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2016-04-05
Technical Paper
2016-01-0267
Rahul Rama Swamy Yarlagadda, Efstratios Nikolaidis, Vijay Kumar Devabhaktuni
Over the last two decades inverse problems have become increasingly popular due to their widespread applications. This popularity continuously demands designers to find alternative methods, to solve the inverse problems, which are efficient and accurate. It is important to use effective techniques that are both highly accurate and computationally efficient. This paper presents a method for solving inverse problems through Artificial Neural Network (ANN) theory. This paper also presents a method to apply Grey Wolf optimizer (GWO) algorithm to solve inverse problems. GWO is a recent optimization method demonstrating great results. Both of the methods are then compared to traditional methods such as Particle Swarm Optimization (PSO) and Markov Chain Monte Carlo (MCMC). Four typical engineering design problems are used to compare the four methods' performance. The results show that the GWO outperforms other methods both in terms of efficiency and accuracy.
2016-04-05
Technical Paper
2016-01-0289
Balakrishna Chinta
Mahalanobis Distance (MD) is gaining momentum in many fields where classification, statistical pattern recognition, and forecasting are primary focus. It is a multivariate method and considers correlation relationships among parameters for computing generalized distance measure to separate groups or populations. MD is a useful statistic in multivariate analysis to test that an observed random sample is from a multivariate normal distribution. This capability alone enables engineers to determine if an observed sample is an outlier (defect) that falls outside the constructed (good) multivariate normal distribution. In Mahalanobis-Taguchi System (MTS), MD is suitably scaled and used as a measure of severity of an abnormality. It is obvious that computed MD depends on values of parameters observed on a random sample. All parameters may not equally impact MD. MD could be highly sensitive with respect to some parameters and less sensitive to some other parameters.
2016-04-05
Technical Paper
2016-01-0278
Philipp Bergmeir, Christof Nitsche, Jürgen Nonnast, Michael Bargende
In order to achieve high customer satisfaction and to avoid high warranty costs caused by component failures of the power-train of hybrid electric vehicles (HEV), car manufacturers have to optimize the dimensioning of these elements. Hence, it is obligatory for them to gain knowledge about the different types of vehicle usage being predominant all over the world. Therefore, in this paper we present a Data Mining system that combines an Autoencoder, i.e., a special kind of Artificial Neural Network used for unsupervised representation learning, with t-Distributed Stochastic Neighbor Embedding, i.e., a technique for dimensionality reduction, to automatically identify and visualize different types of vehicle usage by applying them to aggregated logged on-board data, i.e., load spectrum data.
2016-04-05
Technical Paper
2016-01-0320
Tejas Janardan Sarang, Mandar Tendolkar, Sivakumar Balakrishnan, Gurudatta Purandare
In the automotive industry, multiple prototypes are used for vehicle development purpose. One of the challenging issues focused in R&D is the repeatability of durability tests, in order to get proper failure results for lifetime prediction. Durability test of a vehicle should have consistency throughout the testing period to provide accurate results for assessment and validation. The present work deals with more complex situations than what univariate methods can offer in terms of analysis. Hence, univariate analysis gives less accurate results in terms of checking the repeatability of tests. The current work deals with the development of a new repeatability analysis approach using multivariate analysis. The technique is developed with a non-parametric multivariate method called Mantel test which brings down all the complex parameters of the analysis to one number for checking the repeatability and take corrective measures accordingly.
2016-04-05
Technical Paper
2016-01-0072
Jihas Khan
Unified Diagnostic Service and On Board Diagnostics requires a client side device with a necessary software to implement certain specific algorithms. This paper is proposing a highly optimized, reusable and scalable model based software architecture for implementing these particular algorithms which include flow control, timing control, CAN database parsing, logging of messages, ODX/MDX database parsing, security unlock, intuitive HMI layer design, fault insertion hardware control, DTC display with textual information, frame control, multi network - multi ECU support, software flashing, physical-functional message handling, dll support for other software and interface for multiple hardware host devices. Re usability of this model based product ensures that it can be ported to the diagnostic tool used by a work shop engineer or by a diagnostics validation engineer working at OEM or Tier 1 side. This means that this software is hardware independent.
