Development of a Robust AIS Parametric Model for V8 Engines Using Design for Six Sigma Approach

<div class="section abstract"><div class="htmlview paragraph">Noise pollution is a significant concern for global automotive industries which propels engineers to evolve new methods to meet passenger comfort and regulatory requirements. The primary purpose of an intake manifold in an automotive vehicle is to allow the passage of clean air for combustion and reduce the noise generated due to engine pulsations. This work proposes a Design for Six Sigma (DFSS) approach to optimize the intake manifold for better acoustic performance without compromising performance for a 3.6 L four-stroke engine for a Plug-in Hybrid electric vehicle (PHEV). Conventionally, intake manifold design has been an iterative process. It involves repetitive testing to arrive at an optimum design. The intake manifold must be designed for better acoustics and engine performance, complicating the design process even more. The DFSS approach has input, output, control, and noise factors. Air-borne noise coming from the engine at different speeds is the input, and the throttle body noise is the output for the analysis. All the design parameters affecting the output are considered the control factors, and the two 3.6 L four-stroke engines with different valve timing are considered the noise factor since the design engineer does not control it. The experimental simulation setup will be based on the different levels of control factors. The simulation work for the throttle body noise was carried out using the GT-POWER software. The throttle body noise data (Sound pressure levels Versus Engine speed) was collected from 800 to 6400 rpm for rumble analysis. The design combination which minimizes the rumble was used as the final design.</div></div>

<div class="section abstract"><div class="htmlview paragraph">Emission compliance at the production level has been a challenge for vehicle manufacturers. Diesel oxidation catalyst (DOC) plays a very important role in controlling the emissions for the diesel vehicles. Vehicle manufacturers tend to ‘over design’ the diesel oxidation catalyst to ‘absorb’ the production variations which seems an easier and faster solution. However this approach increases the DOC cost phenomenally which impacts the overall vehicle cost.</div><div class="htmlview paragraph">The main objective of this paper is to address the high variation in CO tail pipe emissions which were observed on a diesel passenger car during development. This variation was posing a challenge in consistently meeting the internal product requirement/specification. This paper outlines a step by step process by following a DFSS (Design for Six Sigma) methodology in selecting an optimized DOC design in terms of tailpipe emission, engine performance and system cost for a given level of engine-out CO emission variation in a cheaper and faster way by combining concepts of virtual emission simulation, Taguchi design of experiments and multi parameter optimization.</div><div class="htmlview paragraph">In order to quantify the emission variation, engine-out & tail pipe emissions were measured on various development vehicles with the same level of hardware and calibration. Further, a parameter diagram (P-diagram) which identified all the control factors, input signal, and noise and error states was developed. The optimal values of control parameters were arrived by rationalizing the DOC design against DOC system cost and other performance criteria using multi parameter optimization methods.</div><div class="htmlview paragraph">The optimized DOC design had a 14% reduction in CO emissions and a ∼14% improvement in robustness based on signal to noise ratio when compared with the baseline design that was being used during development. Monte Carlo simulations predicted an 87% reduction in out-of-specification emissions for an additional 23% increase in cost when compared to baseline.</div></div>

In this paper, a robust optimization method based on design for six sigma (DFSS) is combined to the optimization of a surface mounted permanent synchronous machine (PMSM) by using multilevel genetic algorithm (MLGA). First, MLGA and DFSS are introduced in the robust optimization. Second, by taking into account the tolerances of the motor products, important input parameters could be varied with six sigma distribution and Monte Carlo simulation (MCS) method is used to reduce the calculation cost. Third, to verify the new algorithm, the presented algorithm is applied to the optimization of a PMSM. The results compared with those of traditional GA and MLGA and the discussion of the robust optimization combined with MLGA are presented.

Design for six sigma (DFSS) is a structured approach for designing new products, processes and/or services or redesigning the existing ones. It builds quality into the product during the development and ensures the customer expectations are understood, met, or exceed. In DFSS, variation is aimed to be minimized by applying the techniques of the six sigma approach. Some of these techniques are process control and process capability analysis. Vagueness and impreciseness in these analyses such as the statistical distribution of the considered process can be handled by the fuzzy set theory. Recently, ordinary fuzzy sets have been extended to several new types of fuzzy sets such as Pythagorean fuzzy sets, spherical fuzzy sets, picture fuzzy sets, and intuitionistic fuzzy sets. In this paper, we propose a new extension of intuitionistic fuzzy sets, which is called Penthagorean fuzzy sets and employ it in the process capability analysis of a production process. Penthagorean fuzzy process capability indices are developed and applied to an Autonomous Underwater Vehicle (AUV) design example.

