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A full calibration exercise of a diesel engine air path can take months to complete (depending on the number of variables). Model-based calibration approach can speed up the calibration process significantly. This paper discusses the overall calibration process of the air-path of the Cat® C7.1 engine using statistical machine learning tool. The standard Cat® C7.1 engine's twin-stage turbocharger was replaced by a VTG (Variable Turbine Geometry) as part of an evaluation of a novel air system. The changes made to the air-path system required a recalculation of the air path's boost set point and desired EGR set point maps. Statistical learning processes provided a firm basis to model and optimize the air path set point maps and allowed a healthy balance to be struck between the resources required for the exercise and the resulting data quality.

The automotive industry is dramatically changing. Many automotive Original Equipment Manufacturers (OEMs) proposed new prototype models or concept vehicles to promote a green vehicle image. Non-traditional players bring many latest technologies in the Information Technology (IT) industry to the automotive industry. Typical vehicle’s characteristics became wider compared to those of vehicles a decade ago, and they include not only a driving range, mileage per gallon and acceleration rating, but also many features adopted in the IT industry, such as usability, connectivity, vehicle software upgrade capability and backward compatibility. Consumers expect the latest technology features in vehicles as they enjoy in using digital applications in laptops and mobile phones. These features create a huge challenge for a design of a new vehicle, especially for a human-machine-interface (HMI) system.

Low temperature combustion (LTC) in diesel engines offers attractive benefits through simultaneous reduction of nitrogen oxides and soot. However, it is known that the in-cylinder conditions typical of LTC operation tend to produce high emissions of unburned hydrocarbons (UHC) and carbon monoxide (CO), reducing combustion efficiency. The present study develops from the hypothesis that this characteristic poor combustion efficiency is due to in-cylinder mixture preparation strategies that are non-optimally matched to the requirements of the LTC combustion mode. In this work, the effects of three key fuel path parameters - injection fuel quantity ratio, dwell and injection timing - on CO and HC emissions were examined using a Central Composite Design (CCD) Design of Experiments (DOE) method.

In this paper, residual stress distributions in rectangular bars due to rolling or burnishing at very high rolling or burnishing loads are investigated by roll burnishing experiments and three-dimensional finite element analyses using ABAQUS. First, roll burnishing experiments on rectangular bars at two roller burnishing loads are presented. The results indicate the higher burnishing load induces lower residual stresses and the higher burnishing load does not improve fatigue lives. Next, in the corresponding finite element analyses, the roller is modeled as rigid and the roller rolls on the flat surface of the bar with a low coefficient of friction. The bar material is modeled as an elastic-plastic strain hardening material with a nonlinear kinematic hardening rule for loading and unloading.

With the electrification of the automotive industry, electric motors have emerged as pivotal components. A profound understanding of their vibrational behaviour stands as a cornerstone for guaranteeing not only the optimal performance and reliability of vehicles in terms of noise, vibration, and harshness (NVH), but also the overall driving experience. The use of conventional finite element analysis (FEA) techniques for identification of the natural frequencies characteristics of electric motors often imposes significant computational loads, particularly when accurate material and geometrical properties and wider frequency ranges are considered. On the other hand, traditional reduced order vibroacoustic methodologies utilising simplified 2D representations, introduce several assumptions regarding boundary conditions and properties, leading to sacrifices in the accuracy of the results.

The replacement of the ICE engine with an electric motor has led to a significant reduction in vibration and noise. The characteristics of the electric motor as part of the powertrain still need consideration from an NVH perspective, as there are still two highly tonal components generating noise to the cabin, albeit at higher frequencies. The radial electromagnetic force causes a structural vibration on the casing which changes with motor speed and can be used to indicate vehicle speed. The current excitation causes a primarily tangential force on the poles of the motor at a specific frequency, but both are narrow band and can cause annoyance. The traditional approach to predicting the sound radiation of electric motors is usually based on finite element analysis (FEA). While this method has the capability to estimate the time response, it is computationally too demanding and does not allow for early investigations at systems level.

