Browse Topic: Statistical analysis

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Statistical Analysis of Data Acquired from Propagating Flames in Gasoline Engines Using a Multiple Ion Probe2024-32-003504/18/2025
Multiple-ion-probe method consists of multiple ion probes placed on the combustion chamber wall, where each individual ion probe detects flame contact and records the time of contact. From the recorded data, it is also possible to indirectly visualize the inside of the combustion chamber, for example, as a motion animation of moving flame front. In this study, a thirty-two ion probes were used to record flames propagating in a two-stroke gasoline engine. The experiment recorded the combustion state in the engine for about 3 seconds under full load at about 6500 rpm, and about 300 cycles were recorded in one experiment. Twelve experiments were conducted under the same experimental conditions, and a total of 4,164 cycles of signal data were obtained in the twelve experiments. Two types of analysis were performed on this data: statistical analysis and machine learning analysis using a linear regression model. Statistical analysis calculated the average flame detection time and standard
Yatsufusa, Tomoaki, Okahira, Takehiro, Nagashige, Kohei
Analysis of Lane Departure Caused by Inadequate Motorcycle Driving Maneuvers Due to Road Alignment2024-32-003404/18/2025
There are many riders who drive motorcycles on winding mountain roads and caused single motorcycle traffic accidents on curved roads by lane departure. Driving a motorcycle requires subtle balancing and maneuvering. In this study, in order to clarify the influence of lane departure caused by inadequate driving maneuvers against road alignment, the authors analyzed the required curve initial operation and driving maneuvers in curves depending on the traveling speed using a kinematics simulation for motorcycle dynamics. In addition, it was analyzed how inadequate driving maneuvers for curved roads can easily cause lane departure. As a result, it shows that the steering maneuvers and the lean of motorcycle body during the curves are highly affected by the vehicle speed, and the required maneuvers increases rapidly with increasing speed. The inadequate maneuver in the curves, especially for the lean of motorcycle body and steering torque, even by 10%, may cause failure to follow the
Kuniyuki, Hiroshi, Takechi, So
Intelligent Courier Delivery Scheduling Based on XGBoost Feature Selection and Reinforcement Learning: A Case Study Using Chongqing Cainiao Express Data2025-01-717602/21/2025
This study tackles the issue of order delays in logistics using XGBoost for feature analysis and reinforcement learning for intelligent courier scheduling. Pickup order data from May 1 to October 31, 2023, in Chongqing is analyzed using spatio-temporal statistical methods. Key findings include that order placement peaks at 9:00 a.m., delays peak at 10:00 a.m., and the delay rate is 8.6%. A significant imbalance exists between the regional daily average of dispatchable couriers and order volumes.XGBoost is employed to predict order delays, revealing that pickup location is the most influential factor (27%), followed by courier pickup location (22%). These factors and their relationships are identified as key drivers of delays.To address these issues, a reinforcement learning-based courier scheduling optimization model is developed. The model defines courier location, current time, and pending orders as state variables and adopts an epsilon-greedy strategy for action selection
Wang, Manjun, Yu, Xinlian
Scientific Approach for Pickup Cargo Weight Reduction2024-26-019201/16/2024
Due to increasing competitiveness, the arrival of industry giants, product pricing, etc., the automobile market in India is becoming more dynamic to adopt the changes. Apart from this, the product needs to be competitive to capture market by lowering the benefit margin. After launch and gaining of mass volume of the market, the Value Analysis and Value Engineering (VAVE) helps in minimizing the design and development costs through removal of non-value adding processes and activities by understanding the product's value, functions, features, customer demand, quality, and Real-World Usage Pattern (RWUP) without affecting the performance and eventually help in increasing the profit margin of organization. In this study, the benchmarked based statistical Light Weight Index (LWI) technique is developed for the predicting the world in class optimum weight. For these four statistical Light weight Index numbers is derived based on the geometrical dimensions. This strategy is used for the
Patel, Mayank, Balasubramani, Sritharkumar, Pandurangan, Raman, Cornelio, Ronald, Senrayaperumal, Sakthivel, ved, Kapil, Mohan, Aravind
Application of Hybrid SEA in Vehicle NV Package Optimization2025-01-005005/05/2023
As India’s economy expands and road infrastructure improves, the number of car owners are expected to grow substantially in the coming years. This market potential has intensified competition among original equipment manufacturers (OEMs) to position their products with a focus on cost efficiency while delivering a premium user experience. Noise and Vibration (NV) performance is a critical differentiator in conveying a vehicle's premiumness, and as such, NV engineers must strategically balance the achievement of optimal acoustic performance with constraints on cost, mass, and development timelines. Traditionally, NV package optimization occurs at the prototype or advanced prototype stage, relying heavily on physical testing, which increases both cost and time to market. Furthermore, late-stage design changes amplify these challenges. To address these issues, this paper proposes the integration of Hybrid Statistical Energy Analysis (HSEA) into the early stages of vehicle development
Rai, Nitesh, Mehta, Makrand, Ravindran, Mugundaram
Evaluation of Automotive Closure Design for High Frequency Acoustics Performance2025-01-004905/05/2023
A good NVH environment in a vehicle plays an important role in attracting a large customer base in the automotive market. Hence, NVH has been given significant priority while considering automotive design. NVH performance is monitored using simulations early during the design phase and testing in later prototype stages in the automotive industry. Meeting NVH performance targets possesses a greater risk related to design modifications in addition to the cost and time associated with the development process. Hence, a more enhanced and matured design process involves Design Point Analysis (DPA), which is essentially a decision-making process in which analytical tools derived from basic sciences, mathematics, statistics, and engineering fundamentals are used to develop a product model that better fulfills the predefined requirement. This paper shows the systematic approach of conducting a Design Point Analysis-level NVH study to evaluate the acoustic performance of vehicle door systems in
Ranade, Amod A., Shirode, Satish, Miskin, Atul, Mahamuni, Ketan, Shinde, Rahul, GHAN, PRAVIN, Choudhury, Ashok
Methodology for Sound Quality Metric Development2025-01-007005/05/2023
