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2017-10-08
Journal Article
2017-01-2446
Pengchuan Wang, Nikolaos Katopodes, Yuji Fujii
Abstract Wet clutch packs are the key component for gear shifting in the step-ratio automatic transmission system. The clutch plates are coupled or de-coupled to alter gear ratios based on the driver’s actions and vehicle operating conditions. The frictional interfaces between clutch plates are lubricated with automatic transmission fluid (ATF) for both thermal and friction management. In a 10-speed transmission, there may be as many as 6 clutch packs. Under typical driving conditions, 2 to 3 clutch packs are open, shearing ATF and contributing to energy loss. There is an opportunity to improve fuel economy by reducing the associated viscous drag. An important factor that directly affects clutch drag is the clearance between rotating plates. The axial position of clutch plates changes continuously during operation. It is known in practice that not only the total clearance, but also its distribution between the plates affects the viscous drag.
2017-09-23
Technical Paper
2017-01-1982
Xiaoming Lan, Hui Chen, Xiaolin He, Jiachen Chen, Yosuke Nishimura, Kazuya Ando, Kei Kitahara
Abstract In the recent years, the interaction between human driver and Advanced Driver Assistance System (ADAS) has gradually aroused people’s concern. As a result, the concept of personalized ADAS is being put forward. As an important system of ADAS, Lane Keeping Assistance System (LKAS) also attracts great attention. To achieve personalized LKAS, driver lane keeping characteristic (DLKC) indices which could distinguish different driver lane keeping behavior should be researched. However, there are few researches on DLKC indices for personalized LKAS. Although there are many researches on modeling driver steering behavior, these researches are not sufficient to obtain DLKC indices. One reason is that most of researches are for double lane change behavior which is different from driver lane keeping behavior.
2017-03-28
Technical Paper
2017-01-1398
Yoshiyuki Hatakeyema
Abstract Since drowsy driving is a major cause of serious traffic accidents, there is a growing requirement for drowsiness prevention technologies. This study proposes a drowsy driving prediction method based on eye opening time. One issue of using eye opening time is predicting strong drowsiness before the driver actually feels sleepy. Because overlooking potential hazards is one of the causes of traffic accidents and is closely related to driver cognition and drowsiness, this study focuses on eye opening movements during driving. First, this report describes hypotheses concerning drowsiness and eye opening time based on the results of previous studies. It is assumed that the standard deviation of eye opening time (SDEOP) indicates driver drowsiness and the following two transitions are considered: increasing and decreasing SDEOP. To confirm the hypotheses, the relationship between drowsiness and SDEOP was investigated.
2017-03-28
Technical Paper
2017-01-0894
Nishant Singh
Abstract Improving fuel economy has been a key focus across the automotive industry for several years if not decades. For heavy duty commercial vehicles, the benefits from minor gains in fuel economy can lead to significant savings for fleets as well as owners and operators. Additionally, the regulations require vehicles to meet certain GHG standards which closely translate to vehicle fuel economy. For current state of the art fuel economy technologies, incremental gains are so miniscule that measurements on the vehicle are inadequate to quantify the benefits. Engineers are challenged with high level of variability to make informed decisions. In such cases, highly controlled tests on Engine and Powertrain dynamometers are used, however, there is an associated variability even with these tests due to factors such as part to part differences, deterioration, fuel blends and quality, dyno control capabilities and so on.
2017-03-28
Technical Paper
2017-01-0050
Mario Berk, Hans-Martin Kroll, Olaf Schubert, Boris Buschardt, Daniel Straub
Abstract With increasing levels of driving automation, the perception provided by automotive environment sensors becomes highly safety relevant. A correct assessment of the sensors’ perception reliability is therefore crucial for ensuring the safety of the automated driving functionalities. There are currently no standardized procedures or guidelines for demonstrating the perception reliability of the sensors. Engineers therefore face the challenge of setting up test procedures and plan test drive efforts. Null Hypothesis Significance Testing has been employed previously to answer this question. In this contribution, we present an alternative method based on Bayesian parameter inference, which is easy to implement and whose interpretation is more intuitive for engineers without a profound statistical education. We show how to account for different environmental conditions with an influence on sensor performance and for statistical dependence among perception errors.
