under multiaxial state of stresses/strains which are dependent upon the modes of loading, materials, and life, modeling this behavior has always been a challenging task for fatigue scientists and engineers around the world. As a result, many multiaxial fatigue theories have been developed. Among all the theories, an existing equivalent stress theory is considered for use for the automotive components that are typically designed to prevent Case B cracks in the high cycle fatigue regime.

Dimensional Engineering concentrates effort in the early design phases to meet the dimensional build objectives in automotive production. Design optimization tools include tolerance stack up, datum optimization, datum coordination, dimensional control plans, and measurement plans. These tools are typically based on the assumption that parts are rigid and tooling dimensions are perfect. These assumptions are not necessarily true in automotive assemblies of compliant sheet metal parts on high volume assembly lines. To address this issue, Finite Element Analysis (FEA) has been increasingly used to predict the behavior of imperfect and deformable parts in non-nominal tooling. This paper demonstrates an application of this approach. The complete analysis is divided into three phases. The first phase is a nominal design gravity analysis to validate the nominal design and tooling.

This paper describes an experimental study on the performance of self-piercing riveted (SPR) joints and adhesively bonded SPR joints connecting steel and aluminum components under both quasi-static and cyclic loading. The joint configurations cover a wide range of material gauges, types and grades. Two and three thickness joints, with and without adhesive are also part of this study. Load versus deflection behavior, load carrying capacity, fatigue life and the failure modes for each type of joint are discussed. This study focuses on the influence of dissimilar material and adhesives to the joint performance.

The automotive door structure experience various static and dynamic loading conditions while going through an opening and closing operation. A typical swing door is attached to the body with two hinges and a check strap. These mechanisms carry the loads while the door is opened. Similarly, while closing the door, the latch/striker mechanism along with the seal around the periphery of the door react all loads. Typically, computer aided engineering (CAE) simulations are performed considering a nominal manufacturing (or build) tolerance condition, that results in one loading scenario. But while assembling the door with the body, the build variations in door mechanisms mentioned above can result in different loading scenarios and it should be accounted for design evaluation. This paper discusses various build tolerances and its effect on door durability performances to achieve a robust door design.

This paper describes a reliable CAE methodology to model the linear vibratory behavior of windshields. The windshield is an important component in vehicle NVH performance. It plays an integral role in interior cabin noise. The windshield acts as a large panel typically oriented near vertical at the front of vehicle’s acoustic cavity, hence modeling it accurately is essential to have a reliable prediction of cabin interior noise. The challenge to model the windshield accurately rises from the structural composition of different types of windshields. For automotive applications, windshields come in several structural compositions today. In this paper, we will discuss two types of windshield glass used primarily by automotive manufacturers. First type is the typical laminated glass with polyvinyl butyral (PVB) layer and second type is the acoustic glass with PVB and vinyl layers. Acoustic glass improves acoustic characteristics of the glass in a frequency range of ~ 1200 Hz to ~4000 Hz.

In-cylinder ion sensing is a subject of interest due to its application in spark-ignited (SI) engines for feedback control and diagnostics including: combustion knock detection, rate and phasing of combustion, and mis-fire On Board Diagnostics (OBD). Further advancement and application is likely to continue as the result of the availability of ignition coils with integrated ion sensing circuitry making ion sensing more versatile and cost effective. In SI engines, combustion knock is controlled through closed loop feedback from sensor metrics to maintain knock near the borderline, below engine damage and NVH thresholds. Combustion knock is one of the critical applications for ion sensing in SI engines and improvement in knock detection offers the potential for increased thermal efficiency. This work analyzes and characterizes the ionization signal in reference to the cylinder pressure signal under knocking and non-knocking conditions.