Many individual technical descriptors exist to quantify and describe different kinds of acoustic phenomena. However, each only describes the technical aspects of a sound itself without considering any additional non-acoustic context. Human perception is greatly informed by this context. For example, humans have different expectations for the sound of an electric razor than they do for an internal combustion engine, despite both objects being able to be described by sound pressure level or a measure of roughness. No single technical descriptor alone works in all contexts as a gold standard that objectively determines whether a sound is “good.” Jury tests, however, are a great aid in gaining a measure of this context. When seeking to develop a meaningful quality index for the sounds of a device, it is often necessary to combine the perceptive information from the results of a jury test alongside one or more technical descriptors. The combination of perceptive data and technical
Thiede, Shane
Aspects to consider while defining acceptance criteria and validation target2022-01-007203/29/2022
Two major steps involved in SOTIF analysis are defining acceptance criteria and estimating the validation target. While acceptance criteria aids in determining if we have an acceptable residual risk corresponding to a hazardous behavior, the validation target specifies the amount of testing effort (in hours or representative miles) that is needed to ensure that the acceptance criteria are met. The existing approaches for defining acceptance criteria heavily rely on existing fatality databases or naturalistic driving study data sets. The criterion is selected based on average number of fatalities or crashes per mile or per an hour of operation. The validation target is calculated based on these acceptance criteria. However, are these values really reflecting the acceptable risk criteria and targets? According to statistics, for a given data set and a random sample derived from the dataset, only the mean of population of the data set and the sample can considered to be equal. In the case
Madala, Kaushik, Krishnamoorthy, Jayalekshmi, Avalos Gonzalez, Carlos, SHIVKUMAR, Abhishek, Solmaz, Mert
A fatigue life prediction method of rubber material for Automobile vibration isolator under road load spectrum2022-01-029103/29/2022
Automobile rubber isolator was subjected to random load cycle for a long time in the service process, and its main rubber material for vibration isolation was prone to fatigue failure. Since the traditional Miner damage theory overlooked the load randomness, it had a prediction error problem. In order to improve the prediction accuracy of rubber fatigue life, the traditional Miner damage theory was modified by random uncertainty theory to predict the rubber fatigue life under random load. Firstly, the rubber dumbbell-shaped test column, which was vulcanized from rubber materials commonly used in vibration isolators, was taken as the research object. The uniaxial fatigue test of rubber under different strain amplitudes and strain mean values was carried out. Then the fatigue characteristic curve of rubber with equivalent strain amplitude as the damage parameter was established. Secondly, the load spectrum of the rubber mount of an automobile powertrain was collected from different road
Zhu, Xijun
Assessment of the impact of vehicle emissions on air quality changes during COVID-19 lockdown in Bogota, Colombia.2022-01-070503/29/2022
The COVID-19 pandemic has forced governments to implement rigorous containment measures on reduction or cessation of human mobility, transportation and economic activities, to control the spread of the virus. This is considered as a unique opportunity to study the impact of local lockdowns periods, especially, on the vehicle emission levels, and urban air quality in cities with high pollution levels, such as Bogota, Colombia. The first case was confirmed in Colombia on March 6, 2020, since then to prevent its propagation, the government declared a national lockdown starting from March 20 until August 31, 2020. Therefore, this study attempted to analyse the air quality in Bogota by assessing the concentrations of the atmospheric pollutants NO₂, SO₂, O₃, CO, PM₂.₅ and PM₁₀ during the lockdown period and the corresponding concentrations levels during the same period in 2018 and 2019. The data for this pilot study was obtained from the ambient air quality monitoring stations of Bogota's
Pardo Amaya, Diego, Samuel, Stephen
Research on Vehicle State Segmentation and Failure Prediction Based on Big Data2022-01-025403/29/2022
Vehicle failure prediction technology is an important part of PHM technology, which is of great significance to the safety maintenance of vehicles and to improve driving safety. This article relies on the research group's production-university-research project, based on the vehicle operating data collected by the telematics system on-board terminal (T-box), and conducts research on the state of vehicle failure. First of all, this paper conducts statistical analysis on vehicle historical fault data from T-box, specifically performs preprocessing such as cleaning, integration, and protocol, divides the data set, and establishes an association matrix between fault categories and specific signal parameters that cause such faults. Three angles of time, frequency, and proximity are selected to construct a vehicle state subdivision system. In addition, the K-means algorithm is used to classify different vehicle categories from the perspective of vehicle value, and to establish labeling
Zheng, Lu
Sound Package Optimization of Passenger Bus Using Hybrid Statistical Energy Analysis2021-26-026809/22/2021
Increasing Demands for high fuel efficiency requires imperative light weighting of automotive structure, but this adversely affects the NVH performance since transfer path of noise sources like engine, road, wind to vehicle interior through the panels weakens. Also increasing customer centric approach drives the urge to provide world-class comfort that is cost-effective too. Sound Packaging helps us to optimize these transfer paths through the panel, and can effectively complement efforts of Testing Team, by reducing the redundant iterations required to conclude to most effective trims to be put on. Statistical Energy Analysis Based Simulations is employed for carrying out these iterations at the Virtual Validation Gateway itself. Baseline Vehicle is fully modeled as per the criterion required by inherent SEA theory and simulated within frequency range of 200Hz-10KHz. Trims application areas are identified and layered Trims are applied at these locations to compare its effectiveness
Bhangale, Rajesh, SOUNDATTE, Nitin, shinde, Nikhil, Chavan, Pruthviraj
Systematic Approach for Optimizing Tailgate Stoppers and their Location to Prevent Squeak and Rattle2021-26-028509/22/2021
Tailgate stoppers play vital role in exerting pre-load on the tailgate latch mechanism and also restrict the relative motion of the tailgate against vehicle Body in White (BIW). These stoppers act as dampeners and reduce the transmissibility of vibrations thereby reduce the risk of Squeaks & Rattles (S&R) noises. These noises from tailgate are most annoying to the rear passengers in the vehicle and are recurring in nature. S & R risk simulations reduce cost by eliminating most of the design changes that are required in the physical prototype at the later stages of product development cycle and save time. The risk evaluation in the simulations is based on the relative displacement at the interfaces of two components. These interfaces are represented by Evaluation Lines (E-Lines) which are nothing but a series of nodes at the interface locations. The tailgate stoppers are modeled using a spring element with stiffness calculated from force deflection experiments. The variations due to the