2017-03-28
Journal Article
2017-01-1507
Prashanta Gautam, Yousof Azizi, Abhilash Chandy
Abstract Tire noise is caused due to the complex interactions between the rotating tire and the road surface at the tire/road interface. It is usually caused due to a combination of individual noise generation mechanisms, which can either be structural or air-borne. The influence of each of these noise generation mechanism may vary, depending on various conditions such as tire design, road surface and operating conditions. Due to the many variables that affect the noise generation mechanisms in tires, it is usually a very complex task to isolate and categorize those that are present in the overall tire/road noise spectrum. Various approaches are used to categorize noise generation mechanisms in tires. In this paper, a statistical model based on the assumption that the tire noise acoustic pressure at a specific frequency band is related to the vehicle speed, is used, in order to study tire noise at different speeds.
2017-01-10
Technical Paper
2017-26-0326
Michael Wohlthan, Gerhard Pirker, Igor Sauperl, Andreas Wimmer, Wolfram Rossegger, Norbert Buch
Abstract Experimental investigations on engine test beds represent a significant cost in engine development. To reduce development time and related costs, it is necessary to check the quality of measurements automatically whenever possible directly on the test bed to allow early detection of faults. A fault diagnosis system should provide information about the presence, cause and magnitude of an inconsistency in measurement. The main challenge in developing such a system is to detect the fault quickly and reliably. However, only faults that have actually occurred should be detected because the user will only adopt a system that provides accurate results. This paper presents a methodology for automated fault diagnosis at engine test beds, starting with an explanation of the general procedure. Next, the methods applied for fault detection are introduced.
2016-06-15
Journal Article
2016-01-1809
Alexander Schell, Vincent Cotoni
Abstract Prediction of flow induced noise in the interior of a passenger car requires accurate representations of both fluctuating surface pressures across the exterior of the vehicle and efficient models of the vibro-acoustic transmission of these surface pressures to the driver’s ear. In this paper, aeroacoustic and vibro-acoustic methods are combined in order to perform an aero-vibro-acoustic analysis of a Mercedes-Benz A-class. The exterior aero-acoustic method consists of a time domain incompressible Detached Eddy Simulation (DES) and an acoustic wave equation. The method is extended in this paper to account for convection effects when modelling the exterior sound propagation. The interior vibro-acoustic model consists of a frequency domain Finite Element (FE) model of the side glass combined with a generalized Statistical Energy Analysis (SEA) model of the interior cabin.
2016-04-15
Journal Article
2015-01-9020
Emre Sert, Pinar Boyraz
Abstract Studies have shown that the number of road accidents caused by rollover both in Europe and in Turkey is increasing [1]. Therefore, rollover related accidents became the new target of the studies in the field of vehicle dynamics research aiming for both active and passive safety systems. This paper presents a method for optimizing the rear suspension geometry using design of experiment and multibody simulation in order to reduce the risk of rollover. One of the major differences of this study from previous work is that it includes statistical Taguchi method in order to increase the safety margin. Other difference of this study from literature is that it includes all design tools such as model validation, optimization and full vehicle handling and ride comfort tests. Rollover angle of the vehicle was selected as the cost function in the optimization algorithm that also contains roll stiffness and height of the roll center.
2016-04-05
Technical Paper
2016-01-1422
Tarek Ouali, Nirav Shah, Bill Kim, David Fuente, Bo Gao
Abstract This paper introduces a new method for driving style identification based on vehicle communication signals. The purpose of this method is to classify a trip, driven in a vehicle, into three driving style categories: calm, normal or aggressive. The trip is classified based on the vehicle class, the type of road it was driven on (urban, rural or motorway) and different types of driving events (launch, accelerating and braking). A representative set of parameters, selected to take into consideration every part of the driver-vehicle interaction, is associated to each of these events. Due to the usage of communication signals, influence factors, other than vehicle speed and acceleration (e.g. steering angle or pedals position), can be considered to determine the level of aggressiveness on the trip. The conversion of the parameters from physical values to dimensionless score is based on conversion maps that consider the road and vehicle types.