<div class="htmlview paragraph">The concept of design for six sigma (DFSS) offers a framework to design a product and process right the first time. In general, Taguchi's robust design method has been widely adapted in design optimization, which is a critical phase in any DFSS projects. The objective of the paper is to develop an advanced strategy in selecting an optimized product design and manufacturing process that should be insensitive to various multivariate variation patterns of the multi-stage manufacturing system. A Monte Carlo variation simulation based method is presented that integrates Mohalanobis Distance (MD) method, a discriminant analysis technique, to analyze the manufacturing variation patterns detected by using the multivariate statistical tool, such as principal component analysis (PCA). The proposed method will be explained with an example of an automotive assembly.</div>

<div class="htmlview paragraph">There are several reasons why it can be daunting to apply Six Sigma to product creation. Foremost among them, the functional performance of new technologies is unknown prior to starting a project. Although, Design For Six Sigma (DFSS) was developed to overcome this difficulty, a lack of applicable in-class case studies makes it challenging to train the product creation community. The current paper describes an in-class project which illustrates how Six Sigma is applied to a simulated product creation environment. A toy construction set (TCS) project is used to instruct students how to meet customer expectations without violating cost, packaging volume and design-complexity constraints.</div>

This research focuses on constructing a mathematical model to predict functional defects in system testing by applying Six Sigma approach. The motivation behind this effort is to achieve zero known post release defects of the software delivered to end-user. Besides serving as the indicator of optimizing testing process, predicting functional defects at the start of testing allows testing team to put comprehensive test coverage, find as many defects as possible and determine when to stop testing so that all known defects are contained within testing phase. Design for Six Sigma (DfSS) is chosen as the methodology as it emphasizes on customers' requirement and systematic techniques to build the model. Historical data becomes the crucial elements in this study. Metrics related to potential predictors and their relationships for the model are identified, which focuses on metrics in phases prior to testing phase. Repeatability and capability of testers' consistency in finding defects are analyzed. Type of data required are also identified and collected. The metrics of selected predictors which incorporate testing and development metrics are measured against total functional defects using multiple regression analysis. The best and most significant mathematical model generated by the regression analysis is selected as the proposed prediction model for functional defects in system testing phase. Validation of the model is then conducted to prove the goodness for implementation. Recommendation and future research work are provided at the end of this study.

<div class="section abstract"><div class="htmlview paragraph">The ongoing global demand for greater energy efficiency plays an essential role in vehicle development, especially in the case of electric vehicles (EVs). The thermal management of the full vehicle is becoming increasingly important, since the Heating, Ventilation, and Air Conditioning (HVAC) system has a significant impact on the EV range. Therefore the EV design requires new guidelines for thermal management optimization.</div><div class="htmlview paragraph">In this paper, an advanced method is proposed to identify the most influential cabin design factors which affect the cabin thermal behavior during a cool down drive cycle in hot environmental conditions. These parameters could be optimized to reduce the energy consumption and to increase the robustness of the vehicle thermal response.</div><div class="htmlview paragraph">The structured Taguchi’s <i>Design for Six Sigma</i> (DFSS) approach was coupled with CFD-Thermal FE simulations, thanks to increased availability of HPC. The first control factors selected were related to the thermal capacity of the panel duct, dashboard, interior door panels and seats. Surface IR emissivity and solar radiation absorptivity of these components were then added to the study. Car glass with absorptive and reflective glazing were finally included in the study. The design space of 18 vehicle configurations was simulated in spring and hot summer conditions, with steady state thermal simulations. A 2-step optimization was then conducted, trying first to increase the robustness of the cabin response and, secondly, to reduce the equivalent temperature actually felt by passengers. The <i>Verify</i> phase was then conducted on the <i>Best Engineering</i> design emerged by the 2-step optimization, through quasi-transient CFD-Thermal FE analyses. The thermal results were then sent to a CFD 1D energy prediction model, confirming the HV battery energy saving and the extended range reached during the cool down drive cycle.</div></div>

Many organizations have successfully implemented Six Sigma (6σ) quality programs, but have begun to hit what they call the 5‐sigma barrier — they have discovered that you can only get so much quality improvement from the back end of the development process. To overcome this 5‐sigma barrier, organizations are increasingly adopting the Design for Six Sigma (DFSS) methodology that in many ways reflects the “systematics” of product development. This paper examines the Six Sigma and DFSS approach and how DFSS in essence is a “Statistical Systems Engineering” approach that can achieve six‐sigma levels and beyond in product development.

