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Technical Paper

Analysis of a Coupling System of Aircraft Environmental Control and Fuel Tank Inerting Based on Membrane Separation

2019-09-16
2019-01-1895
This paper raises a coupling system of aircraft environmental control and fuel tank inerting based on membrane separation. The system applies a membrane dehumidifier to replace water vapor removal unit of heat regenerator, condenser and water separator, which is widely used in conventional aircraft environmental control system (ECS) nowadays. Water vapor can travel across the membrane wall under its pressure difference without phase change, so the dehumidification process consumes no cooling capacity as traditional ECS and the cooling capacity of the new system increases. This paper first compares the thermodynamic properties of ECS based on membrane dehumidification and the traditional ECS based on condensation. The results show that the membrane dehumidification system has larger cooling capacity and lighter weight. For a given cooling capacity requirement, the membrane dehumidification system can use less bleed air since the enthalpy of the outlet air is lower.
Technical Paper

Aero-Engine Inlet Vane Structure Optimization for Anti-Icing with Hot Air Film Using Neural Network and Genetic Algorithm

2019-06-10
2019-01-2021
An improved anti-icing design with film heating ejection slot and cover for the inlet part of aero-engine was brought out, which combines the interior jet impingement with the exterior hot air film heating and shows promising application for those parts manufactured with composite materials. A hybrid method based on the combination of the Back Propagation Neural Network (BPNN) and Genetic Algorithm (GA) is developed to optimize the anti-icing design for a typical aero-engine inlet vane in two dimensions. The optimization aims to maximize the heating performance of the hot air film, which is assessed by the heating effectiveness. The film-heating ejection angle and the cover opening angle are the two geometric variables to be optimized. Numerical model was established and validated to generate training and testing samples for BPNN, which was used to predict the objective function and find the optimal design variables in conjunction with the GA.
Technical Paper

Structural-Acoustic Modeling and Optimization of a Submarine Pressure Hull

2019-06-05
2019-01-1498
The Energy Finite Element Analysis (EFEA) has been validated in the past through comparison with test data for computing the structural vibration and the radiated noise for Naval systems in the mid to high frequency range. A main benefit of the method is that it enables fast computations for full scale models. This capability is exploited by using the EFEA for a submarine pressure hull design optimization study. A generic but representative pressure hull is considered. Design variables associated with the dimensions of the king frames, the thickness of the pressure hull in the vicinity of the excitation (the latter is considered to be applied on the king frames of the machinery room), the dimensions of the frames, and the damping applied on the hull are adjusted during the optimization process in order to minimize the radiated noise in the frequency range from 1,000Hz to 16,000Hz.
Technical Paper

Survey of Automotive Privacy Regulations and Privacy-Related Attacks

2019-04-02
2019-01-0479
Privacy has been a rising concern. The European Union has established a privacy standard called General Data Protection Regulation (GDPR) in May 2018. Furthermore, the Facebook-Cambridge Analytica data incident made headlines in March 2018. Data collection from vehicles by OEM platforms is increasingly popular and may offer OEMs new business models but it comes with the risk of privacy leakages. Vehicular sensor data shared with third-parties can lead to misuse of the requested data for other purposes than stated/intended. There exists a relevant regulation document introduced by the Alliance of Automobile Manufacturers (“Auto Alliance”), which classifies the vehicular sensors used for data collection as covered and non-sensitive parameters.
Technical Paper

Research on the Driving Stability Control System of the Dual-Motor Drive Electric Vehicle

2019-04-02
2019-01-0436
In order to improve the steering stability of the dual-motor drive electric vehicle, Taking the yaw rate and the sideslip angle as the control variables, Using the improved two degree of freedom linear dynamic model and seven degree of freedom nonlinear vehicle dynamics model, The hierarchical structure is used to establish the dual-motor drive electric vehicle steering stability control strategy which consist of the upper direct yaw moment decision-making layer based on the sliding mode controller and the lower additional yaw moment distribution layer based on the optimization theory. The Matlab/Simulink-Carsim joint simulation platform was built. The control strategy proposed in this paper was simulated and verified under the snake test condition and double-line shift test condition.
Technical Paper

Vehicle Velocity Prediction and Energy Management Strategy Part 1: Deterministic and Stochastic Vehicle Velocity Prediction Using Machine Learning