2016-04-05
Technical Paper
2016-01-1436
K. Han Kim, Sheila Ebert-Hamilton, Matthew Reed
Abstract Automotive seats are commonly described by one-dimensional measurements, including those documented in SAE J2732. However, 1-D measurements provide minimal information on seat shape. The goal of this work was to develop a statistical framework to analyze and model the surface shapes of seats by using techniques similar to those that have been used for modeling human body shapes. The 3-D contour of twelve driver seats of a pickup truck and sedans were scanned and aligned, and 408 landmarks were identified using a semi-automatic process. A template mesh of 18,306 vertices was morphed to match the scan at the landmark positions, and the remaining nodes were automatically adjusted to match the scanned surface. A principal component (PC) analysis was performed on the resulting homologous meshes. Each seat was uniquely represented by a set of PC scores; 10 PC scores explained 95% of the total variance. This new shape description has many applications.
2016-04-05
Technical Paper
2016-01-0113
William Buller, Rini Sherony, Brian Wilson, Michelle Wienert
Abstract Based on RADAR and LiDAR measurements of deer with RADAR and LiDAR in the Spring and Fall of 2014 [1], we report the best fit statistical models. The statistical models are each based on time-constrained measurement windows, termed test-points. Details of the collection method were presented at the SAE World Congress in 2015. Evaluation of the fitness of various statistical models to the measured data show that the LiDAR intensity of reflections from deer are best estimated by the extreme value distribution, while the RCS is best estimated by the log-normal distribution. The value of the normalized intensity of the LiDAR ranges from 0.3 to 1.0, with an expected value near 0.7. The radar cross-section (RCS) varies from -40 to +10 dBsm, with an expected value near -14 dBsm.
2016-04-05
Technical Paper
2016-01-0275
Frédéric Kihm, Andrew Halfpenny, Kurt Munson
Abstract Ground vehicle components are designed to withstand the real operational conditions they will experience during their service life. Vibration tests are performed to qualify their endurance. In order to replicate the same failure mechanism as in real conditions, the test specification must be representative of the service loads. The accelerated testing method, based on fatigue damage spectra (FDS), is a process for deriving a synthesized power spectral density (PSD) representing a random stationary Gaussian excitation and applied over a reduced duration. In real life, however, it is common that service loading includes non-Gaussian excitations. The consequences of not using a representative test signal during product validation testing are a higher field failure rate and added warranty costs. The objective of this paper is to describe a method for synthesizing a PSD test specification with a given kurtosis value, which represents a nonstationary non-Gaussian signal.
2016-04-05
Technical Paper
2016-01-0270
Zhigang Wei, Limin Luo, Michael Start, Litang Gao
Product validation and reliability demonstration require testing of limited samples and probabilistic analyses of the test data. The uncertainties introduced from the tests with limited sample sizes and the assumptions made about the underlying probabilistic distribution will significantly impact the results and the results interpretation. Therefore, understanding the nature of these uncertainties is critical to test method development, uncertainty reduction, data interpretation, and the effectiveness of the validation and reliability demonstration procedures. In this paper, these uncertainties are investigated with the focuses on the following two aspects: (1) fundamentals of the RxxCyy criterion used in both the life testing and the binomial testing methods, (2) issues and benefits of using the two-parameter Weibull probabilistic distribution function.
2016-04-05
Technical Paper
2016-01-0289
Balakrishna Chinta
Abstract 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 in abnormality assessment. 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
Journal Article
2016-01-0316
Dorin Drignei, Zissimos Mourelatos, Ervisa Kosova, Jingwen Hu, Matthew Reed, Jonathan Rupp, Rebekah Gruber, Risa Scherer
Abstract We have recently obtained experimental data and used them to develop computational models to quantify occupant impact responses and injury risks for military vehicles during frontal crashes. The number of experimental tests and model runs are however, relatively small due to their high cost. While this is true across the auto industry, it is particularly critical for the Army and other government agencies operating under tight budget constraints. In this study we investigate through statistical simulations how the injury risk varies if a large number of experimental tests were conducted. We show that the injury risk distribution is skewed to the right implying that, although most physical tests result in a small injury risk, there are occasional physical tests for which the injury risk is extremely large. We compute the probabilities of such events and use them to identify optimum design conditions to minimize such probabilities.