<div class="htmlview paragraph">A new high output supercharged Northstar DOHC 4.4L V8 engine has been developed for new “V” series Cadillac performance models. The new engine combines the highest power rating of any production Cadillac engine to date with operating refinement uncommon at this power level.</div> <div class="htmlview paragraph">The new engine incorporates a high capacity airflow system including a unique GM Powertrain (GMPT) patented supercharger. The design integrates the intake manifold and supercharger (SC) into a supercharger module (SCM) supplied with throttle body (TB) and intercoolers (IC).</div> <div class="htmlview paragraph">The new engine architecture is based on the naturally aspirated (NA) rear wheel drive (RWD) engine released in 2004, but has been specifically designed and upgraded from the NA version for the greater structural and thermal loads that result from supercharging. Technologies specific to this supercharged engine version include a precision sand cast aluminum block, multi-layer steel (MLS) head gaskets, heavy-duty pistons and connecting rods, a piston cooling system, and specially polished exhaust ports. This new design results in exceptional performance over the entire operating range coupled with uncommon operating refinement.</div> <div class="htmlview paragraph">Simultaneous engineering and extensive use of math-based 3D design and analysis enabled a short development time and minimized the amount of development hardware required, while ensuring the highest reliability for the new engine.</div> <div class="htmlview paragraph">The new engine will be manufactured at the all-new GM Powertrain Performance Build Center in Wixom, MI.</div>

The non-uniform AC current distribution among the multi-layer conductors in a high-temperature superconducting (HTS) cable reduces the current capacity and increases the AC loss. In this paper, Particle swarm optimization coupled with differential evolution operator (DEPSO) has been applied in structural optimization of HTS cables. While the existence of fluctuation in design variables or operation conditions has a great influence on the cable quality, in order to eliminate the effects of parameter perturbations in design and improve the design efficiency, a robust design method based on design for six sigma (DFSS) is applied in this paper. The optimization solutions show that the proposed optimization procedure can not only achieve a uniform current distribution, but also improve significantly the reliability and robustness of the HTS cable quality.

<div class="section abstract"><div class="htmlview paragraph">Existing multi-axle steering system designs generally use the deterministic optimization method without considering the uncertainties during the design process; therefore an actual steering movement may deviate from the ideal movement calculated by some mathematical models. In order to make design results have less sensitive to the uncertainties in the design process, some uncertainties need be taken into account at the early design stage. This paper proposes a robust optimization design method for a double front axle steering system (DFASS) of heavy trucks based on Monte Carlo method. The DFASS consists of two trapezoidal steering mechanisms (TSM) and one rocker system, and the optimization objectives of DFASS include the minimum mean value and variance of the maximum turning angle error of the TSM and rocker system. In addition, the robust optimization model includes 13 design variables which are all geometry parameters of DFASS and represented by normal distribution. Through the orthogonal experiment, we obtain the important factors affecting optimization objectives and build the response surface models of optimization objective. Based on the response surfaces, robustness design of DFASS is performed. By simulating analysis, the improved robustness of DFASS based on robust design method is approved.</div></div>

<div class="section abstract"><div class="htmlview paragraph">The exhaust blowdown pulse from each cylinder of a multi-cylinder engine propagates through the exhaust manifold and can affect the in-cylinder pressure of other cylinders which have open exhaust valves. Depending on the firing interval between cylinders connected to the same exhaust manifold, this blowdown interference can affect the exhaust stroke pumping work and the exhaust pressure during overlap, which in turn affects the residual fraction in those cylinders. These blowdown interference effects are much greater for a turbocharged engine than for one which is naturally aspirated because the volume of the exhaust manifolds is minimized to improve turbocharger transient response and because the turbines restrict the flow out of the manifolds.</div><div class="htmlview paragraph">The uneven firing order (intervals of 90°-180°-270°-180°) on each bank of a 90° V8 engine causes the blowdown interference effects to vary dramatically between cylinders. These effects are illustrated in this paper for a twin-turbocharged engine with single scroll turbochargers and log style exhaust manifolds. An AVL tool called Gas exchange and Combustion Analysis (GCA) is used to estimate residual fraction for each cylinder based on measured intake port, cylinder pressure, and exhaust port pressure profiles. The uneven firing interval causes imbalance between cylinders in residual fraction (increasing knock), fresh air (increasing CO due to uneven air-fuel ratio), and pumping work. These effects also preclude running high overlap for scavenging at low rpm, and diminish the potential benefits of dual cam phasing at part load.</div><div class="htmlview paragraph">The advantages and disadvantages of various methods to diminish the magnitude of these effects are investigated through 1D performance simulation and engine dynamometer testing, including the use of twin scroll turbochargers, exhaust camshafts with different exhaust valve opening timings on pairs of cylinders, and a balance tube between exhaust manifolds.</div></div>