2016-04-05
Technical Paper
2016-01-0271
David A. Warren
The objective of the paper is to outline the steps taken to change the reliability and maintenance environment of a plant from completely reactive to proactive. The main systems addressed are maintenance function fulfillment with existing staffing; work order management, planning, and scheduling; preventive maintenance (PM) definition and frequency establishment; predictive maintenance (PdM) scheduling and method definition; and shutdown planning and execution. The work order management methods were evaluated and modified to provide planning and scheduling of work orders on a weekly basis. The computerized maintenance and management system (CMMS) was updated to automatically insert work orders into the backlog of work for completion. A failure modes and effects analysis (FMEA) was performed and the results of the FMEA led to implementation of the following PM and PdM activities: vibration analysis, thermal imaging, and temperature monitoring.
2016-04-05
Technical Paper
2016-01-1212
Yupu Chen, Miaohua huang
Lithium-ion battery plays a key role in electric vehicles, which is critical to the system availability. One of the most important aspects in battery managements systems(BMS) in electric vehicles is the stage of health(SOH) estimation. The state of health (SOH) estimation is very critical to battery management system to ensure the safety and reliability of EV battery operation. The classical approach of current integration(coulomb counting) can not get the accurate values because of accumulative error. In order to provide timely maintenance and replacements of electric vehicles, several estimation approaches have been proposed to develop a reliable and accurate battery state of health estimation. A common drawback of previous algorithm is that the computation quantity is huge and not quite accurate, that is updated partially in this study.
2016-04-05
Technical Paper
2016-01-1112
Byeong wook Jeon, Sang-Hwan Kim, Donghoon Jeong, Joseph Young-il Chang
In general, driving performance development of a vehicle is focused on satisfying preference of average customers. But there is no single standardized setup which can fulfill various driving tastes of all drivers, since they are different by gender, culture, age group, and personal habits. To resolve this issue, automotive companies have introduced selectable drive mode buttons which drivers can manually select desired drive mode among Normal, Eco, and Sport. These manually selected multi-mode systems provides variety of choices than single-mode system, but it still is a transitory solution which induces inconvenience of requiring drivers' effort to select and frequently change preferred drive mode in volatile driving situations. Also, it is a questionable supposition that categorizing complex needs of drivers into 3 modes is sufficient.
2016-04-05
Technical Paper
2016-01-0643
Jian Zhang, Changwen Liu, Fengrong Bi, Yiqiang Pei, Xiaobo Bi
Knock threshold detection is the key of closed loop control of ignition in gasoline engine, and it is also the difficult point in knock measurement. In this paper, an investigation of knock detection in gasoline direct injection (GDI) engines using bispectrum slice and ensemble empirical mode decomposition (EEMD) based on the engine cylinder head vibration signals. By adding some finite amplitude Gaussian white noises to the signal, EEMD keeps the signal continuous in different time span, and therefore the mode mixing inhering in the classical empirical mode decomposition (EMD) method is alleviated. Power spectrum density (PSD) estimation is used to determine the band range of the resonance frequency generated by knock component. EEMD was used to decompose the original signals, the time-frequency characteristics of the Intrinsic Mode Functions (IMF) were analyzed using Continues Wavelet Transform (CWT) due to its excellent time-frequency resolution.
2016-04-05
Technical Paper
2016-01-1195
Atsushi Baba, Kinnosuke Itabashi, Nozomu Teranishi, Yoshihiro Edamoto, Kensuke Osamura, Ichiro Maruta PhD, Shuichi Adachi PhD
This paper proposes a battery state estimation on a battery management system (BMS) for hybrid electric vehicles (HEVs) and electric vehicles (EVs). It is important to estimate a state of charge (SOC) and parameters of the battery such as a state of health (SOH), internal resistances and dynamics of electrochemical reactions. The BMS can provide information on the driving range of the EVs to the drivers by accurately estimating SOC and SOH. It can also calculate a state of power (SOP) to use the battery safely by accurately estimated SOC, internal resistances and others. For that purpose, this paper proposes the BMS adopted a simultaneous state of charge (SOC) and parameter estimation method using log-normalized unscented Kalman filter. The key idea is a log-normalization of the parameters to improve numerical stability and robustness of the algorithm. The proposed system is verified by a series of simulations using experimental data with EVs.
