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Metal cutting/machining is a widely used manufacturing process for producing high-precision parts at a low cost and with high throughput. In the automotive industry, engine components such as cylinder heads or engine blocks are all manufactured using such processes. Despite its cost benefits, manufacturers often face the problem of machining chips and cutting oil residue remaining on the finished surface or falling into the internal cavities after machining operations, and these wastes can be very difficult to clean. While part cleaning/washing equipment suppliers often claim that their washers have superior performance, determining the washing efficiency is challenging without means to visualize the water flow. In this paper, a virtual engineering methodology using particle-based CFD is developed to address the issue of metal chip cleanliness resulting from engine component machining operations. This methodology comprises two simulation methods.

Onboard, embedded cellular modems are enabling a range of new connectivity features in vehicles and rich, real-time data set transmissions from a vehicle’s internal network up to a cloud database are of particular interest. However, there is far too much information in a vehicle’s electrical state for every vehicle to upload all of its data in real-time. We are thus concerned with which data is uploaded and how that data is processed, structured, stored, and reported. Existing onboard data processing algorithms (e.g. for DTC detection) are hardcoded into critical vehicle firmware, limited in scope and cannot be reconfigured on the fly. Since many use cases for vehicle data analytics are still unknown, we require a system which is capable of efficiently processing and reporting vehicle deep data in real-time, such that data reporting can be switched on/off during normal vehicle operation, and that processing/reporting can be reconfigured remotely.

Vehicle idle quality has become an increasing quality concern for automobile manufacturers because of its impact on customer satisfaction. There are two factors that critical to vehicle idle quality, the engine excitation force and vehicle sensitivity (transfer function). To better understand the contribution to the idle quality from these two factors and carry out well-planned improvement measures, a quick and easy way to measure vehicle sensitivity at idle conditions is desired. There are several different ways to get vehicle sensitivity at idle conditions. A typical way is to use CAE. One of the biggest advantages using CAE is that it can separate vehicle sensitivities to different forcing inputs. As always, the CAE results need to be validated before being fully utilized. Another way to get vehicle sensitivity is through impact test using impact hammer or shaker. However this method doesn't include the mount preload due to engine firing torque [3, 4, & 5].

Accurate prediction of engine combustion characteristics, especially burn rates, can eliminate a number of hardware iterations, thus resulting in a significant reduction in design and developmental time and cost. An analytical methodology has been developed which allows the determination of part-load MBT spark timing to within 2 crank-angle degrees. The design methodology employs the in-house-developed steady-state quasi-dimensional engine simulation model (GESIM), coupled with full-field measurement of the in-cylinder fluid motion at bottom dead center (BDC) in the computer-controlled water analog system (AquaDyne). The in-cylinder flow-field measurements are obtained using 3-D Particle Tracking Velocimetry (3-D PTV), also developed in-house. In this methodology, the in-cylinder flow measurement data are used to calibrate both the tumble and swirl models in GESIM.

Advancing intake valve timing shortly after engine crank and run-up can potentially reduce vehicle cold start hydrocarbon (HC) emissions in port fuel injected (PFI) engines equipped with intake variable cam timing (iVCT). Due to the cold metal temperatures, there can be significant accumulation of liquid fuel in the intake system and in the cylinder. This accumulation of liquid fuel provides potential sources for unburned hydrocarbons (HCs). Since the entire vehicle exhaust system is cold, the catalyst will not mitigate the release of unburned HCs. By advancing the intake valve timing and increasing valve overlap, liquid fuel vaporization in the intake system is enhanced thereby increasing the amount of burnable fuel in the cylinder. This increase in burnable HCs must be countered by a reduction in injector-delivered fuel via a compensator that reacts to cam movement.

Thermal fatigue presents a new challenge in cast aluminum engine design. Accurate thermomechanical stress analysis and reliable failure criterion are the keys to a successful life prediction. It is shown that the material stress and strain behavior of cast aluminum is strongly temperature and strain rate sensitive. A unified viscoplasticity constitutive relation is thus proposed to simultaneously describe the plasticity and creep of cast aluminum components deforming at high temperatures. A fatigue failure criterion based on a damage accumulation model is introduced. Damages due to mechanical fatigue, environmental impact and creep are accounted for. The material stress and strain model and thermal fatigue model are shown to be effective in accurately capturing features of thermal fatigue by simulating a component thermal fatigue test using 3D FEA with ABAQUS and comparing the results with measured data.

