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Viewing 121 to 150 of 10366
2017-03-28
Technical Paper
2017-01-0064
Agish George, Jody Nelson
Abstract The ISO 26262 standard for functional safety was first released in 2011 and has been widely incorporated by most OEMs and Tier1 suppliers. The design and conformance of the product to functional safety standards is strongly intertwined with the product development cycle and needs to be carefully managed. The consideration for functional safety needs to begin right from the product’s concept phase through engineering and production and finally decommissioning. The application of the standard in a project can bring significant challenges especially to managers who are relatively new to the standard. This paper provides some guidelines on the key tasks involved in managing ISO26262 in projects and some ways to approach them. The paper is expected to help managers manage ISO26262 compliant projects. The paper also tries to come up with a metric that can be used for resource estimation for implementing ISO26262 in projects.
2017-03-28
Technical Paper
2017-01-0065
Bülent Sari, Hans-Christian Reuss
Abstract Safety is becoming more and more important with the ever increasing level of safety related E/E Systems built into the cars. Increasing functionality of vehicle systems through electrification of power train and autonomous driving leads to complexity in designing system, hardware, software and safety architecture. The application of multicore processors in the automotive industry is becoming necessary because of the needs for more processing power, more memory and higher safety requirements. Therefore it is necessary to investigate the safety solutions particularly for Automotive Safety Integrity Level (ASIL-D) Systems. This brings additional challenges because of additional requirements of ISO 26262 for ASIL-D safety concepts. This paper presents an approach for model-based “dependent failure analysis” which is required from ISO 26262 for ASIL-D safety concepts with decomposition approach.
2017-03-28
Technical Paper
2017-01-0632
Chen Yang, Haiyuan Cheng, Zizhu fan, Jiandong Yin, Yuan Shen
Abstract In recent years, more attention has been focused on environment pollution and energy source issues. As a result, increasingly stringent fuel consumption and emission legislations have been implemented all over the world. For automakers, enhancing engine’s efficiency as a must contributes to lower vehicle fuel consumption. To reach this goal, Geely auto started the development of a 3-cylinder 1.0L turbocharged direct injection (TGDI) gasoline engine to achieve a challenging fuel economy target while maintaining fun-to-drive and NVH performance. Demanding development targets for performance (specific torque 205Nm/L and specific power 100kW/L) and excellent part-load BSFC were defined, which lead to a major challenge for the design of engine systems, especially for combustion system.
2017-03-28
Journal Article
2017-01-0642
Richard Osborne, Trevor Downes, Simon O'Brien, Ken Pendlebury, Mark Christie
Abstract The Magma engine concept is characterised by a high compression ratio, central injector combustion system employed in a downsized direct-injection gasoline engine. An advanced boosting system and Miller cycle intake-valve closing strategies are used to control combustion knock while maintaining specific performance. A key feature of the Magma concept is the use of high CR without compromise to mainstream full-load performance levels. This paper focuses on development of the Magma combustion system using a single-cylinder engine, including valve event, air motion and injection strategies. Key findings are that Early Intake Valve Closing (EIVC) is effective both in mitigating knock and improving fuel consumption. A Net Indicated Mean Effective Pressure (NIMEP) equivalent to 23.6 bar Brake Mean Effective Pressure (BMEP) on a multi-cylinder engine has been achieved with a geometric compression ratio of 13:1.
2017-03-28
Technical Paper
2017-01-0650
Xinyu Li, Xinyu Ge, Ying Wang
Abstract The automotive industry is dramatically changing. Many automotive Original Equipment Manufacturers (OEMs) proposed new prototype models or concept vehicles to promote a green vehicle image. Non-traditional players bring many latest technologies in the Information Technology (IT) industry to the automotive industry. Typical vehicle’s characteristics became wider compared to those of vehicles a decade ago, and they include not only a driving range, mileage per gallon and acceleration rating, but also many features adopted in the IT industry, such as usability, connectivity, vehicle software upgrade capability and backward compatibility. Consumers expect the latest technology features in vehicles as they enjoy in using digital applications in laptops and mobile phones. These features create a huge challenge for a design of a new vehicle, especially for a human-machine-interface (HMI) system.