Choudhury, Shibayan Roy, Wayal, Abhay, Gosavi, Santosh, Mullapudi, Dattatreyudu
Study of the Effects of Active Noise Cancellation on Music Playback2021-01-101608/31/2021
Technology for automotive active noise cancellation (ANC) such as HARMAN’s Engine Order Cancellation (EOC) system help reduce in-cabin noise levels using a set of error microphones and the vehicle’s built-in audio system to generate anti-noise signals. A major benefit of these systems is that significant reduction in unwanted noise levels in the 20 - 400 Hz range can be achieved without the addition of extra noise control material. However, in the instances where the frequencies of anti-noise signals and music signals overlap, a degradation in the overall music reproduction quality is possible. In this paper, we study the effects of EOC on music playback by applying signal processing and statistical methods to objectively measure degradation in audio content when EOC is active. This study is carried out using production EOC software in a simulation environment. The simulation models the cabin acoustic response from measured vehicles and uses recordings of vehicle noise and music as
Basu, Sattwik, Tackett, Jeffrey, Trumpy, David, Walt, Adam, Adari, Santosh
Human Perception of Seat Vibration Quality Pilot Study2021-01-106808/31/2021
Driving comfort and automotive product quality are strongly associated with the vibration that is transmitted to the occupants of a vehicle at the points of contact to the human body, including the seat, steering wheel, and pedals. Of these three contact locations, the seats have the most general importance, as all occupants of a vehicle experience seat vibration. Particularly relevant to driving comfort is the way in which vehicle occupants perceive seat vibration, which may be different than expected considering sensor measured vibration levels. Much of the interest in seat vibration has been focused on internal combustion engine powertrain vibration, especially idle vibration. However, electrification of vehicles changes the focus from low frequency idle vibration to higher frequency vibration sources. In this pilot study, the equal comfort curves for seat vibration were physically measured, which quantified perceived vibration amplitude as a function of amplitude and frequency with
Bastiaan, Jennifer, Green, Edward, Rengarajan, Revathi
A Novel Dissipative Acoustic Material2021-01-112808/31/2021
Due to modern trends in the automotive industry, such as vehicle electrification, light-weighting, reduced NVH (Noise, Vibration and Harshness) packaging space, etc., it is desirable to have a low profile and light-weight acoustic material with multi-functionality. If one single layer of a thin acoustic material can provide comparable absorption and transmission loss to a multilayer treatment, it will benefit the industry by saving weight, packaging space and system cost. Acoustic absorption and sound transmission loss performance of a new dissipative material at reduced weight and thickness is introduced in this paper. The acoustic performance of the material was evaluated by using random incidence absorption and transmission loss as well as in-vehicle experiment. Further potential applications for this material have been identified using the Statistical Energy Analysis (SEA) method with panel leakage considered.
Yoo, Taewook, Gerdes, Ronald, Lee, Seungkyu, Shi, Tongyang
Object Tracking Comparison for Automated Vehicles Using MathWorks Toolsets2021-01-011004/06/2021
Object trackers are a tool to achieve accurate object state estimation over time. Due to their complexity, a framework to experiment with different variations of trackers and their subcomponents is desired. This drove the authors research and experimentation with object tracking using MathWorks toolsets. In this paper, three object trackers - Point Target Tracker (PTT), Gamma Gaussian Inverse Wishart Probability Hypothesis Density (GGIW-PHD), and Gaussian Mixture Probability Hypothesis Density (GM-PHD) - are compared in simulation for track statistics and object/track accuracy. The results show that a rectangular GM-PHD multi object tracker outperforms the other trackers. A follow up is shown using real-world data and the process used to get the sensor data into the appropriate MathWorks format. The impact of COVID-19 prevented the collection of ground truth data so the real-world data cannot be compared using the same metrics. For this reason, the simulation portion of this paper will
Bassett, Alex, Cicotte, David, Currier, Patrick
Variability Analysis of FMVSS-121 Air Brake Systems: 60-mi/hr Service Brake System Performance Data for Truck Tractors2020-01-164010/05/2020
In support of the Federal Motor Carrier Safety Administration’s (FMCSA’s) ongoing interest in connected and automated commercial vehicles, this report summarizes analyses conducted to quantify variability in stopping distance tests conducted on commercial truck tractors. The data used were retrieved from tests performed under the controlled conditions specified for FMVSS-121 air brake system compliance testing. The report explores factors affecting the variability of the service brake stopping distance as defined by 49 CFR 571.121, S5.3.1 Stopping Distance—trucks and buses stopping distance. Variables examined in this analysis include brake type, weight, wheelbase, and tractor antilock braking system (ABS). This analysis uses existing test data collected between 2010 and 2019. Several of the examined parameters affected both tractor stopping distance and stopping distance variability. First, the average stopping distance for disc/disc brakes was shorter than either drum/drum or disc
Lascurain, Mary Beth, Franzese, Oscar, Siekmann, Adam
Powertrain Design Optimization for a Range-Extended Electric Pickup and Delivery Truck02-13-03-001410/02/2020
The ongoing electrification and data-intelligence trends in logistics industries enable efficient powertrain design and operation. In this work, the commercial package delivery vehicle powertrain design space is revisited with a specific combination of optimization and control techniques that promise accurate results with relatively fast computational time. The specific application that is explored here is a Class 6 pickup and delivery truck. A statistical learning approach is used to refine the search for the most optimal designs. Five hybrid powertrain architectures, namely, two-speed e-axle, three-speed and four-speed automatic transmission (AT) with electric motor (EM), direct-drive, and dual-motor options are explored, and a set of Pareto-optimal designs are found for a specific driving mission that represents the variations in a hypothetical operational scenario. The modeling and optimization processes are performed on the MATLAB™-Simulink platform. A cross-architecture
Anil, Vijay Sankar, Zhao, Tong, Zhao, Mingjie, Villani, Manfredi, Ahmed, Qadeer, Rizzoni, Giorgio
Powertrain Design Optimization for a Range-Extended Electric Pickup and Delivery Truck02-13-03-0014-TEST-REC10/02/2020