<div class="htmlview paragraph">Cast aluminum alloys 356 and 319 and wrought alloy 3003 were corrosion tested in a commercial (Fleetguard DCA-4) supplemental coolant additive (SCA) package modified by varying the potassium nitrate level.</div> <div class="htmlview paragraph">Electrochemical techniques were used to determine the stability of the passive film as a function of nitrate concentration. Cyclic potentiodynamic polarization and cyclic galvanostaircase polarization were the principle techniques used and compared. In the presence of the other inhibitors, the passive film stability did not change as the nitrate concentration varied. The corrosion resistance of each alloy was more dependent on the alloy chemistry with 3003 being the most resistant and 319 being the least. The two electrochemical techniques provided results consistent with each other.</div> <div class="htmlview paragraph">With the introduction of advanced materials and processes to the heavy duty diesel engine, the challenge in formulating a coolant is to provide adequate protection for all the materials in the cooling system. Cast and wrought aluminum alloys are increasingly being used or are being considered for use in such components as manifolds, pump housings, and radiators. In the past, silicates have been used in coolants to provide protection to aluminum alloys, however overconcentration of the SCA has lead to silicate dropout in the form of a gel which interferes with coolant flow and heat transfer. The use of a low silicate phosphate/molybdate based additive package is an improvement over the traditional borate/nitrite system, however it still contains substantial amounts of nitrate. Although nitrate is added to improve pitting protection in aluminum, excessive amounts can promote brass cracking.</div> <div class="htmlview paragraph">Gravimetric techniques such as the ASTM D-1384 glassware test, cavitation, and hot surface testing have traditionally been used to develop SCA formulations for heavy duty use. Although electrochemical testing has been used extensively in diverse applications such as nuclear power generation, petrochemical production and industrial coatings development, it has only relatively recently come to be accepted for characterizing material behavior in heavy duty, cooling systems (<span class="xref">1</span>, <span class="xref">2</span>, <span class="xref">3</span>, <span class="xref">4</span> and <span class="xref">5</span>). In addition to the shorter test times for determining an “instantaneous” corrosion rate, valuable information can be obtained as to an alloy's natural passivity and the effectiveness of inhibitors in forming protective films (<span class="xref">6</span>). A brief summary of electrochemical testing theory is given in the Appendix and a list of terms and symbols are defined after the Conclusion section.</div> <div class="htmlview paragraph">The purpose of this study is to apply electrochemical corrosion measurement techniques to evaluate the effect of nitrate concentration in Fleetguard's DCA-4 on several typical aluminum alloys, both cast and wrought. It is hoped that the results of this will allow us to specify the minimum amount of nitrate for adequate pitting protection for these alloys. Cyclic potentiodynamic polarization and cyclic galvanostaircase polarization were the primary experimental techniques used to study passivation as a function of nitrate concentration. Potentiodynamic polarization (Tafel plots) were used to measure corrosion current, and hence, rate and polarization resistance. While cyclic potentiodynamic polarization is more commonly used to study repassivation, the kinetic effects on aluminum alloys in particular make the results from this technique dependent on the parameters chosen in making the scan. The pitting potential and the protection potential are dependent, for example on scan rate. To avoid these problems, Hirozawa has proposed the use of the cyclic galvanostaircase technique. This method and its advantages are described in more detail elsewhere (<span class="xref">7</span>, <span class="xref">8</span> and <span class="xref">9</span>). In this study, these two methods will be compared in our specific environment.</div>

<div class="htmlview paragraph">Three diesel engine types with cylinder capacities of 5.86; 9.57 and 17.7 liters have been converted to spark ignition engines for liquefied petroleum gas (LPG) fuel. These four-stroke, water-cooled engines cover a power range from 96 kW to 230 kW and are suitable for use in heavy-duty trucks, buses and stationary applications. The first two engines - the 8060 and 8220 - are six in-line engines, the 8280 is a V8 engine. Todate only naturally aspirated LPG engines have been completely developed.</div> <div class="htmlview paragraph">In view of the availability of the fuel, attractive costs in some areas and in order to offer an alternative to diesel engines if the proposed emission legislation in the nineties with regard to particulates and nitric oxide emissions cannot be fulfilled economically, LPG powered vehicles may be an attractive option for urban applications.</div> <div class="htmlview paragraph">This paper describes the IVECO 8060, 8220 and 8280 LPG engines and their operating characteristics. The performance characteristics of these engines are attractive for road vehicle applications because they provide maximum torque at low engine speeds and an extended full load speed range. The overall engine durability is superior to that of gasoline-based LPG engines and may even be superior to diesel engines.</div>