2017-03-28
Journal Article
2017-01-0651
Yaodong Hu, Siyuan Feng, Changsheng Yao, Wenbo Shao, Lubing Xu, Xieyuan Zhang, Li Lin, Jinyu Zhang, Fuyuan Yang, Rusheng Yan
Abstract This paper conducts an investigation on the operating cycle of Bus No. 306, which is equipped with wireless charging system, in Changsha, Hunan Province, China. The wireless charging system and electric buses are manufactured by ZTE Corporation (Zhongxing Telecommunication Equipment Corporation) and BYD Company Limited, respectively. In this paper, the operating cycle is quantified and modeled based on experimental data. The real-time bus route and SOC (state of charge) during daytime operation are recorded with the help of GPS (global position system) and BMS (battery management system). The wireless charging process is tested with a power analyzer and its charging efficiency is compared with a plug-in system. Besides, the radiation level while charging is also taken into consideration. Currently, the buses are designed to operate in daytime and get charged at night.
2017-03-28
Technical Paper
2017-01-0455
Harshad Hatekar, Baskar Anthonysamy, V. Saishanker, Lakshmi Pavuluri, Gurdeep Singh Pahwa
Abstract Structural elastomer components like bushes, engine mounts are required to meet stringent and contrasting requirements of being soft for better NVH and also be durable at different loading conditions and different road conditions. Silent block bushes are such components where the loading in radial direction of bushes are high to ensure the durability of bushes at high loads, but has to be soft on torsion to ensure good NVH. These requirements present with unique challenge to optimize the leaf spring bush design, stiffness and material characteristics of the rubber. Traditionally, bushes with varying degree of stiffness are selected, manufactured and tested on vehicle and the best one is chosen depending on the requirements. However, this approach is costly, time consuming and iterative. In this study, the stiffness targets required for the bush were analysed using static and dynamic load cases using virtual simulation (MSC.ADAMS).
2017-03-28
Journal Article
2017-01-0551
Alessandro D'Adamo, Sebastiano Breda, Salvatore Iaccarino, Fabio Berni, Stefano Fontanesi, Barbara Zardin, Massimo Borghi, Adrian Irimescu, Simona Merola
Abstract Engine knock is one of the most limiting factors for modern Spark-Ignition (SI) engines to achieve high efficiency targets. The stochastic nature of knock in SI units hinders the predictive capability of RANS knock models, which are based on ensemble averaged quantities. To this aim, a knock model grounded in statistics was recently developed in the RANS formalism. The model is able to infer a presumed log-normal distribution of knocking cycles from a single RANS simulation by means of transport equations for variances and turbulence-derived probability density functions (PDFs) for physical quantities. As a main advantage, the model is able to estimate the earliest knock severity experienced when moving the operating condition into the knocking regime.
2017-03-28
Technical Paper
2017-01-0202
Zhigang Wei, Raghuram Mandapati, Ranjith Nayaki, Jason Hamilton
Life testing or test-to-failure method and binomial testing method are the two most commonly used methods in product validation and reliability demonstration. The two-parameter Weibull distribution function is often used in the life testing and almost exclusively used in the extended time testing, which can be considered as an accelerated testing method by appropriately extending the testing time but with significantly reduced testing samples. However, the fatigue data from a wide variety of sources indicate that the three-parameter Weibull distribution function with a threshold parameter at the left tail is more appropriate for fatigue life data with large sample sizes. The uncertainties introduced from the assumptions about the underlying probabilistic distribution would significantly affect the interpretation of the test data and the assessment of the performance of the accelerated binomial testing methods, therefore, the selection of a probabilistic model is critically important.
2017-03-28
Technical Paper
2017-01-0201
Tejas Janardan Sarang, Amar Phatak, Jay Bendkhale
Abstract In the recent years, the timeline of releasing a new vehicle has decreased drastically due to rapidly changing trends in the automotive industry. Therefore, it is very important to constantly optimize the development phases, starting from concept initiation to the final testing of production ready vehicle. The real world tests conducted on vehicles take huge amount of time, since these tests are carried out for large kilometers to periodically analyze tire wear, clutch wear and brake failure. Collecting large kilometers of CAN data is also tedious and time consuming due to various unwanted variables which add up during real world tests. In this paper, a technique known as Rescaled Range Analysis is adapted to abridge the collection of kilometers data from testing by nearly ten times. This analysis estimates a Hurst coefficient to correlate the entire data with its divided parts. The division factor of the entire data is very crucial for the analysis.