The ongoing electrification and data-intelligence trends in logistics industries enable efficient powertrain design and operation. In this work, the commercial package delivery vehicle powertrain design space is revisited with a specific combination of optimization and control techniques that promise accurate results with relatively fast computational time. The specific application that is explored here is a Class 6 pickup and delivery truck. A statistical learning approach is used to refine the search for the most optimal designs. Five hybrid powertrain architectures, namely, two-speed e-axle, three-speed and four-speed automatic transmission (AT) with electric motor (EM), direct-drive, and dual-motor options are explored, and a set of Pareto-optimal designs are found for a specific driving mission that represents the variations in a hypothetical operational scenario. The modeling and optimization processes are performed on the MATLAB™-Simulink platform. A cross-architecture
Anil, Vijay Sankar, Zhao, Tong, Zhao, Mingjie, Villani, Manfredi, Ahmed, Qadeer, Rizzoni, Giorgio
Influence of Nozzle Geometry Parameters on the Propagation of Fuel Spray Investigated with Linear and Non-Linear Regression Models2020-01-211409/15/2020
The nozzle geometry of fuel injectors has a strong influence on turbulences and pressure gradients within the nozzle flow. The flow situation at the nozzle outlet determines the spray propagation into the ambient atmosphere. This spray penetration is critical for gasoline direct injection (GDI) systems. When the spray penetration is too high, it can cause wall and cylinder impingement, which increases particle emissions drastically. However, prediction of fuel spray propagation in dependency of nozzle hole geometry is difficult due to the large difference in scale between the nozzle flow and the spray development. Because of this, spray measurements with varying nozzle geometry parameters and statistical evaluation of these datasets are useful for the future development of fuel injectors. In this study, shadowgraphy measurements of real-size single-hole glass nozzles are presented. The nozzles cover a wide range of geometry parameters relevant to a GDI system. The total penetration
Conrad, Chris, Wensing, Michael
Using Statistical Energy Analysis to Optimize Sound Package for Realistic Load Cases2020-01-152506/03/2020
The statistical energy analysis (SEA) is widely used to support the development of the sound package of cars. This paper will present a model prepared to investigate the sound package of the new Audi A3 and its correlation against measurements. Special care was given during the creation of the model on the representation of the structure to able the analysis of structure borne energy flow on top of the classical airborne analysis usually done with SEA. The sound package is also detailed in the model to allow further optimization and analysis of its performance. Two real life load cases will be presented to validate the model with measurements. First, the dominating powertrain and second, a case with dominating rolling noise. An analysis of the contribution of the different source components and a way to diagnose the weak paths of the vehicle will be presented. The focus of this investigation is the application of optimally adjusted treatment.
Venor, Joseph, Caillet, Arnaud, März, Christian, Martin, Simon, Fatmi, Oussama, Glavac, Matej
Research on Tracking Algorithm for Forward Target-Vehicle Using Millimeter-Wave Radar2020-01-070204/14/2020
In order to solve such problems that the millimeter-wave radar is of large computation, poor robustness and low precision of the target tracking algorithm, this paper presents an algorithmic framework for millimeter-wave radar tracking of target-vehicles. The target measurement information outside the millimeter- wave radar detection range is eliminated by the data plausibility judgment method based on the millimeter-wave radar detection parameters. Target clustering is made using Manhattan distance, to eliminate clutter interference and cluster multiple target measurements into one. The data association is made by use of nearest neighbor to determine the correspondence between information received measured by the radar and the real target. The vehicle is the key detection target of the vehicle millimeter-wave radar during road driving. These target-vehicles generally have no vertical movement or small moving speed in the vertical direction, so only the movement of the target-vehicle
Song, Shiping, Wu, Jian, Yang, Yu, He, Rui, Chen, Xuesong, Li, Xin
Human-Driving Highway Overtake and Its Perceived Comfort: Correlational Study Using Data Fusion2020-01-103604/14/2020
As an era of autonomous driving approaches, it is necessary to translate handling comfort - currently a responsibility of human drivers - to a vehicle imbedded algorithm. Therefore, it is imperative to understand the relationship between perceived driving comfort and human driving behaviour. This paper develops a methodology able to generate the information necessary to study how this relationship is expressed in highway overtakes. To achieve this goal, the approach revolved around the implementation of sensor Data Fusion, by processing data from CAN, camera and LIDAR from experimental tests. A myriad of variables was available, requiring individuating the key-information and parameters for recognition, classification and understanding of the manoeuvres. The paper presents the methodology and the role each sensor plays, by expanding on three main steps: Data segregation and parameter selection; Manoeuvre detection and processing; Manoeuvre classification and database generation. It
Carello, Massimiliana, Ferraris, Alessandro, de Carvalho Pinheiro, Henrique, Cruz Stanke, Diego, Gabiati, Giovanni, Camuffo, Isabella, Grillo, Massimo
Defining Fundamental Vehicle Actions for the Development of Automated Driving Systems2020-01-071204/14/2020
Automated Driving Systems (ADSs) show great potential to improve our transport systems. Safety validation, before market launch, is challenging due to the large number of miles required to gather enough evidence for a proven in use argumentation. Hence there is ongoing research to find more effective ways of verifying and validating the safety of ADSs. It is crucial both for the design as well as the validation to have a good understanding of the environment of the ADS. A natural way of characterizing the external conditions is by modelling and analysing data from real traffic. Towards this end, we present a framework with the primary ultimate objective to completely model and quantify the statistically relevant actions that other vehicles conduct on motorways. Two categories of fundamental actions are identified by recognising that a vehicle can only move longitudinally and laterally. The fundamental actions are defined in detail to create a set that is collectively exhaustive and
Gyllenhammar, Magnus, Zandén, Carl, Törngren, Martin
Accident Statistical Distributions from NASS CDS - An Update2020-01-051804/14/2020
The National Automotive Sampling System (NASS) Crashworthiness Data System (CDS) contains an abundance of field crash data. As technology advances and the database continues to grow over the years, the statistical significance of the data increases and trends can be observed. The purpose of this paper is to provide a broad-based, up-to-date, reference resource with respect to commonly sought-after crash statistics. Charts include up-to-date crash distributions by Delta-V and impact direction with corresponding injury severity rates. Rollover data is also analyzed, as well as historical trends for injury severity, belt usage, air bag availability, and the availability of vehicle safety technology.