2016-04-05
Technical Paper
2016-01-0642
Understanding oil transport mechanisms is critical to developing better tools for oil consumption and piston skirt lubrication. Our existing Two-Dimensional Laser Induced Fluorescence (2DLIF) with an acquisition rate of 1 frame every one or two cycles was proven to be effective to display oil accumulation patterns and their evolution over many cycles in the piston ring pack system. Yet, the existing system is unable to resolve instantaneous oil flows in the piston system. In this work, a high-speed LIF system was developed. After a number of iterations the finalized high speed LIF system includes a 23 W, 100 kHz, 532 nm laser and a high speed camera capable of 100,000 FPS at 384 x 264 pixel resolution. After each component was selected, optimization of the quality of images taken from the system began. Each component in the optical system was tested for improvement of image quality; such components include: camera lens, beam expander, beam splitter, and optical filter.
2016-04-05
Technical Paper
2016-01-0283
Joydip Saha, Harry Chen, Sadek Rahman
More stringent Federal emission regulations and fuel economy requirements have driven the automotive industry toward more sophisticated vehicle thermal management systems which may include various new technologies such as active grill shutter, variable coolant flow control devices, PWM controlled fan and control strategies in order to best utilize the waste heat and minimize overall power consumption. With these new technologies and new devices, the comprehensive vehicle-thermal-system simulation tools are essential to evaluate and develop the optimal system solution for new cooling system architectures. This paper will discuss how the model-based vehicle thermal system simulation tools have been developed from analytical & empirical data, and have been used for assessment and development of new cooling system architectures.
2016-04-05
Technical Paper
2016-01-0641
Thomas De Cuyper, Sam Bracke, Jolien Lavens, Stijn Broekaert, Kam Chana, Michel De Paepe, Sebastian Verhelst
To optimize internal combustion engines (ICEs), a good understanding of engine operation is essential. The heat transfer from the working gases to the combustion chamber walls plays an important role, not only in the performance, but also in the emissions of the engine. Besides, thermal management of ICEs is becoming more and more important as an additional tool for optimizing efficiency and emission aftertreatment. In contrast little is known about the convective heat transfer inside the combustion chamber due to the complexity of the working processes. Heat transfer measurements inside the combustion chamber pose a challenge in instrumentation due to the harsh environment. Additionally, the heat loss in a spark ignition (SI) engine shows a high temporal and spatial variation. In this paper we examine the heat transfer in a production SI ICE through the use of Thin Film Gauge (TFG) heat flux sensors. An inlet valve has been equipped with 7 TFG sensors in a row.
2016-04-05
Technical Paper
2016-01-0377
Wallace Ferreira, Trenton Meehan, Valdir Cardoso, Neil Bishop
In most aspects of mechanical design related to a motor vehicle there are two ways to treat dynamic fatigue problems: A time domain approach vs. a frequency domain approach. Time domain approaches are the most common and most widely used especially in the automotive industries. On the other hand, frequency domain approaches can provide some analysis advantages especially in terms of computational costs and lead time for results delivery. There are only few commercially available software packages that handle fatigue problems in the frequency domain and most of them are limited to single input analysis (or small numbers of inputs) or they are limited in terms of the types of stresses that can be processed, or the type of fatigue analysis that can be performed (typically the strain-life approach is excluded). These are serious limitations.
2016-04-05
Technical Paper
2016-01-0274
Sharon L. Honecker, David J. Groebel, Adamantios Mettas
In order to accurately predict product reliability, it is best to design a test in which many specimens are tested for a long duration. However, this scenario is not often practical due to economic and time constraints. This paper describes a reliability test in which a limited number of specimens are tested with little time remaining before the scheduled start of production. During the test, an unexpected failure mode that can be mitigated through a product redesign occurs. Because the scheduled start of production is near, there is not time to perform a test with redesigned specimens, so the current test proceeds as planned. We discuss several methods and the associated assumptions that must be made to account for the presence of the unexpected failure mode in the test data in order to make predictions of reliability of the redesigned product.