2017-03-28
Technical Paper
2017-01-0375
Ligong Pan, Seung Hyun Jung, Sushanth Ramavath, Mohamed El-Essawi, Randall Frank, Jiawei Qin, Ramarajan Ilankamban, Yuan Yao, Homa Torab, Yuzhao Song, Jim Alanoly
Abstract Over the past decades, Computer Aided Engineering (CAE) based assessment of vehicle durability, NVH (Noise, Vibration and Harshness) and crash performance has become very essential in vehicle development and verification process. CAE activity is often organized as different groups based on the specific attributes (durability, NVH and crash). Main reasons for this are the expertise required and the difference in the finite element software technologies (explicit vs implicit) used to perform and interpret various CAE analyses in each of the attributes. This leads to individual attribute team creating its own model of the vehicle and there is not much exchange of the CAE models between the attribute teams. Different model requirements for each attribute make model sharing challenging. However, CAE analyses for all attributes start with common CAD and follow the same sub-process in vehicle development cycle.
2017-03-28
Journal Article
2017-01-0404
Anatoliy Dubrovskiy, Sergei Aliukov, Sergei Dubrovskiy, Alexander Alyukov
Abstract Currently, a group of scientists consisting of six doctors of technical sciences, professors of South Ural State University (Chelyabinsk, Russia) has completed a cycle of scientific research for creation of adaptive suspensions of vehicles. We have developed design solutions of the suspensions. These solutions allow us to adjust the performance of the suspensions directly during movement of a vehicle, depending on road conditions - either in automatic mode or in manual mode. We have developed, researched, designed, manufactured, and tested experimentally the following main components of the adaptive suspensions of vehicles: 1) blocked adaptive dampers and 2) elastic elements with nonlinear characteristic and with improved performance.
2017-03-28
Technical Paper
2017-01-0348
Mani Shankar, I V N Sri Harsha, K V Sunil, Ramsai Ramachandran
Abstract In an automobile, road loads due to tire-road interaction are transferred to vehicle body through suspension. This makes suspension a critical component from the body durability perspective. During vehicle design and development, optimization of suspension parameters to suit ride and handling performance is a continuous and iterative process. These changes on suspension can affect vehicle body durability performance. This paper tries to establish a process to evaluate the effect of changes in suspension parameters on body durability, thus helping in understanding the impact of these changes. The process starts with virtual model building in Multi Body Dynamics software. The base line model is correlated with testing using fatigue at some critical locations on Body in White (BIW).
2017-03-28
Journal Article
2017-01-0622
Sury Janarthanam, Sarav Paramasivam, Patrick Maguire, James Gebbie, Douglas Hughes
Abstract Hybrid Electric Vehicles (HEV) utilize a High Voltage (HV) battery pack to improve fuel economy by maximizing the capture of vehicle kinetic energy for reuse. Consequently, these HV battery packs experience frequent and rapid charge-discharge cycles. The heat generated during these cycles must be managed effectively to maintain battery cell performance and cell life. The HV battery pack cooling system must keep the HV battery pack temperature below a design target value and maintain a uniform temperature across all of the cells in the HV battery pack. Herein, the authors discuss some of the design points of the air cooled HV battery packs in Ford Motor Company’s current model C-Max and Fusion HEVs. In these vehicles, the flow of battery cooling air was required to not only provide effective cooling of the battery cells, but to simultaneously cool a direct current high voltage to low voltage (DC-DC) converter module.