Yaek, Jennifer L., Brown, Thomas, Goertz, Alan
Benchmarking the Localization Accuracy of 2D SLAM Algorithms on Mobile Robotic Platforms2020-01-102104/14/2020
Simultaneous Localization and Mapping (SLAM) algorithms are extensively utilized within the field of autonomous navigation. In particular, numerous open-source Robot Operating System (ROS) based SLAM solutions, such as Gmapping, Hector, Cartographer etc., have simplified deployments in application. However, establishing the accuracy and precision of these ‘out-of-the-box’ SLAM algorithms is necessary for improving the accuracy and precision of further applications such as planning, navigation, controls. Existing benchmarking literature largely focused on validating SLAM algorithms based upon the quality of the generated maps. In this paper, however, we focus on examining the localization accuracy of existing 2-dimensional LiDAR based indoor SLAM algorithms. The fidelity of these implementations is compared against the OptiTrack motion capture system which is capable of tracking moving objects at sub-millimeter level precision. Finally, the error statistics for each of the algorithm was
Basu Thakur, Mugdha, Schmid, Matthias, Krovi, Venkat N
Research on the Test and Evaluation Method of Fuel Consumption Based on Chinese Light-Duty Test Cycle2020-01-036304/14/2020
Considering the defect of current test method and learning from the developing experience of other methods around the world, a method adopted China Light-duty Vehicle Test Cycle (CLTC) which is suitable for the real condition of Chinese road was put forword. Through comparing the test results of 20 vehicles with big data statistics, the results obtained by this method are close to those from customers and the difference between them is around 6%. Thus, the rationality of this method is proved. Furthermore, this method can evaluate the real fuel consumption of vehicle running on Chinese roads.
Wang, Yang, Hui, Chun, Liu, Yu
Recovering Color Images from Scattered LightTBMG-3547811/01/2019
Engineers at Duke University have developed a method for extracting a color image from a single exposure of light scattered through a mostly opaque material. The technique has applications in a wide range of fields from healthcare to astronomy.
The Right Stuff for Aging Electronics/Intermittence/No Fault Found2019-01-188909/16/2019
For those in the avionics repair and maintenance business, the acronyms NFF (No Fault Found), NTF (No Trouble Found), and CND (Cannot Duplicate) are, unfortunately, all too familiar terms. After several decades of frustration with this illusive phenomenon, it continues to consume an enormous amount of test and diagnostic effort and is the source of considerable cost and discomfort within the multi-level avionics repair model. There are undoubtedly many causes of NFF and all of them should be addressed. The question is: Where do you start and which solution will be the most beneficial? Our particular efforts have focused on the literal or statistical analysis of NFF, recognizing that if the system’s MTBF (Mean Time Between Failure) has decreased, or if the device's NFF rate has increased with age and deterioration, a physical fault is most likely present. However, if it isn’t found during conventional testing then it probably only fails intermittently. Similarly, having an intermittent
Knudsen, Hector I.
Simulation of Aircraft Assembly via ASRP Software2019-01-188709/16/2019
ASRP (Assembly Simulation of Riveting Process) software is a special tool for assembly process modelling for large scale airframe parts. On the base of variation simulation, ASRP provides a convenient way to analyze, verify and optimize the arrangement of temporary fasteners. During the assembly of airframe certain criteria on residual gap between parts must be fulfilled. The numerical approach implemented in ASRP allows to evaluate the quality of contact on every stage of assembly process and solve verification and optimization problems for temporary fastener patterns. The paper is devoted to description of several specialized approaches that combine statistical analysis of measured data and numerical simulation using high-performance computing for optimization of fastener patterns, calculation of forces in fasteners needed to close initial gaps, and identification of hazardous areas in junction regions via ASRP software.
Zaitseva, Nadezhda, Pogarskaia, Tatiana, Minevich, Olga, Shinder, Julia, Bonhomme, Elodie
Graphene Lid Extends Photoemission Electron Microscopy to LiquidsTBMG-3475307/01/2019
By capping liquids with graphene (an ultrathin sheet of pure carbon), researchers can easily image and analyze liquid interfaces and the surface of nanometer-scale objects immersed in liquids. In the imaging technique known as photoemission electron microscopy (PEEM), ultraviolet light or X-rays bombard a sample, stimulating the material to release electrons from a region at or just beneath its surface. Electric fields act as lenses, focusing the emitted electrons to create an image.