The primary function of automotive windscreen wipers is to remove excess water and debris to secure a clear view for the driver. Their successful operation is imperative to vehicle occupants’ safety. To avoid reliance on experimental testing there is a need to develop physics-based models that can quantify the effects of design-based decisions on automotive wipers. This work presents a suite of evaluative tools that can provide quantitative data on the effects of design decisions. We analyse the complex non-linear contact interaction between the wiper blade and the automotive screen using finite element analysis, assessing the impact of blade geometry on the contact distribution. The influence of the evolution of normal applied load by the wiper arm is also investigated as to how it impacts the contact distribution evolution. The dynamics of the blade are subsequently analysed using a multiple connected mass spring damper system.

Lightly damped non-linear systems such as vehicular drivelines undergo a plethora of Noise, Vibration and Harshness (NVH) problems. The clonk phenomenon is one concern which occurs as the result of impulsive torque input in the form of sudden clutch actuation or throttle tip-in and back-out. The resulting impact of meshing gear pairs propagate structural waves down the driveline. With lightly damped thin-walled tubes having high modal density, elasto-acoustic coupling occurs. High frequency noise emission is of metallic nature and quite disconcerting to vehicle occupants as well as passers-by. It is perceived as structural failure and/or poor-quality build. Therefore, the occurrence of the phenomenon is a concern to vehicle manufacturers and progressively constitutes a warranty concern. This paper investigates the clonk phenomenon through use of a long-wheel base rear drive light truck test rig.

Sensor selection for the control of modern powertrains is a recognised technical challenge. The key question is which set of sensors is best suited for an effective control strategy? This paper addresses the question through probabilistic modelling and Bayesian analysis. By quantifying uncertainties in the model, the propagation of sensor information throughout the model can be observed. The specific example is an abstract model of the slip behaviour of Selective Catalytic Reduction (SCR) DeNOx aftertreatment systems. Due to the ambiguity of the sensor reading, linearization-based approaches including the Extended Kalman Filter, or the Unscented Kalman Filter are not successful in resolving this problem. The stochastic literature suggests approximating these nonlinear distributions using methods such as Markov Chain Monte Carlo (MCMC), which is able in principle to resolve bimodal or multimodal results.

A typical cab used on agriculture machines is made up of a metal frame structure with large enclosing panels of glass, plastic, and metal. Acoustic treatments such as coatings, textiles and foams are used within the cab for aesthetics but also to mediate undesired noise. To develop effective designs for the cab to combat noise, accurate tools for measurement, and predictive methods for sound transmission loss are needed. This paper focuses on Sound Transmission Loss (STL) of the rear upper panel of a cab used in agriculture machines. Results from CAE based tools such as Statistical Energy Analysis (SEA), Finite Element Analysis (FEA) and Hybrid FE-SEA methods are compared to measurements. The panel studied included features such as curvature, deep drawn beads with a glass window and a damping coating. The simulation results are refined by incorporating methods for accurate modeling of ribs stiffness, curvature effect and radiation efficiency by synthetic modal approach.

Pass-by/exterior noise of earth moving machines (EMM) and forestry machines is becoming a focus at early product development stages. ISO 6395 (2) or EC/2000/14 (1) standards defines exterior noise test procedure for EMM. However, these standards do not provide insights for diagnosing any noise issues which may arise. The analysis challenges are posed by the moving machine and acoustic sources with respect to the stationary hemisphere target microphone on the ground and changing operating condition of sources as function of time. There is need to develop a seamless methodology to identify acoustic sources, quantify respective source strengths and rank partial contributions from each source to the total target microphone response in order to overcome the aforementioned challenges.

Structure-borne inputs to hybrid FEA/SEA models could have significant effects on the model prediction accuracy. The purpose of this work was to obtain the structure-borne noise (SBN) inputs using a simplified transfer path analysis (TPA) and identify the significance of the structure-borne and airborne contributions to the spectator sound power of an engine with enclosure for future modeling references. Force inputs to the enclosure from the engine were obtained and used as inputs to a hybrid engine enclosure model for sound prediction.

This paper presents the findings from a numerical study of a gasoline direct injection engine flow using the Large Eddy Simulation (LES) modelling technique. The study is carried out over 30 successive engine cycles. The study illustrates how the more simple but robust Smagorinsky LES sub-grid scale turbulence model can be applied to a complex engine geometry with realistic engineering mesh size and computational expense whilst still meeting the filter width requirements to resolve the majority of large scale turbulent structures. Detailed description is provided here for the computational setup, including the initialisation strategy. The mesh is evaluated using a turbulence resolution parameter and shows the solution to generally resolve upwards of 80% of the turbulence kinetic energy.