2017-03-28
Technical Paper
2017-01-0326
Samuel J. Tomlinson, Martin J D Fisher, Thomas Smith, Kevin Pascal
Abstract When sealing an application with a radial O-ring system design there is a balance that must be struck between O-ring function and the ease of assembly. If design parameters are not properly controlled or considered it is possible to design an O-ring seal that would require assembly insertion forces that exceed acceptable ergonomic practices from a manufacturing standpoint. If designs are released into production with these high insertion forces manufacturing operators will struggle to assemble parts, creating opportunity for potential operator injury due to repetitive strain or CTD. In this study several variables impacting O-ring system insertion forces were tested to quantify the effects. Results were analyzed to identify design controls that could be implemented from an early design phase to optimize both functionality and ease of assembly.
2017-03-28
Journal Article
2017-01-0325
Samer Abbas, John Joyce
Abstract Severity-mitigating mechanisms (typically software-based) detect failures in a system and perform functions in order to reduce the severities of failures. Various approaches to FMEA analysis of severity-mitigating mechanisms exist within the industry. Three are compared and contrasted. Each method is compared against its ability to capture the three fundamental failures of a system that has severity-mitigating mechanisms: 1 a failure occurs and mitigating action is taken,2 a failure occurs and mitigating action is not taken,3 no failure occurs but mitigating action is taken. One method is advocated over the others because it: uses existing FMEA formatting; addresses all three cases; supports consistent linkage between FMEAs in a hierarchy of systems with any number of layers.
2017-03-28
Journal Article
2017-01-0322
Samer Abbas, John Joyce
Abstract When analyzing the failure rate (or occurrence) of a system failure cause, the typical approach is to obtain an occurrence rating from the results of testing. However, in many cases, the occurrence of a system failure cause can be derived from a combination of occurrences of failure causes of the element (sub-system) failure mode coinciding with the system failure cause being assessed. This paper explores a few approaches for deriving occurrences from element FMEAs over a majority of cases before settling on a probabilistic approach that converts occurrences to worst-case failure rates to achieve the most fine-tuned combined occurrence rating. Finally, a “complex analysis” worksheet, where the logical combination of occurrences and failure rates is custom defined by the engineer, is introduced for handling special cases.
2017-03-28
Journal Article
2017-01-0271
Robert Jane, Gordon G. Parker, Wayne Weaver, Ronald Matthews, Denise Rizzo, Michael Cook
Abstract This paper considers optimal power management during the establishment of an expeditionary outpost using battery and vehicle assets for electrical generation. The first step in creating a new outpost is implementing the physical protection and barrier system. Afterwards, facilities that provide communications, fires, meals, and moral boosts are implemented that steadily increase the electrical load while dynamic events, such as patrols, can cause abrupt changes in the electrical load profile. Being able to create a fully functioning outpost within 72 hours is a typical objective where the electrical power generation starts with batteries, transitions to gasoline generators and is eventually replaced by diesel generators as the outpost matures.
2017-03-28
Technical Paper
2017-01-0278
John Kelly Villota Pismag, Hisham Alawneh, Cristian Adam, Samir A. Rawashdeh, Pramita Mitra, Yifan Chen, Gary Strumolo
Abstract The potential for Augmented Reality (AR) spans many domains. Among other applications, AR can improve the discovery and learning experience for users inspecting a particular item. This paper discusses the use of AR in the automotive context; particularly, on improving the user experience in a dealership show room. Visual augmentation, through a tablet computer or glasses allows users to take part in a self-guided tour in learning about the various features, details, and options associated with a vehicle. The same approach can be applied to other learning scenarios, such as training and maintenance assistance. We evaluated a set of AR Glasses and a general purpose tablet. A table-top showroom was developed demonstrating what the actual user experience would be like for a self-guided dealership tour using natural markers and three-dimensional content spatially registered to physical objects in the user’s field of view.
2017-03-28
Technical Paper
2017-01-0232
Nizar Khemri, Hao Ying, Joseph Supina, Fazal Syed
Abstract Realistic vehicle fuel economy studies require real-world vehicle driving behavior data along with various factors affecting the fuel consumption. Such studies require data with various vehicles usages for prolonged periods of time. A project dedicated to collecting such data is an enormous and costly undertaking. Alternatively, we propose to utilize two publicly available vehicle travel survey data sets. One is Puget Sound Travel Survey collected using GPS devices in 484 vehicles between 2004 and 2006. Over 750,000 trips were recorded with a 10-second time resolution. The data were obtained to study travel behavior changes in response to time-and-location-variable road tolling. The other is Atlanta Regional Commission Travel Survey conducted for a comprehensive study of the demographic and travel behavior characteristics of residents within the study area.