Uncertainty of the Ice Particles Median Mass Diameters Retrieved from the HAIC-HIWC Dataset: A Study of the Influence of the Mass Retrieval Method2019-01-198306/10/2019
In response to the ice crystal icing hazard identified twenty years ago, aviation industry, regulation authorities, and research centers joined forces into the HAIC-HIWC international collaboration launched in 2012. Two flight campaigns were conducted in the high ice water content areas of tropical mesoscale convective systems in order to characterize this environment conducive to ice crystal icing. Statistics on cloud microphysical properties, such as Ice Water Content (IWC) or Mass Median Diameter (MMD), derived from the dataset of in situ measurements are now being used to support icing certification rulemaking and anti-icing systems design (engine and air data probe) activities. This technical paper focuses on methodological aspects of the derivation of MMD. MMD are estimated from PSD and IWC using a multistep process in which the mass retrieval method is a critical step. Complementary to previous studies reporting on MMD values calculated from the HAIC-HIWC dataset, this paper
Coutris, Pierre, Schwarzenboeck, Alfons, Leroy, Delphine, Grandin, Alice, Dezitter, Fabien, Strapp, J. Walter
Ice Nucleation in the Presence of Electric Fields: An Experimental Study2019-01-202006/10/2019
In the present study, ice nucleation in sessile water drops during continuous cool down is studied experimentally under the impact of a constant electric field, to determine its influence on heterogeneous nucleation. The experimental setup enables simultaneous observation of multiple drops under well-defined conditions with and without an electric field and at temperatures down to -40 °C. A single experimental run contains 40 drops exposed to the same conditions. Drops with a well-defined size are produced employing a drop-on-demand drop generator. Based on multiple experimental runs using the same drops, the nucleation behavior is analyzed using statistical methods to determine the drop survival curves and nucleation site densities for varying conditions. Besides the influence of the electric field, the influence of different drop ensembles is investigated for a constant cooling rate of 5 K/min. A comparison of the experiments with and without an electric field is used to elaborate
Löwe, Jens-Michael, Schremb, Markus, Hinrichsen, Volker, Tropea, Cameron
Vibroacoustic Model’s Likelihood Computation Based on a Statistical Reduction of Random FRF Matrices2019-01-159306/05/2019
Improvement of vibroacoustic models prediction capabilities requires an adapted indicator to compare experimental measurements with the results of the computational model. When dealing with highly uncertain objects such as series production cars, a probabilistic approach is mandatory to be able to describe the dispersion of experimental results. Moreover, a probabilistic non-parametric model also account for modeling uncertainties and simplifications that are part of any engineering process. The proposed approach deals with Frequency Response Functions since FRFs are the common way to handle vibroacoustic models. When considering multiple input and output points configuration, FRFs are frequency dependent complex matrices. Since the probabilistic modeling is available in current vibroacoustic software, collections of random realizations of the FRF matrix can be computed from the existing FE model. The model’s likelihood naturally appears as the probability of a measured quantity to be
Gagliardini, Laurent, Soize, Christian, Reyes, Justin
Machine Learning Based Technology for Reducing Engine Starting Vibration of Hybrid Vehicles2019-01-145006/05/2019
Engine starting vibration of hybrid vehicle with Toyota hybrid system has variations even in the same vehicle, and a large vibration that occurs rarely may cause stress to the passengers. The contribution analysis based on the vibration theory and statistical analysis has been done, but the primary factor of the rare large vibration has not been clarified because the number of factors is enormous. From this background, we apply machine learning that can reproduce multivariate and complicated relationships to analysis of variation factors of engine starting vibration. Variations in magnitude of the exciting force such as motor torque for starting the engine and in-cylinder pressure of the engine and timing of these forces are considered as factors of the variations. In addition, there are also nonlinear factors such as backlash of gears as a factor of variations. For the variation factor analysis, it is difficult to measure the physical quantities mentioned above from experiments
Shimode, Kento, Ishizaki, Keisuke, Komada, Masashi
A Transient SEA Model for Transmission of Non-Stationary Wind Noise2019-01-147306/05/2019
Automakers have reported that passenger perception of vehicle interior wind noise is strongly correlated to the non-Gaussian and non-stationary character of the exterior aero-acoustic wind loading. Researchers in other domains have shown that leptokurtic non-Gaussian loading (Kurtosis κ>3) can be synthesized by non-stationary modulation of otherwise Gaussian random loading. This paper introduces a transient statistical energy analysis (SEA) model for the aero-vibro acoustic transmission of non-stationary wind noise which uses the same approach - a modulation of otherwise Gaussian random fluctuating pressure loading, in each one third octave band. The authors have previously shown that the non-stationary character of random wind loading can be measured in a wind tunnel or on the road with a suitable surface pressure microphone array. This paper reviews the formulation of a Transient SEA model and the predicted modulation frequency response functions for transmission of non-stationary