Acoustic standing waves are excited in internal combustion chambers by both normal combustion and autoignition. The energy in these acoustic modes can be transmitted through the engine block and radiated as high-frequency engine noise. Using finite-element models of two different (four-valve and two-valve) production engine combustion chambers, the mode shapes and relative frequencies of the in-cylinder volume acoustic modes are calculated as a function of crank angle. The model is validated by comparison to spectrograms of experimental time-sampled waveforms (from flush-mounted cylinder pressure sensors and accelerometers) from these two typical production spark-ignited engines.

General Motors Powertrain Division has developed a new V-8 engine for Cadillac vehicles in the 1990s. The Northstar engine incorporates the use of aluminum for both the cylinder block and head and other lightweight materials throughout. The valve train incorporates direct acting hydraulic lifters actuating the four valves per cylinder through dual overhead camshafts. The primary focus of the project has been to produce an engine of unquestioned reliability and exceptional value which is pleasing to the customer throughout the range of loads and speeds. The engine was designed with a light weight valve train, low valve overlap and moderate lift, resulting in a very pleasing combination of smooth idle and a broad range of power. The use of analytical methods early in the design stage enabled systems to be engineered to optimize reliability, pleaseability and value by reducing frictional losses, noise, and potential leak paths, while increasing efficiency and ease of manufacture.

A vehicle fleet test has been conducted to determine if octane advantages due to selected cooling system variables persist with stabilized deposits. The variables tested were reduced coolant temperatures, a direct substitution of aluminum for the iron cylinder head and an aluminum head with Unique Cooling. Octane requirements, octane requirement increase (ORI), emissions and fuel economy results are presented and discussed. Engine tests to determine the sensitivity of octane to independently controlled engine temperatures confirmed the primary dependence upon coolant temperature. Additional tests identified some of the variables which cause octane differences among the cylinders of one engine and between engine families.

Due to the challenges in quantifying hand loads in manufacturing environments it is often assumed that the load is evenly distributed between the hands, even when handling parts with non-uniform mass distribution. This study estimated hand loads for six female subjects, when handling a custom part in 8 different configurations (2 weights, 4 CofM locations). The calculated hand loads varied from 20 to 50% of the weight being handled. The magnitude of asymmetrical hand loading depended on both the part orientation and the location of the CoM. Based on this study the knowledge of part weight, CofM location and hand positioning will allow the users of digital human models to perform more realistic and reliable task analysis assessments as the force distributions will be more representative of the actual loading rather than simply assuming the load is evenly distributed between the hands.

An experimental and analytical study was conducted to investigate the effects of load control with port throttling on stability and fuel consumption at idle. With port throttling, the pressure in the intake port increases during the valve-closed period due to flow past the throttle. If the pressure in the port recovers to ambient before the valve overlap period, back flow into the intake system from the cylinder is eliminated. This allows increased valve overlap to be used without increasing the residual mass fraction in the cylinder. Results showed that, with high valve overlap and port throttling, idle stability and fuel consumption can be maintained at values associated with low overlap in a conventionally throttled engine. However, implementation of this concept in production is regarded to require precision-fit and balanced port throttles, an external vacuum pump for vacuum systems support, and revision of the PCV system.

In the past twenty years, the explicit finite element method has been successfully employed for crash simulation. At present, crashworthiness analysis is still basically a calibration based engineering practice, but not a fully predictive process. The increasing expectations and requirements on CAE are even more challenging. To develop a predictive and reliable CAE tool, it is important to investigate the root causes that affect the numerical accuracy and the availability of the analytical method. Some of the challenging issues are discussed here from both theoretical and engineering aspects, such as convergence of explicit finite element method, locking-free shell element, analysis of material rupture, and modeling of spot weld.

A simple and accurate analytical expression relating the expected process (long term) and sampling (short-term) product variability is developed using a variational mathematical principle. Of the several complex functional forms discovered, simplicity and ease of use are used to select an expression providing the most reliable estimation for and convenient expression of Z score (σ level) as a function of defects per opportunity (DPO) or per million opportunities (DPMO). In the absence of scientific calculators or computers, this expression allows engineers to accurately estimate long term process variability to within 0.01 of its true value without resulting to (laborious) tables or a computer. Also, a high precision approximation is provided for cases when DPO is less than 1% which estimates Z-score to within 0.003 of the actual value (at 6σ).