2017-03-28
Technical Paper
2017-01-0235
Qiuming Gong, Jimmy Kapadia
Abstract Plug-in hybrid electric vehicles (PHEV) have an EV mode driving range which can cover a portion of customer daily driving. This EV mode range affects the refuel frequency substantially compared with conventional vehicle. For a conventional vehicle, daily driving pattern, tank size and fuel economy are the factors affecting the refuel frequency. While for a PHEV, EV range is another factor would affect the results substantially. Traditional method of label range can’t represent real world driving range between fill-ups for PHEV well. How to accurately predict the PHEV refuel distance taking into account real world customer driving patterns and PHEV parameters become critical for PHEV system design and optimization. This paper presents real world big customer data based PHEV refuel distance estimation modeling. The target is to estimate PHEV refuel distance given several specific parameters such as EV range, hybrid mode fuel economy, tank size etc.
2017-03-28
Journal Article
2017-01-0236
Zhigang Wei, Kamran Nikbin
In the Big Data era, the capability in statistical and probabilistic data characterization, data pattern identification, data modeling and analysis is critical to understand the data, to find the trends in the data, and to make better use of the data. In this paper the fundamental probability concepts and several commonly used probabilistic distribution functions, such as the Weibull for spectrum events and the Pareto for extreme/rare events, are described first. An event quadrant is subsequently established based on the commonality/rarity and impact/effect of the probabilistic events. Level of measurement, which is the key for quantitative measurement of the data, is also discussed based on the framework of probability. The damage density function, which is a measure of the relative damage contribution of each constituent is proposed. The new measure demonstrates its capability in distinguishing between the extreme/rare events and the spectrum events.
2017-03-28
Journal Article
2017-01-0237
Jonas Biteus, Tony Lindgren
Abstract Maintenance planning of trucks at Scania have previously been done using static cyclic plans with fixed sets of maintenance tasks, determined by mileage, calendar time, and some data driven physical models. Flexible maintenance have improved the maintenance program with the addition of general data driven expert rules and the ability to move sub-sets of maintenance tasks between maintenance occasions. Meanwhile, successful modelling with machine learning on big data, automatic planning using constraint programming, and route optimization are hinting on the ability to achieve even higher fleet utilization by further improvements of the flexible maintenance. The maintenance program have therefore been partitioned into its smallest parts and formulated as individual constraint rules. The overall goal is to maximize the utilization of a fleet, i.e. maximize the ability to perform transport assignments, with respect to maintenance.
2017-03-28
Technical Paper
2017-01-0238
Velappan Shalini, Sridharan Krishnamurthy, Srinivasan Narasimhan
Abstract This study compares the model efficacy of Neural Network and Vector Auto Regression. Further it also analyses the impact of predictors controlling for total industry volume. Understanding both the methodologies has their distinctive advantages and disadvantages. Our empirical findings indicate that based on the characteristics of data such as non-stationary, non-linearity and non-normality paves the way for use of machine learning algorithm relative to econometrics technique. Our results suggest that data type and its characteristics are more important in determining the methodology than the methodology itself. In industry, econometrics methodologies are widely used due to their usage simplicity and its ability to explain the relationships in simple terms.
2017-03-28
Journal Article
2017-01-0241
Thiago B. Murari, Paulo Ungaretti, Marcelo A. Moret
Abstract Geometric Dimensioning and Tolerancing is used to describe the allowed feature variations regarding the product design. Tolerance specification is important in many stages of all phases on product development. The product development engineering need to define the symbols to use on the Feature Control Frame of every component. Since the component function has an increment on its complexity year over year, it is not trivial to define those symbols anymore. The determination of dimensional tolerance shall be preceded by careful specification of the types of tolerance and symbols that will be applied in controlled features. Poor tolerance specifications can increase the production cost, require late product changes or lead to legal issues.