Bremner, Paul, Clifton, Scott, Todter, Chris
A Trajectory-Based Method for Scenario Analysis and Test Effort Reduction for Highly Automated Vehicle2019-01-013904/02/2019
Unlike the test of passive safety of traditional vehicles, highly automated vehicles (HAV) need more capabilities to be tested. Besides, there are more parameter combinations for the scenarios that need to be tested for each capability, resulting in a high time-consuming and costs for the autonomous vehicle tests. This paper proposes a method for scenario analysis and test effort reduction. Firstly, the trajectories of the vehicle under test (VUT) in the scenario are analyzed, and the trajectories which lead to the test mission failure are obtained. Based on the above trajectories, the threshold that lead to the test mission failure, or a combination of thresholds are analyzed. The above thresholds or a combination of thresholds values are defined as Scenario Character Parameter (SCP). The process of the analysis of the SCPs are related to the abilities of the HAV, but does not depend on the specific algorithm of the HAV. Therefore, through the above analysis of trajectories and SCPs
Qi, Yunlong, Luo, Yugong, Li, Keqiang, Kong, Wei, Wang, Yongsheng
Estimation of the Relative Roles of Belt-Wearing Rate, Crash Speed Change, and Several Occupant Variables in Frontal Impacts for Two Levels of Injury2019-01-121904/02/2019
Driver injury probabilities in real-world frontal crashes were statistically modeled to estimate the relative roles of five variables of topical interest. One variable pertained to behavior (belt-wearing rate), one pertained to crash circumstances (speed change), and three pertained to occupant demographics (sex, age, and body mass index). The attendant analysis was composed of two parts: (1) baseline statistical modeling to help recover the past, and (2) sensitivity analyses to help consider the future. In Part 1, risk functions were generated from statistical analysis of real-world data pertaining to 1998-2014 model-year light passenger cars/trucks in 11-1 o’clock, full-engagement frontal crashes documented in the National Automotive Sampling System (NASS, 1997-2014). The selected data yielded a weighted estimate of 1,269,178 crash-involved drivers. Those data were parsed for four subpopulations: two levels of belt use (properly-belted vs. unbelted) and two levels of driver injury
Laituri, Tony, Henry, Scott, Li, Guosong
Failure Prediction for Robot Reducers by Combining Two Machine Learning Methods2019-01-050804/02/2019
There are many production robots used at car manufacturing plants, and each of them is fitted with several reducers. A breakdown of one of these reducers may cause a huge loss due to the stoppage of all production lines. Therefore, condition-based maintenance is currently being used to predict failures by predetermined thresholds for average and standard deviations. However, this method can cause many false alarms or some false negatives. There are some ways of suppressing false alarms, such as detecting a change in the probability density function. However, when false alarms are suppressed using the probability density function in the operational range, some false negatives may occur, leading to a breakdown of a reducer and huge loss. A false negative is caused by overlooking an anomaly with slight changes and it is difficult to detect using only the probability density function. Therefore, we developed the Difference Signum Method (DSM) to detect an anomaly with slight changes by
Tanaka, Yasuhiro, Takagi, Toru
Risk Assessment of Fuel Property Variability Using Quasi-Random Sampling/Design of Experiments Methodologies2019-01-138703/19/2019
Increases in on-board heat generation in modern military aircraft have led to a reliance on thermal management techniques using fuel as a primary heat sink. However, recent studies have found that fuel properties, such as specific heat, can vary greatly between batches, affecting the amount of heat delivered to the fuel. With modern aircraft systems utilizing the majority of available heat sink capacity, an improved understanding of the effects of fuel property variability on overall system response is important. One way to determine whether property variability inside a thermal system causes failure is to perform uncertainty analyses on fuel thermophysical properties and compare results to a risk assessment metric. A sensitivity analysis can be performed on any properties that cause inherent system variability to determine which properties contribute the most significant impact. For the current study, a quasi-random sampling based uncertainty analysis was combined with a surrogate
McCarthy, Kevin, Jackson, Galen R.
A Method for System Identification in the Presence of Unknown Harmonic Excitations Based on Operational Modal Analysis2019-01-500701/23/2019
Operational modal analysis techniques classically have been developed based on the assumption that the input to the system is a stationary white noise. While, in many practical cases, the systems are excited by combination of white noise and colored noises (harmonic excitations). Consequently, in conditions where non-white noises are present, the existing OMA methods cannot completely distinguish between the system poles and the induced poles due to colored noises. In order to overcome this weakness of OMA methods, some researches have been conducted in the field. In this paper, a new method is proposed for identifying the modal parameters of the system under the unknown colored noises, based on the Power Spectral Density Transmissibility (PSDT) function. In this work, the proposed methodology is established upon applying the auxiliary force, which can re-excite the system under operational conditions. In order to identify the modal parameters through the PSDT function, an appropriate
Khodaygan, S.