This paper describes a joint SAE automotive and aerospace Recommended Practice SAE J3168 now in development to standardize a process for Reliability Physics Analysis. This is a science-based approach to implement Physics-of-Failure research in conducting durability simulations in a Computer Aided Engineering Environment. It is used to calculate failure mechanism susceptibilities and estimate the likelihood of failure and the expected durability life of Electrical, Electronic and Electromechanical components and equipment, due to stresses such as mechanical shock, vibration, temperature cycling, etc. Reliability Physics Analysis is based on the material science principle of stress driven damage accumulation in materials. The process enables the identification of potential failure risks early in the design phase so that such risks can be designed out in order to efficiently design high reliable and robustness into electronic products.

Lane change events can be a source of traffic accidents; drivers can make improper lane changes for many reasons. In this paper we present a comprehensive study of a passive method of predicting lane changes based on three physiological signals: electrocardiogram (ECG), respiration signals, and galvanic skin response (GSR). Specifically, we discuss methods for feature selection, feature reduction, classification, and post processing techniques for reliable lane change prediction. Data were recorded for on-road driving for several drivers. Results show that the average accuracy of a single driver test was approx. 70%. It was greater than the accuracy for each cross-driver test. Also, prediction for younger drivers was better.

To address the conflicting goals of minimal piston friction and minimal piston noise, a dynamic power cylinder model was developed to predict piston motion and side loads within the cylinder. This correlated model was the basis of a comprehensive analytical design of experiments (DOE) where both piston noise and piston friction were monitored. The results of the DOE were used to generate metamodels for piston friction and for piston noise. To insure design robustness, variability was introduced into the surrogate models via First Order Reliability Method (FORM). A Pareto curve using 99% probability was constructed and a piston robust to both noise and friction was selected.

Residual stress of an air quenched engine cylinder head is studied in the present paper. The numerical simulation is accomplished by sequential thermal and stress analyses. Thermal history of the cylinder head is simulated by using the commercial Computation Fluid Mechanics (CFD) code FLUENT. The only parameter adjustable in the analysis is the incoming air speed. Predicted temperatures at two locations are comparable with available thermocouple data. Stress analysis is performed using ABAQUS with a Ford proprietary material constitutive relation, which is based on coupon tests on the as-solution treated material. Both temperature and strain rate impacts on material behavior of the as-solution treated material are considered in the stress and strain model. Predicted residual strain is shown to be consistent with measured data, which is obtained by using strain gauging and sectioning method.

Reliability-based design optimization (RBDO) has been widely used to obtain a reliable design via an existing CAE model considering the variations of input variables. However, most RBDO approaches do not consider the CAE model bias and uncertainty, which may largely affect the reliability assessment of the final design and result in risky design decisions. In this paper, the Gaussian Process Modeling (GPM) approach is applied to statistically correct the model discrepancy which is represented as a bias function, and to quantify model uncertainty based on collected data from either real tests or high-fidelity CAE simulations. After the corrected model is validated by extra sets of test data, it is integrated into the RBDO formulation to obtain a reliable solution that meets the overall reliability targets while considering both model and parameter uncertainties.

As automotive competition is becoming more and more global, automotive products (vehicles or systems or components) are often developed in one market and made and/or used in other markets. The operating conditions are often different from one market to another market. If the market unique operating conditions are not considered in its development and manufacture process, the product may not fully perform its intended function over useful life period, and may experience fewer failure modes in one market but more or different failure modes in other markets. This paper presents a Reliability Engineering approach, based on “Failure Mode Avoidance”, to the product development for global automotive markets. The approach includes three phases: Discover operating conditions (noise factors) and their potential failure modes Develop countermeasures to deal with the noise factors, and Verify the effectiveness of the countermeasures using Reliability Demonstration Matrix.

Typically, “Reliability and Maintainability (R&M)” is perceived as a tool for products alone. Putting emphasis on reliability only at the cost of maintainability is another archetype. Inclusion of both reliability and maintainability (R&M) in all the phases of the machinery and equipment (M&E) life cycle is required in order to be world competitive in manufacturing. R&M is mainly a design function and it should be a part of any design review. Inclusion of the R&M concept early in the life cycle of M&E is key to cost effective and competitive manufacturing. Neither responsive manufacturing nor preventive maintenance can raise it above the level of inherent R&M.