2019-04-02
2019-01-1051
There is a pressing need to develop accurate and robust approaches for predicting vehicle speed to enhance fuel economy/energy efficiency, drivability and safety of automotive vehicles. This paper details outcomes of research into various methods for the prediction of vehicle velocity. The focus is on short-term predictions over 1 to 10 second prediction horizon. Such short-term predictions can be integrated into a hybrid electric vehicle energy management strategy and have the potential to improve HEV energy efficiency. Several deterministic and stochastic models are considered in this paper for prediction of future vehicle velocity. Deterministic models include an Auto-Regressive Moving Average (ARMA) model, a Nonlinear Auto-Regressive with eXternal input (NARX) shallow neural network and a Long Short-Term Memory (LSTM) deep neural network. Stochastic models include a Markov Chain (MC) model and a Conditional Linear Gaussian (CLG) model.
Technical Paper

A Methodology of Design for Fatigue Using an Accelerated Life Testing Approach with Saddlepoint Approximation

2019-04-02
2019-01-0159
We present an Accelerated Life Testing (ALT) methodology along with a design for fatigue approach, using Gaussian or non-Gaussian excitations. The accuracy of fatigue life prediction at nominal loading conditions is affected by model and material uncertainty. This uncertainty is reduced by performing tests at a higher loading level, resulting in a reduction in test duration. Based on the data obtained from experiments, we formulate an optimization problem to calculate the Maximum Likelihood Estimator (MLE) values of the uncertain model parameters. In our proposed ALT method, we lift all the assumptions on the type of life distribution or the stress-life relationship and we use Saddlepoint Approximation (SPA) method to calculate the fatigue life Probability Density Functions (PDFs).
Technical Paper

Vehicle Velocity Prediction and Energy Management Strategy Part 2: Integration of Machine Learning Vehicle Velocity Prediction with Optimal Energy Management to Improve Fuel Economy

2019-04-02
2019-01-1212
An optimal energy management strategy (Optimal EMS) can yield significant fuel economy (FE) improvements without vehicle velocity modifications. Thus it has been the subject of numerous research studies spanning decades. One of the most challenging aspects of an Optimal EMS is that FE gains are typically directly related to high fidelity predictions of future vehicle operation. In this research, a comprehensive dataset is exploited which includes internal data (CAN bus) and external data (radar information and V2V) gathered over numerous instances of two highway drive cycles and one urban/highway mixed drive cycle. This dataset is used to derive a prediction model for vehicle velocity for the next 10 seconds, which is a range which has a significant FE improvement potential. This achieved 10 second vehicle velocity prediction is then compared to perfect full drive cycle prediction, perfect 10 second prediction.
Technical Paper

A Software Tool for Injury Analysis of Blast and Crash Data

2019-04-02
2019-01-1225
In recent years the U.S. Army Tank-Automotive Research, Development, and Engineering Center (TARDEC) has been investigating the survivability and injury mechanisms of underbody blast and crash, and their effects on personnel, with the use of Anthropomorphic Test Devices (ATD), or crash test dummies. Injury Assessment Reference Values (IARV) for crash have been researched for decades, and the US Army Research Laboratory (ARL), some years ago, also developed IARVs for underbody blast for the Hybrid III 50th percentile ATD. More recently, TARDEC extended these IARVs for the 5th and 95th percentile. With the advent of TARDEC’s Occupant Protection Laboratory large amounts of data were accumulated, which brought an interest in automating the analysis, and so a software tool was developed. The interactive in-house written software, called ICalc, allows the user to open test data files acquired from blast testing, drop tower testing, and crash testing.
Technical Paper

Evaluation of Different ADAS Features in Vehicle Displays

2019-04-02
2019-01-1006
The current study presents the results of an experiment on driver performance including reaction time, eye-attention movement, mental workload, and subjective preference when different features of Advanced Driver Assistance Systems (ADAS) warnings (Forward Collision Warning) are displayed, including different locations (HDD (Head-Down Display) vs HUD (Head-Up Display)), modality of warning (text vs. pictographic), and a new concept that provides a dynamic bird’s eye view for warnings. Sixteen drivers drove a high-fidelity driving simulator integrated with display prototypes of the features. Independent variables were displayed as modality, location, and dynamics of the warnings with driver performance as the dependent variable including driver reaction time to the warning, EORT (Eyes-Off-Road-Time) during braking after receiving the warning, workload and subject preference.
Technical Paper