Characterization of GDI PM during Vehicle Start-Stop Operation2019-01-005001/15/2019
As the fuel economy regulations increase in stringency, many manufacturers are implementing start-stop operation to enhance vehicle fuel economy. During start-stop operation, the engine shuts off when the vehicle is stationary for more than a few seconds. When the brake is released by the driver, the engine restarts. Depending on traffic conditions, start-stop operation can result in fuel savings from a few percent to close to 10%. Gasoline direct injection (GDI) engines are also increasingly available on light-duty vehicles. While GDI engines offer fuel economy advantages over port fuel injected (PFI) engines, they also tend to have higher PM emissions, particularly during start-up transients. Thus, there is interest in evaluating the effect of start-stop operation on PM emissions. In this study, a 2.5L GDI vehicle was operated over the FTP75 drive cycle. Runs containing cold starts (FTP-75 cycle Phases 1 & 2) and multiple runs containing hot starts (FTP-75 cycle Phases 3 & 4) were
Storey, John M., Moses-DeBusk, Melanie, Huff, Shean, Thomas, John, Eibl, Mary, Li, Faustine
Evaluation of Atomization Timing and Optimal Water Content for an Emulsified Fuel Droplet2018-32-005910/30/2018
The emulsified fuel means that it is mixed fuel with water and stabilized by surfactant. The difference of boiling points between fuel and water occur the secondary atomization during heating process. The water content strongly influence on the timing of secondary atomization(1). However, the water content is determined empirically. It means that it is the doubtful of compatibility fuel and a combustor. Then the emulsified fuel is needed the engineering evaluation (not empirically) to take advantage of sure secondary atomization. This research focuses on the timing and behavior of secondary atomization with an emulsified fuel droplet and the proposal of engineering evaluation. Moreover, we propose novel test method without the suspending wire to avoid heat transfer from itself. Namely, the novel point is heating process by floating in the high temperature silicone oil. This method can reveal the atomization behavior of a fuel droplet similar to the spray combustion. The measured data
Aoki, Junichi, Tanaka, Junya
Probabilistic Approach to Predict Abnormal Combustion in Spark Ignition Engines2018-01-172209/10/2018
This study presents a computational framework to predict the outcome of combustion process based on a given RANS initial condition by performing statistical analysis of Sankaran number, Sa, and ignition regime theory proposed by Im et al. [1]. A criterion to predict strong auto-ignition/detonation a priori is used in this study, which is based on Sankaran-Zeldovich criterion. In the context of detonation, Sa is normalized by a sound speed, and is spatially calculated for the bulk mixture with temperature and equivalence ratio stratifications. The initial conditions from previous pre-ignition simulations were used to compute the spatial Sa distribution followed by the statistics of Sa including the mean Sa, the probability density function (PDF) of Sa, and the detonation probability, PD. Sa is found to be decreased and detonation probability increased significantly with increase of temperature. The statistic mean Sa calculated for the entire computational domain and the predicted Sa
Mubarak Ali, Mohammed Jaasim, Luong, Minh Bau, Sow, Aliou, Hernandez Perez, Francisco, Im, Hong
Statistical Study of Ring Geometry Effect on Piston Ring/Liner Tribology Using Classical Design of Experiment2018-01-165809/10/2018
An instantaneous piston ring/liner friction model has been presented to estimate the minimum oil film thickness and power loss contributed by piston rings under hydrodynamic lubrication. The model is based on lubrication theory considering lubricant viscosity variation with respect to temperature. A numerical scheme is developed to solve Reynolds and load equilibrium equations simultaneously to obtain the cyclic variation of oil film thickness and power loss. The model considers the ring profile geometry, the ring mechanical properties and their effects on the tribological performance of piston ring. The relevant trends and relations between parameters are considered with relatively simple approach to compute the minimum oil film thickness and mechanical power loss. Besides, Design of Experiment (DOE) technique and ANOVA analysis are employed to determine the effect of influential parameters such as ring width, ring crown height, ring elastic properties and ring end gap on the average
Delprete, Cristiana, Razavykia, Abbas
Feature-Based Response Classification in Nonlinear Structural Design Simulations10-02-03-001207/24/2018
An applied system design analysis approach for automated processing and classification of simulated structural responses is presented. Deterministic and nonlinear dynamics are studied under ideal loading and low noise conditions to determine fundamental system properties, how they vary and possibly interact. Using powerful computer resources, large amounts of simulated raw data can be produced in a short period of time. Efficient tools for data processing and interpretation are then needed, but existing ones often require much manual preparation and direct human judgement. Thus, there is a need to develop techniques that help to treat more virtual prototype variants and efficiently extract useful information from them. For this, time signals are evaluated by methods commonly used within structural dynamics and statistical learning. A multi-level multi-frequency stimulus function is constructed and simulated response signals are combined into frequency domain functions. These are
Andersson, Niclas, Rinaldo, Raoul
Influence of the Friction Coefficient in Self-Pierce Riveting Simulations: A Statistical Analysis05-11-02-001305/08/2018
In this work, optimal modeling parameters for self-pierce riveting (SPR) were determined using a factorial design of experiments (DOE). In particular, we show statistically how each of the calibrating parameters used in modeling the SPR process through nonlinear finite element modeling can drastically change the geometry of the joint. The results of this study indicate that the degree of interlock, which is a key feature of a sound joint, is largely influenced by the friction between the die and bottom sheet as well as the friction between the rivet and top sheet. Furthermore, this numerical study also helped elucidate the role of friction in SPR and sheds light on how coatings with diverse friction coefficients can affect material deformation and ultimately structural integrity of the joint.
Moraes, J.F.C., Jordon, J.B.
Calculating System Failure Rates Using Field Return Data. Application of SAE-J3083 for Functional Safety and Beyond2018-01-107404/03/2018
In early design activities (typically before the hardware is built), a reliability prediction is often required for the electronic components and systems in order to assess their future reliability and in many cases to meet customer specifications. These specifications may include the allocated reliability for a particular electronic unit and in the cases of functional safety products to meet the ASIL (Automotive Safety and Integrity Level) requirement specified by the functional safety standard ISO 26262. The standard allows for the use of “statistics based on field returns or tests” as a valid alternative to the handbook-based reliability prediction. This paper presents a newly developed SAE-J3083 standard “Reliability Prediction for Automotive Electronics Based on Field Return Data”, which covers the types of the required data, ways to collect it, and the methodology of how to process this data to calculate the failure rates and meet the expected safety goals.
Kleyner, Andre, Hodgson, Keith
Target Correlation and Allocation Using Reliability Metrics to Validate Design Effectiveness of Improved Sample2018-01-079004/03/2018
All automotive components, systems and vehicles undergo stringent validation protocol standards. Nevertheless, there are certain factors which cannot be captured during validation phase and result in field failures. With multiple players prying for market share in the automotive industry, timely resolution of field failures can go a long way in retaining customer base. In such a scenario, when customer’s tolerance on field failures is very limited, failures need severe attention and must be captured as early as possible to cut down warranty expenses. This project aims at creating a methodology to simulate field failures and validate improved design. The reliability parameters such as β (Shape Factor), η (Scale factor), Reliability and life are estimated and the values are compared between field and lab conditions. Life estimated in field conditions (Failure data base) and lab are correlated using Reliability techniques and target is established for validating improved sample. Cross
Yogeeswaran, Ramarajan, Subramaniom, Shiju
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