Warranty forecasting of repairable systems is very important for manufacturers of mass produced systems. It is desired to predict the Expected Number of Failures (ENF) after a censoring time using collected failure data before the censoring time. Moreover, systems may be produced with a defective component resulting in extensive warranty costs even after the defective component is detected and replaced with a new design. In this paper, we present a forecasting method to predict the ENF of a repairable system using observed data which is used to calibrate a Generalized Renewal Processes (GRP) model. Manufacturing of products may exhibit different production patterns with different failure statistics through time. For example, vehicles produced in different months may have different failure intensities because of supply chain differences or different skills of production workers, for example.

The latest trend in transmission hydraulic controls development ise body integrated direct acting control solenoid, ted by multiple automotive OEMs. The advantages of integrated direct acting control solenoids are key enablers for OEMs to meet more and more stringent fuel economy requirement and competitive environment. In the meantime, there are unique challenges in both designing and manufacturing of such solenoids, due to the fact the solenoid armature can only push the spool valve with limited force and limited stroke. Through analytical methods, this paper explains design guidelines to overcome the challenges and quantifies the impact of design decision to critical functional objectives. Multiple valve design configurations, including both normally low and normally high functionality, are covered in the analysis. Unique manufacturing process concerns are also addressed.

An experimental campaign was carried out to evaluate the influence of CNG and gasoline on the exhaust emissions and fuel consumption of a bi-fuel passenger car over on-road tests performed in the city of Naples. The chosen route is very traffic congested during the daytime of experimental measurements. An on-board analyzer was used to measure CO, CO2, NOx tailpipe concentrations and the exhaust flow rate. Throughout a carbon balance on the exhaust pollutants, the fuel consumption was estimated. The exact spatial position was acquired by a GPS which allowed to calculate vehicle speed and the traffic condition was monitored by a video camera. Whole trip realized by the vehicle was subdivided in succession of kinematic sequences and the vehicle emissions and fuel consumption were analyzed and presented as value on each kinematic sequence. Moreover, throughout a multivariate statistical analysis of sequences, the driving cycles characterizing the use of vehicle were identified.

This paper describes a study on identifying a suitable thickness for finite element modeling a “deformable washer” to simulate bolted joints for vehicle level durability analysis based on experimental results. First, a test matrix table is introduced, which is based on representative vehicle structures for different bolt/nut sizes, bolt grades, sheet gages, and sheet materials etc. Then coupon tests, both static and fatigue, are illustrated. Next, the corresponding finite element model with different thickness of “deformable washers” and results are presented. Following that, the optimal “deformable washer” thickness is recommended based on statistical parameters (mean and standard deviation) of the relative differences between finite element analysis results and physical test results. Lastly, a case study is demonstrated for the proposed strategy.

In this study, a unique multi-camera three-dimensional digital image correlation (3D-DIC) system was designed and applied to an engine dynamometer cell to measure the displacement and strain of the exhaust manifold while an engine was running in a durability test. In the engine dynamometer cell, the ambient temperature varies from 25°C to 80°C~100°C cyclically and the exhaust manifold experiences high temperatures up to 900°C with high frequency vibrations. In order to obtain reliable data under such conditions, two 3D-DIC systems were designed and set up in the engine dynamometer. One is a high-speed 3D-DIC system, consisting of cameras with a sampling rate of 1250 frames per second. It was used to measure the local displacement of the bolted joint in the exhaust manifold. The high-speed measurement system is able to record the behavior of the bolt during the thermal cycles.

Sensory jury testing was utilized to characterize vibration levels perceived by the operator, with respect to levels measured using instrumentation, in order to develop a tool for the evaluation of vibration at the operator interfaces. Details of the jury testing and jury data processing method are highlighted as well as the refinement of vibration characterization for a specific application. The vibration at user interface locations of both snowmobiles and ATVs was measured along with subjective feedback from a panel of jurists. Statistical analysis was performed on the jury data to provide both a qualitative and quantitative number to represent the opinion of the jury. Correlations were developed between the measured levels of vibration and the opinions of the jury. Finally, a set of correlation functions suitable for design predictions was developed.