Evaluation of Low Mileage GPF Filtration and Regeneration as Influenced by Soot Morphology, Reactivity, and GPF Loading

2019-04-02
2019-01-0975
As European and Chinese tailpipe emission regulations for gasoline light-duty vehicles impose particulate number limits, automotive manufacturers have begun equipping some vehicles with a gasoline particulate filter (GPF). Increased understanding of how soot morphology, reactivity, and GPF loading affect GPF filtration and regeneration characteristics is necessary for advancing GPF performance. This study investigates the impacts of morphology, reactivity, and filter soot loading on GPF filtration and regeneration. Soot morphology and reactivity are varied through changes in fuel injection parameters, known to affect soot formation conditions. Changes in morphology and reactivity are confirmed through analysis using a transmission electron microscope (TEM) and a thermogravimetric analyzer (TGA) respectively.
Journal Article

Analyzing and Preventing Data Privacy Leakage in Connected Vehicle Services

2019-04-02
2019-01-0478
The rapid development of connected and automated vehicle technologies together with cloud-based mobility services are revolutionizing the transportation industry. As a result, huge amounts of data are being generated, collected, and utilized, hence providing tremendous business opportunities. However, this big data poses serious challenges mainly in terms of data privacy. The risks of privacy leakage are amplified by the information sharing nature of emerging mobility services and the recent advances in data analytics. In this paper, we provide an overview of the connected vehicle landscape and point out potential privacy threats. We demonstrate two of the risks, namely additional individual information inference and user de-anonymization, through concrete attack designs. We also propose corresponding countermeasures to defend against such privacy attacks. We evaluate the feasibility of such attacks and our defense strategies using real world vehicular data.
Technical Paper

A Real-Time Traffic Light Detection Algorithm Based on Adaptive Edge Information

2018-08-07
2018-01-1620
Traffic light detection has great significant for unmanned vehicle and driver assistance system. Meanwhile many detection algorithms have been proposed in recent years. However, traffic light detection still cannot achieve a desirable result under complicated illumination, bad weather condition and complex road environment. Besides, it is difficult to detect multi-scale traffic lights by embedded devices simultaneously, especially the tiny ones. To solve these problems, this paper presents a robust vision-based method to detect traffic light, the method contains main two stages: the region proposal stage and the traffic light recognition stage. On region proposal stage, we utilize lane detection to remove partial background from the original image. Then, we apply adaptive canny edge detection to highlight region proposal in Cr color channel, where red or green color proposals can be separated easily. Finally, extract the enlarged traffic light RoI (Region of Interest) to classify.
Technical Paper

Embedding CNN-Based Fast Obstacles Detection for Autonomous Vehicles

2018-08-07
2018-01-1622
Forward obstacles detection is one of the key tasks in the perception system of autonomous vehicles. The perception solution differs from the sensors and the detection algorithm, and the vision-based approaches are always popular. In this paper, an embedding fast obstacles detection algorithm is proposed to efficiently detect forward diverse obstacles from the image stream captured by the monocular camera. Specifically, our algorithm contains three components. The first component is an object detection method using convolution neural networks (CNN) for single image. We design a detection network based on shallow residual network, and an adaptive object aspect ratio setting method for training dataset is proposed to improve the accuracy of detection. The second component is a multiple object tracking method based on correlation filter for the adjacent images.
Technical Paper

Simulation of Flow Control Devices in Support of Vehicle Drag Reduction

2018-04-03
2018-01-0713
Flow control devices can enable vehicle drag reduction through the mitigation of separation and by modifying local and global flow features. Passive vortex generators (VG) are an example of a flow control device that can be designed to re-energize weakly-attached boundary layers to prevent or minimize separation regions that can increase drag. Accurate numerical simulation of such devices and their impact on the vehicle aerodynamics is an important step towards enabling automated drag reduction and shape optimization for a wide range of vehicle concepts. This work demonstrates the use of an open-source computational-fluid dynamics (CFD) framework to enable an accurate and robust evaluation of passive vortex generators in support of vehicle drag reduction. Specifically, the backlight separation of the Ahmed body with a 25° slant is used to evaluate different turbulence models including variants of the RANS, DES, and LES formulations.
Technical Paper