2016-04-05
Technical Paper
2016-01-1287
Kazutaka Kimura, Yuki Kudo, Akinori Sato
Abstract In recent years, automakers have been developing various types of environmentally friendly vehicles such as hybrid (HV), plug-in hybrid (PHV), electric (EV), and fuel cell (FCV) vehicles to help reduce greenhouse gas (GHG) emissions. However, there are few commercial solar vehicles on the market. One of the reasons why automakers have not focused attention on this area is because the benefits of installing solar modules on vehicles under real conditions are unclear. There are two difficulties in measuring the benefits of installing solar modules on vehicles: (1) vehicles travel under various conditions of sunlight exposure and (2) sunlight exposure conditions differ in each region. To address these problems, an analysis was performed based on an internet survey of 5,000 people and publically available meteorological data from 48 observation stations in Japan.
2016-04-05
Technical Paper
2016-01-0585
Muhsin M. Ameen, Yuanjiang Pei, Sibendu Som
Abstract The primary strength of large eddy simulation (LES) is in directly resolving the instantaneous large-scale flow features which can then be used to study critical flame properties such as ignition, extinction, flame propagation and lift-off. However, validation of the LES results with experimental or direct numerical simulation (DNS) datasets requires the determination of statistically-averaged quantities. This is typically done by performing multiple realizations of LES and performing a statistical averaging among this sample. In this study, LES of n-dodecane spray flame is performed using a well-mixed turbulent combustion model along with a dynamic structure subgrid model. A high-resolution mesh is employed with a cell size of 62.5 microns in the entire spray and combustion regions. The computational cost of each calculation was in the order of 3 weeks on 200 processors with a peak cell count of about 22 million at 1 ms.
2016-04-05
Technical Paper
2016-01-1582
Dirk Wieser, Sabine Bonitz, Lennart Lofdahl, Alexander Broniewicz, Christian Nayeri, Christian Paschereit, Lars Larsson
Abstract Flow visualization techniques are widely used in aerodynamics to investigate the surface trace pattern. In this experimental investigation, the surface flow pattern over the rear end of a full-scale passenger car is studied using tufts. The movement of the tufts is recorded with a DSLR still camera, which continuously takes pictures. A novel and efficient tuft image processing algorithm has been developed to extract the tuft orientations in each image. This allows the extraction of the mean tuft angle and other such statistics. From the extracted tuft angles, streamline plots are created to identify points of interest, such as saddle points as well as separation and reattachment lines. Furthermore, the information about the tuft orientation in each time step allows studying steady and unsteady flow phenomena. Hence, the tuft image processing algorithm provides more detailed information about the surface flow than the traditional tuft method.
2016-04-05
Journal Article
2016-01-0387
Yunkai Gao, Jingpeng Han, Jianguang Fang, Shihui Wang
Abstract A compiled method of the programmed load spectrum, which can simplify and accelerate the fatigue bench test of a car body, is proposed and its effectiveness is checked by the fatigue simulation. By using the multi-body dynamics model with a satisfactory accuracy, the virtual iteration is applied to cascade body loads from the wheel hubs. Based on the rain-flow counting method and statistics theory, the distributions of the body loads are analyzed, and then the programmed load spectrum is compiled and simplified. Through comparative study, the simulation results of random and programmed load spectrum are found to agree well with each other in terms of the damage distribution and fatigue life, which demonstrates the effectiveness of the presented method.