2016-04-05
Technical Paper
2016-01-0279
Chong Chen, Zhenfei Zhan, Jie Li, Yazhou Jiang, Helen YU
To reduce the computational time in the iterations of reliability-based design optimization, surrogate models are frequently utilized to approximate time-consuming computer aided engineering models. However, surrogate models introduces additional sources of uncertainty, such as model uncertainty. In this paper, an efficient uncertainty quantification method considering both model and parameter uncertainties is proposed. Firstly, the uncertainty of input parameters are represented in the form of Probability Density Function (PDF). Then, bias correction is then performed to improve the predictive capabilities of the surrogate models, whose uncertainty can be quantified as confidence intervals. Finally, Monte Carlo sampling is utilized to quantify the compound uncertainties. A numerical example and a real-world vehicle weight reduction design example are used to demonstrate the validity of the proposed method.
2016-04-05
Technical Paper
2016-01-0350
Andre Camboa, Bernardo Ribeiro, Miguel Vaz, Luis Pinheiro, Ricardo Malta
This paper describes the development of an automotive bonnet for an electric vehicle based on a polymer-metal hybrid configuration. Special focus is given to the engineering design and prototyping phases. Three different reinforcement geometries were developed and six mechanical simulations were done through finite element analysis to aid best frame geometry choice. The entire bonnet was prototyped containing the selected frame geometry. The fabrication of the frame was performed through metal stamping and the exterior panel through reaction injection moulding followed by their assembling through adhesive bonding. A dimensional control was made over metallic frame by using 3D scanning equipment in order to measure geometrical divergence implicit by its fabrication. This paper addresses also the tool engineering development for those three previous mentioned processes.
2016-04-05
Technical Paper
2016-01-0268
Junqi Yang, Zhenfei Zhan, Ling Zheng, Helen Yu, Yazhou Jiang, Hui Zhao, Jie LI
Computer modeling and simulation have significantly facilitated the efficiency of product design and development in modern engineering, especially in the automotive industry. For the design and optimization of car models, optimization algorithms usually work better if the initial searching points are within or close to a feasible domain. Therefore, finding a feasible design domain in advance is beneficial. A data mining technique, ID3 (Iterative Dichotomizer 3), is exploited in this paper to identify a set of reduced feasible design domains from the original design space. Within the reduced feasible domains, optimal designs can be efficiently obtained while releasing computational burden in iterations. A mathematical example is used to illustrate the proposed method. Then an industrial application about automotive structural optimization is employed to demonstrate the proposed methodology. The results show its potential in practical engineering.
2016-04-05
Technical Paper
2016-01-0276
Mahalingesh Burkul, Hemant Bhatkar, Mahesh Badireddy, Narayanan Vijayakumar
In an automotive product development environment, identifying the premature structural failures is one of the important tasks for Body-In-White (BIW), sub-assemblies and components. The integrated car body structure i.e. monocoque structure, is widely used in passenger cars and SUVs. This structure is subjected to bending and torsional vibrations, due to dynamic loads. Normally the stresses due to bending are relatively small compared to stresses due to torsion in Body-In-White under actual road conditions [1]. This paper focuses on evaluating the life of Body-In-White structures subjected to torsional loading. An accelerated test method was evolved for identifying failure modes of monocoque BIW by applying torsion fatigue. The observation of the crack generation and propagation was made with respect to a number of torsion fatigue cycles.
2016-04-05
Journal Article
2016-01-0075
Steven Holland, Tim Felke, Luis Hernandez, Robab Safa-Bakhsh, Matthew A. Wuensch
Aerospace Recommended Practice (ARP) 6268 has been developed to specify a common process by which IVHM functionality and supporting design data for components and subsystems can be integrated into larger Integrated Vehicle Health Management (IVHM) applications. The ARP has been developed within the Framework of the SAE HM1 committee by engineering focals from automotive and aerospace perspectives. The intent of the ARP is to facilitate a substantial reduction in the cost to develop, deploy and support IVHM systems through the use of standard interfaces and machine interpretable data submittals. This paper will provide an overview of the principle elements of the ARP and describe how it would be applied by Integrators and suppliers of components and systems for Aerospace and Automotive applications.