Infrared Borescopic Evaluation of High-Energy and Long-Duration Ignition Systems for Lean/Dilute Combustion in Heavy-Duty Natural-Gas Engines

2018-04-03
2018-01-1149
Natural gas (NG) is attractive for heavy-duty (HD) engines for reasons of cost stability, emissions, and fuel security. NG cannot be reliably compression-ignited, but conventional gasoline ignition systems are not optimized for NG and are challenged to ignite mixtures that are lean or diluted with exhaust-gas recirculation (EGR). NG ignition is particularly challenging in large-bore engines, where completing combustion in the available time is more difficult. Using two high-speed infrared (IR) cameras with borescopic access to one cylinder of an HD NG engine, the effect of ignition system on the early flame-kernel development and cycle-to-cycle variability (CCV) was investigated. Imaging in the IR yielded strong signals from water emission lines, which located the flame front and burned-gas regions and obviated image intensifiers. A 9.7-liter, six-cylinder engine was modified to enable exhaust-gas recirculation and to provide optical access.
Technical Paper

Cooling Parasitic Considerations for Optimal Sizing and Power Split Strategy for Military Robot Powered by Hydrogen Fuel Cells

2018-04-03
2018-01-0798
Military vehicles are typically armored, hence the open surface area for heat rejection is limited. Hence, the cooling parasitic load for a given heat rejection can be considerably higher and important to consider upfront in the system design. Since PEMFCs operate at low temp, the required cooling flow is larger to account for the smaller delta temperature to the air. This research aims to address the combined problem of optimal sizing of the lithium ion battery and PEM Fuel Cell stack along with development of the scalable power split strategy for small a PackBot robot. We will apply scalable physics-based models of the fuel cell stack and balance of plant that includes a realistic and scalable parasitic load from cooling integrated with existing scalable models of the lithium ion battery. This model allows the combined optimization that captures the dominant trends relevant to component sizing and system performance.
Technical Paper

Fuel Economy Analysis of Periodic Cruise Control Strategies for Power-Split HEVs at Medium and Low Speed

2018-04-03
2018-01-0871
Hybridization of vehicles is considered as the most promising technology for automakers and researchers, facing the challenge of optimizing both the fuel economy and emission of the road transport. Extensive studies have been performed on power-split hybrid electric vehicles (PS-HEVs). Despite of the fact that their excellent fuel economy performance in city driving conditions has been witnessed, a bottle neck for further improving the fuel economy of PS-HEVs has been encountered due to the inherent engine-generator-motor power circulation of the power-split system under medium-low speed cruising scenarios. Due to the special mechanical constraints of the power-split device (PSD), the conventional periodic cruising strategy like Pulse and Glide cannot be applied to PS-HEVs directly.
Technical Paper

Real-Time Automatic Test of AEB with Brake System in the Loop

2018-04-03
2018-01-1450
The limitation of drivers' attention and perception may bring collision dangers, Autonomous Emergency Braking (AEB) can help drivers to avoid the potential collisions through active braking. Since the positive effect of it, motor corporations have begun to equip their vehicles with the system, and regulatory agencies in various countries have introduced test standards. At this stage, the actuator of AEB usually adopts Electronic Stability Program (ESP), but it poor performance of continuous working period and active pressure built-up for all wheels limits its implements. Electromechanical brake booster can realize power assisted brake without relying on the vacuum source and a variety of specific power curves. Moreover it can achieve the active braking with a rapid response, which make it can fulfill requirements of automotive electric and intelligent development.
Technical Paper

Study of Effects of Thermal Insulation Techniques on a Catalytic Converter for Reducing Cold Start Emissions

2018-04-03
2018-01-1431
Previous work done at the University of Michigan shows the capability of the vacuum-insulated catalytic converter (VICC) to retain heat during soak and the resulting benefits in reducing cold start emissions. This paper provides an improved version of the design which overcomes some of the shortcomings of the previous model and further improves the applicability and benefits of VICC. Also, newer materials have been evaluated and their effects on heat retention and emissions have studied using the 1-D after treatment model. Cold start emissions constitute around 60% to 80% of all the hydrocarbon and CO emissions in present day vehicles. The time taken to achieve the catalyst light-off temperature in a three-way catalytic converter significantly affects the emissions and fuel efficiency. The current work aims at developing a method to retain heat in catalytic converter, thus avoiding the need for light-off and reducing cold start emissions effectively.
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