2016-04-05
Technical Paper
2016-01-0380
Ghassan Abed, Yung-Li Lee, Jian Zhu
Abstract Two popular critical plane models developed by Fatemi-Socie and Smith-Watson-Topper were derived from the experimental observations of the nucleation and growth of cracks during loading. The Fatemi-Socie critical plane model is applicable for the life prediction of materials for which the dominant failure mechanism is shear crack nucleation and growth, while the Smith-Watson-Topper model, for materials that fail predominantly by crack growth on planes perpendicular to the planes of maximum tensile strain or stress. The two critical plane models have been validated primarily by in-phase and 90° out-of-phase loading, and few, on the complex, non-proportional loading paths. A successful critical plane model should be able to predict both the fatigue life and the dominant failure planes.
2016-04-05
Technical Paper
2016-01-1387
Subash Sudalaimuthu, Barry (Baizhong) Lin, Mohamed Sithik, Rajeev Sakunthala Rajendran
Abstract The advanced Optimization techniques help us in exploring the light weight architecture. This paper explains the process of designing a lightweight track bar bracket, which satisfies all durability performance targets. The mounting locations and load paths are critical factors that define the performance and help in the development of weight efficient structure. The process is to identify the appropriate bolt location through Design of Experiment (DOE) and topology based studies; followed by section and shape optimization that help to distribute material in a weight efficient manner across the structure. Load path study using topology optimization is performed to identify the load path for durability load cases. Further shape optimization is done using hyper study to determine the exact thickness of the webs and ribs. A significant weight reduction from the baseline structure is observed. This process may be applicable for all casting components.
2016-04-05
Journal Article
2016-01-1572
Jugal Popat, Aneesh Nabar, Meighan Read, Chen Fu, Chunhui Zhang, Galab Kausik, Harsh Patel, Peter Thomas Tkacik
Abstract Published information on studies of something so critical to safety as passenger vehicle tire pressures can be found [1, 2]; however, they only account for rolling tires. Studies related to spare tire pressures are lacking. This paper is the result of measurements on 150+ vehicles and the most surprising results are presented regarding the influence of Tire Pressure Monitoring Systems (TPMS) and the new spare tire locations and use. A statistical study was performed on the collected data to determine the correlation between tire pressures, vehicle age and TPMS. One particular topic of investigation was the relationship between various factors that influence spare tire pressure. Some newer models, particularly some mini-vans, have placed the spare tire in an unusual and inconvenient place for regular maintenance. Based on the data collected, TPMS has a positive influence on rolling tires but not on spare tires.
2016-04-05
Technical Paper
2016-01-1616
Keiichiro Iida, Kunizo Onda, Akiyoshi Iida, Chisachi Kato, Shinobu Yoshimura, Yoshinobu Yamade, Yoshimitsu Hashizume, Yang Guo
Abstract One-way coupled simulation method that combines CFD, structural and acoustical analyses has been developed aiming at predicting the aeroacoustical interior noise for a wide range of frequency between 100 Hz and 4 kHz. Statistical Energy Analysis (SEA) has been widely used for evaluating transmission of sound through a car body and resulting interior sound field. Instead of SEA, we directly computed vibration and sound in order to investigate and understand propagation paths of vibration in a car body and sound fields. As the first step of this approach, we predicted the pressure fluctuations on the external surfaces of a car by computing the unsteady flow around the car. Secondly, the predicted pressure fluctuations were fed to the subsequent structural vibration analysis to predict vibration accelerations on the internal surfaces of the car.
2015-09-15
Technical Paper
2015-01-2441
Ahmet Oztekin
Abstract This paper outlines an analytical framework to perform a data-driven, risk-based assessment of Air Traffic Control (ATC) facilities. Safety associated with an ATC facility is modeled as an influence network using a set of risk factors. A novel hybrid approach employing Adaptive-Network based Fuzzy Inference Systems is introduced to propagate the model. Statistical analysis of system-wide data for each risk factor is performed to identify outliers and understand underlying distributions. They are then used to define Fuzzy Membership Functions for model variables. Analytical Hierarch Process (AHP) is used to determine rules required by the model's inference engine. Finally, the methodology is applied to a set of ATC facilities using real data.