2016-04-05
Journal Article
2016-01-0282
Julio Abraham Carrera
Recent emissions standards have become more restrictive in terms of CO2 and NOx reduction. This has been translated into higher EGR rates at higher exhaust gas temperatures with lower coolant flow rates for much longer lifetimes. In consequence, Thermal Load for EGR coolers has been increased and boiling and its interaction with thermal fatigue are now a critical issue during their development. It is almost impossible to avoid localized boiling inside an EGR cooler and, in fact, it would not be strictly necessary when it is below the Critical Heat Flux (CHF). However when CHF is exceeded, film boiling occurs leading to the sudden drop of the heat transfer rate and the metal temperature rise. In consequence, thermal stress increases even when film boiling is reached only in a small area inside the part. It is very difficult to accurately predict under which conditions CHF is reached and to stablish the margins to avoid it.
2016-04-05
Journal Article
2016-01-0277
Xingxing Feng, Kaimin Zhuo, Jinglai Wu, Vikas Godara, Yunqing Zhang
Interval inverse problems can be defined as problems to estimate input through given output, where the input and output are interval numbers. Many problems in engineering can be formulated as inverse problems like vehicle suspension design. Interval metrics, instead of deterministic metrics, are used for the suspension design of a vehicle vibration model with five degrees of freedom. The vibration properties of a vehicle vibration model are described by reasonable intervals and the suspension interval parameters are to be solved. A new interval inverse analysis method, which is a combination of Chebyshev inclusion function and optimization algorithm such as multi-island genetic algorithm, is presented and used for the suspension design of a vehicle vibration model with six conflicting objective functions. The interval design of suspension using such an interval inverse analysis method is shown and validated, and some useful conclusions are reached.
2016-04-05
Journal Article
2016-01-0280
Alaa El-Sharkawy, Amr Sami, Abd El-Rahman Hekal, Dipan Arora, Masuma Khandaker
`In this paper, the development a transient thermal analysis model for the exhaust system is presented. Given the exhaust gas temperature out of the engine, a software tool has been developed to predict changes in exhaust gas temperature and exhaust surface temperature under various operating conditions. The software is a thermal solver that will predict exhaust gas and wall surface temperature by modeling all heat transfer paths in the exhaust system which includes multi-dimensional conduction, internal forced/natural convection, external forced/natural convection, and radiation. The analysis approach involves the breaking down of the thermal system into multiple components, which include the exhaust system (manifold, takedown pipe, tailpipe, etc.), catalytic converter, DPF/GPF (diesel particulate filter or gasoline particulate filter), if they exist, thermal shields, etc.
2016-04-05
Journal Article
2016-01-0640
Alan Kastengren, Daniel Duke, Andrew Swantek, James Sevik, Katarzyna Matusik, Thomas Wallner, Christopher F. Powell
Understanding the short-lived structure of the plasma that forms between the electrodes of a spark plug is crucial to the development of improved ignition models for SI engines. However, measuring the amount of energy deposited in the gas directly and non-intrusively is difficult, due to the short time scales and small length scales involved. The breakdown of the spark gap occurs at nanosecond time scales, followed by an arc phase lasting a few microseconds. Finally, a glow discharge phase occurs over several milliseconds. It is during the arc and glow discharge phases that most of the heat transfer from the plasma to the electrodes and combustion gases occurs. In this paper, we present the results of a proof of concept experiment that demonstrates the use of time-resolved x-ray radiography to measure the density of the plasma in the spark gap during the glow discharge phase of a conventional transistorized coil ignition system.
2016-04-05
Journal Article
2016-01-0644
Syahar Shawal, Martin Goschutz, Martin Schild, Sebastian Kaiser, Marius Neurohr, Juergen Pfeil, Thomas Koch
Early flame-front propagation has been investigated in research engines with large optical access for quite some time. Usually, chemiluminescence is visualized with sensitive camera systems and the images can then be used to, e.g., determine flame shape and flame-front propagation speed. However, optically accessible internal combustion engines are limited in their operating range (load and speed), have large uncooled glass parts, and operate mostly in steady state. In contrast, large-aperture UV endoscopes enable optical access in nearly unmodified production engines, operated at speeds and loads significantly exceeding the limits of most “optical” engines. Here, we investigate the image quality achievable with an endoscope system in terms of detecting the premixed flame front. This study is an extension of our previous work on endoscopic flame imaging documented in SAE 2014-01-1178.