2017-03-28
Journal Article
2017-01-0243
Zhenghui Sha, Veronica Saeger, Mingxian Wang, Yan Fu, Wei Chen
Abstract For achieving viable mass customization of products, product configuration is often performed that requires deep understanding on the impact of product features and feature combinations on customers’ purchasing behaviors. Existing literature has been traditionally focused on analyzing the impact of common customer demographics and engineering attributes with discrete choice modeling approaches. This paper aims to expand discrete choice modeling through the incorporation of optional product features, such as customers’ positive or negative comments and their satisfaction ratings of their purchased products, beyond those commonly used attributes. The paper utilizes vehicle as an example to highlight the range of optional features currently underutilized in existing models. First, data analysis techniques are used to identify areas of particular consumer interest in regards to vehicle selection.
2017-03-28
Journal Article
2017-01-0245
Kanna Akella, N. Venkatachalam, K. Gokul, Keunho Choi, Ramachandraprabhu Tyakal
Abstract Voice of customer is typically captured through multiple connect points like surveys, warranty claims, social media, and so on. Customer verbatim is collected through these connect points to encourage free expression of opinion by customers. Such verbatim data is generally of high value and is typically analyzed using Natural Language Processing (NLP) techniques for translating into influencing actions in manufacturing, customer service, marketing, and product development departments. One of the challenges in analyzing unstructured verbatim data is to map that data onto appropriate concern codes (CCCs), which are typically used in automotive firms for tracking quality and satisfaction metrics. These concern codes map to a hierarchy of function areas in the organization aimed at improving product, service and hence the customer’s overall experience.
2017-03-28
Journal Article
2017-01-0247
N. Khalid Ahmed, Jimmy Kapadia
Abstract Electrified vehicles including Battery Electric Vehicles (BEVs) and Plug-In Hybrid Vehicles (PHEVs) made by Ford Motor Company are fitted with a telematics modem to provide customers with the means to communicate with their vehicles and, at the same time, receive insight on their vehicle usage. These services are provided through the “MyFordMobile” website and phone applications, simultaneously collecting information from the vehicle for different event triggers. In this work, we study this data by using Big Data Methodologies including a Hadoop Database for storing data and HiveQL, Pig Latin and Python scripts to perform analytics. We present electrified vehicle customer behaviors including geographical distribution, trip distances, and daily distances and compare these to the Atlanta Regional Survey data. We discuss customer behaviors pertinent to electrified vehicles including charger types used, charging occurrence, charger plug-in times etc.
2017-03-28
Technical Paper
2017-01-0200
Hongwei Zhang, Liangjin Gui, Zijie Fan
Abstract Road test simulation on test rig is widely used in the automobile industry to shorten the development circles. However, there is still room for further improving the time cost of current road simulation test. This paper described a new method considering both the damage error and the runtime of the test on a multi-axial test rig. First, the fatigue editing technique is applied to cut the small load in road data to reduce the runtime initially. The edited road load data could be reproduced on a multi-axial test rig successfully. Second, the rainflow matrices of strains on different proving ground roads are established and transformed into damage matrices based on the S-N curve and Miner rules using a reduction method. A standard simulation test for vehicle reliability procedure is established according to the proving ground schedule as a target to be accelerated.
2017-03-28
Technical Paper
2017-01-0199
Harpreet Grewal, Anthony D'Amato, Kathleen Rossie
Abstract Designing a durability test for an automatic transmission that appropriately reflects customer usage during the lifetime of the vehicle is a formidable task; while the transmission and its components must survive severe usage, overdesigning components leads to unnecessary weight, increased fuel consumption and increased emissions. Damage to transmission components is a function of many parameters including customer driving habits and vehicle and transmission characteristics such as weight, powertrain calibration, and gear ratios. Additionally, in some cases durability tests are required to verify only a subset of the total parameter space, for example, verifying only component modifications. Lastly, the ideal durability test is designed to impose the worst case loading conditions for the maximum number of internal components, be as short as practicable to reduce testing time, with minimal variability between tests in order to optimize test equipment and personnel resources.
Viewing 121 to 150 of 10366