Caterpillar uses heat treatment to enhance the properties of a significant number of parts. Traditional heat treat process optimization is both time consuming and expensive when done by empirical methods. This paper describes a computer simulation of the heat treatment process, developed by Caterpillar, based upon finite element analysis. This approach combines thermal, microstructural, and stress analysis to accurately model material transformation during quenching. Examples are presented to illustrate the program.

A nonlinear, three-dimensional finite element analysis of the cylinder head gasket joint has been developed to allow accurate prediction of global and local joint behavior during engine operation. Nonlinear material properties and load cases that simulate full cycle engine operation are the analysis foundation. The three-dimensional, nonlinear, full-cycle simulation accurately predicts cylinder head gasket joint response to assembly, thermal, and cylinder pressure loading. Predictions correlate well with measured engine test data. Analysis results include local pressure distribution and global load splits. Insight into joint loading and an improved understanding of overall joint behavior provide the basis for informed design and development decisions.

Operator noise is an important aspect for noise and vibration of off-highway vehicles and a quieter cab is critical for the operator comfort. The noise level inside the cab is influenced by structural and acoustic transfer paths. In this paper, we used hybrid FE-SEA approach to consider both structural and acoustic transfer path as FEM and SEA methods individually face limitations in high and low frequencies respectively. A hybrid FE-SEA cab model was built to predict the structural and acoustic transfer functions. The analysis model was built with the systematic approach validated at each step with the laboratory test results. For the structural transfer function, structural excitations were applied at four cab mount locations and accelerations at various locations on the cab were validated. For the acoustic transfer function, the cab was excited with the volume velocity source inside the cab and sound power output of various panels were calculated and compared to the test results.

Analyzing the combustion characteristics, engine performance, and emissions pathways of the internal combustion (IC) engine requires management of complex and an increasing quantity of data. With this in mind, effective management to deliver increased knowledge from these data over shorter timescales is a priority for development engineers. This paper describes how this can be achieved by combining conventional engine research methods with the latest developments in process informatics and statistical analysis. Process informatics enables engineers to combine data, instrumental and application models to carry out automated model development including optimization and validation against large data repositories of experimental data.

Development of Terrain-Vehicle Systems Analysis involving statistically variable ground, has necessitated the development of field instrumentation for mass measurement of soil parameter input. To this end, the idea originally conceived and tested at U.S. Army's Land Locomotion Laboratory in Detroit, was revived and adapted to modern requirements. The Wheeled Automated Bevameter (WAB) was presented as a better vehicle analog for measuring soil parameters than the conventional plate-shearing instrument hitherto used. It yields itself to mass production of terrain input, without which further progress in Terramechanics, based on statistical changes of the environment may be impossible.

The efforts of the ISO “Test Variability Task Force” have been aimed at improving the understanding and at reducing brake dynamometer test variability during performance testing. In addition, dynamometer test results have been compared and correlated to vehicle testing. Even though there is already a vast amount of anecdotal evidence confirming the fact that different procedures generate different friction coefficients on the same brake corner, the availability of supporting data to the industry has been elusive up to this point. To overcome this issue, this paper focuses on assessing friction levels, friction coefficient sensitivity, and repeatability under ECE, GB, ISO, JASO, and SAE laboratory friction evaluation tests.

A qualitative FMEA study of Polymer Electrolyte Fuel Cell (PEFC) technology is established and presented in the current work through a literature survey of mechanisms that govern performance degradation and failure. The literature findings are translated into Fault Tree (FT) diagrams that depict how basic events can develop into performance degradation or failure in the context of the following top events; (1) activation losses; (2) mass transportation losses; (3) Ohmic losses; (4) efficiency losses and (5) catastrophic cell failure. Twenty-two identified faults and forty-seven frequent causes are translated into fifty-two basic events and a system of FTs with twenty-one reoccurring dominant mechanisms. The four most dominant mechanisms discussed that currently curtail sustained fuel cell performance relate to membrane durability, liquid water formation, flow-field design, and manufacturing practices.