2016-04-05
Journal Article
2016-01-0639
Brian C. Kaul, Benjamin Lawler, Akram Zahdeh
Engine acoustics measured by microphones near the engine have been used in controlled laboratory settings for combustion feedback and even combustion phasing control, but the use of these techniques in a vehicle where many other noise sources exist is problematic. In this study, surface-mounted acoustic emissions sensors are installed on the block of a 2.0L turbocharged GDI engine, and the signal is analyzed to identify useful feedback features. The use of acoustic emissions sensors, which have a very high frequency response and are commonly used for detecting material failures for health monitoring, including detecting gear pitting and ring scuffing on test stands, enables detection of acoustics both within the range of human hearing and in the ultrasonic spectrum. The high-speed acoustic time-domain data are synchronized with the crank-angle-domain combustion data, and various engine events, including combustion and both the start and end of fuel injection are identified.
2016-04-05
Technical Paper
2016-01-0073
Peter Subke, Muzafar Moshref
Especially in the production of passenger cars, the reprogramming of electronic control units can be considered as state-of-the art. Today, the automotive industry has to solve the problem that reprogramming of the ever-increasing amount of data takes too long. The CAN bus as interface hit the wall, CAN-FD might solve the problem, Ethernet will do. UDSonIP (ISO 14229) on DoIP (ISO 13400) and Ethernet (IEEE 802.11) are employed in the production of high-class passenger cars. On those vehicles, former discretionary pins of the OBD connector (SAE J1962) are used for the wired connection of external test equipment that supports UDSonIP. With a device that that fits the OBD connector and acts as a bridge between the Ethernet signals to WLAN, external test equipment that supports wireless communication, can be connected to the vehicle. Examples for such wireless devices include smart phones and tablets.
2016-04-05
Journal Article
2016-01-0269
Zhigang Wei, Michael Start, Jason Hamilton, Limin Luo
Durability and reliability performance is one of the most important concerns for vehicle components and systems, which experience cyclic fatigue loadings and may eventually fail over time. Durability and reliability testing is a critical process in product validation but it is usually costly and time consuming. Therefore, accelerated testing methods are often used to shorten the development time, reduce the associated cost while not significantly sacrifice the accuracy of the assessment. There are several commonly used accelerated testing methods available: accelerated test-to-failure, accelerated binomial testing (bogey testing), and accelerated degradation testing etc. However, these accelerated testing methods are often used separately and independently. Therefore, the maximum potential, in terms of efficiency and economy, of these accelerated testing methods has not been fulfilled. In this paper, a general framework for accelerated testing and data analysis is established.
2016-04-05
Technical Paper
2016-01-0270
Zhigang Wei, Limin Luo, Michael Start, Litang Gao
Statistical parameters, such as mean, standard deviation, in particular, failure probability are of significant interest to durability and reliability engineers. These parameters can be estimated from samples, however, these estimated parameters usually contain significant uncertainties and cannot be fully representative of the population, particularly, for test data with small sample sizes. Generally, sample size is a balanced result between durability/reliability performance and cost. There are several ways to characterize and quantify the uncertainty caused by the sample size effects, and one of the most commonly used engineering approach for failure probability is RxxCyy, in which xx and yy represent xx% reliability (R) and yy% confidence (C). RxxCyy criterion is commonly used in both test-to-failure method and the binomial test method [4-8].
2016-04-05
Technical Paper
2016-01-0076
Mostafa Anwar Taie, Eman Magdy Moawad, Mohammed Diab, Mohamed ElHelw
New challenges and complexities are continuously increasing in advanced driver assistance systems (ADAS) development (e.g. active safety, driver assistant and autonomous vehicle systems). Therefore, the health management of ADAS’ components needs special improvements. Since software contribution in ADAS’ development is increasing significantly, remote diagnosis and maintenance for ADAS become more important. Furthermore, it is highly recommended to predict the remaining useful life (RUL) for the prognosis of ADAS’ safety critical components; e.g. (Ultrasonic, Cameras, Radar, Lidar). This paper presents a remote diagnosis, maintenance and prognosis (RDMP) framework for ADAS, which can be used during development phase and mainly after production. An overview of RDMP framework’s elements is explained to demonstrate how/when this framework is connected to database servers and remote analysis servers.
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