2015-06-15
Technical Paper
2015-01-2236
Parimal Tathavadekar, Ricardo O. de Alba Alvarez, Michael Sanderson, Rabah Hadjit
Abstract Finite element analysis (FEA) is commonly used in the automotive industry to predict low frequency NVH behavior (<150 Hz) of structures. Also, statistical energy analysis (SEA) framework is used to predict high frequency (>400 Hz) noise transmission from the source space to the receiver space. A comprehensive approach addressing the entire spectrum (>20 Hz) by taking into account structure-borne and air-borne paths is not commonplace. In the works leading up to this paper a hybrid methodology was employed to predict structure-borne and air-borne transfer functions up to 1000 Hz by combining FEA and SEA. The dash panel was represented by FE structural subsystems and the noise control treatments (NCTs) and the pass-throughs were characterized via testing to limit uncertainty in modeling. The rest of the structure and the fluid spaces were characterized as SEA subsystems.
2015-05-01
Journal Article
2015-01-9083
Salah A. Elmoselhy
In order to strike a balance between cost and availability, the present study presents the strategic implementation of the hybrid lean-agile manufacturing system. The proposed implementation is based on literature review and statistical analysis. The study presents short term and long term proposed plans for implementing this newly developed system in a sustainable way. It shows how the strategic facet of the hybrid lean-agile manufacturing system addresses the key manufacturing competitive dimensions. The paper presents as well a cost-benefit analysis in comparison with the lean manufacturing system and agile manufacturing system based on the net present value. The study shows that the expectedly most efficient among the manufacturing systems is the Hybrid Lean-Agile Manufacturing System with normalized comparative improvement of about 58% and 42%, respectively.
2015-04-14
Technical Paper
2015-01-0232
Yanwu Ge, Gang Li, Xiang Di
Abstract In view of the requirements of torque-based engine control and coordinated control for hybrid powertrain systems during mode switching and shifting, engine torque needs to be known. A framework for torque generated model was established, and the influencing factors of engine effective torque were analyzed. Then steady and transient performance tests of DEUTZ 6V1015 diesel engine were designed in order to get sample data to train ENNs. By use of the trained ENNs the estimations of both steady and transient friction torque and indicated thermal efficiency were completed, results were: the estimation error of friction torque and indicated thermal efficiency was less than 5%. Then the complete torque generated model was established by embedding the trained ENNs, and the estimation of effective torque was done, results were: the estimation error was less than 5%.
2015-04-14
Journal Article
2015-01-0243
Ludwig Brabetz, Tobias Kerner, Mohamed Ayeb
Abstract The increasing power and safety requirements of electrical systems present a challenge for future automotive electrical networks. However, the modeling of use-profiles and the overall power consumption of electrical systems proves to be difficult as the number of potential on/off combinations of the loads is tremendous. Furthermore, the operation of some loads is correlated or depends upon the operating conditions. Thus, simple worst-case calculations applied to this complexity often lead to an over-specification of components. The proposed approach is based on the probabilities of loads being in the on-state and their respective interdependencies with each other and with boundary conditions such as time of day. Applying basic statistics and a new iterative algorithm, it allows the calculation of the probability of consumed total power for a given set of boundary conditions and of, very importantly, its expected continuous period.
2015-04-14
Journal Article
2015-01-0480
Santosh Tiwari, Don Jones, Simon Xu
Abstract Response Surface Models are often used as a surrogate for expensive black-box functions during optimization to reduce computational cost. Often, the CAE analysis models are highly nonlinear and multi-modal. A response surface approximation of such analysis as a result is highly multi-modal; i.e. it contains multiple local optima. A gradient-based optimizer working with such a response surface will often converge to the nearest local optimum. There does not exist any method to guarantee a global optima for non-convex multi-modal functions. For such problems, we propose an efficient algorithm to find as many distinct local optima as possible. The proposed method is specifically designed to work in large dimensions (about 100 ∼ 1000 design variables and similar number of constraints) and can identify most of the locally optimal solutions in a reasonable amount of time.
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