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Journal Article

Investigations on Spark and Corona Ignition of Oxymethylene Ether-1 and Dimethyl Carbonate Blends with Gasoline by High-Speed Evaluation of OH* Chemiluminescence

2018-03-01
Abstract Bio-fuels of the 2nd generation constitute a key approach to tackle both Greenhouse Gas (GHG) and air quality challenges associated with combustion emissions of the transport sector. Since these fuels are obtained of residual materials of the agricultural industry, well-to-tank CO2 emissions can be significantly lowered by a closed-cycle of formation and absorption of CO2. Furthermore, studies of bio-fuels have shown reduced formation of particulate matter on account of the fuels’ high oxygen content therefore addressing air quality issues. However, due to the high oxygen content and other physical parameters these fuels are expected to exhibit different ignition behaviour. Moreover, the question is whether there is a positive superimposition of the fuels ignition behaviour with the benefits of an alternative ignition system, such as a corona ignition.
Journal Article

Optimization of WEDM Cutting Parameters on Surface Roughness of 2379 Steel Using Taguchi Method

2018-04-07
Abstract Surface roughness is one of the important aspects in producing quality die. Wire Electrical Discharge Machine (WEDM) is commonly used in tool and die fabrication, since the die material is usually difficult to cut using traditional metal removal processes. Selection of optimal WEDM cutting parameters is crucial to obtain quality die finish. In this study, 2379 steel which equivalent to SKD 11 is selected as the die material. Four main WEDM cutting parameters, namely, pulse duration (A), pulse interval (B), servo voltage (C), ignition pulse current (D), were experimentally evaluated for both main cut and multiple trim cuts using Taguchi Method. Taguchi’s L9 orthogonal array is employed for experimental design and analysis of variance (ANOVA) was used in recognizing levels of significance of WEDM cutting parameters.
Journal Article

Carbon Fiber/Epoxy Mold with Embedded Carbon Fiber Resistor Heater - Case Study

2018-04-07
Abstract The paper presents a complete description of the design and manufacturing of a Carbon Fiber/epoxy mold with an embedded Carbon Fiber resistor heater, and the mold performances in terms of its surface temperature distribution and thermal deformations resulting from the heating. The mold was designed for manufacturing aileron skins from Vacuum Bag Only prepreg cured at 135°C. The glass transition temperature of the used resin-hardener system was about 175°C. To ensure homogenous temperature of the mold working surface in the course of curing, the Carbon Fiber heater was embedded in a layer of a highly heat-conductive cristobalite/epoxy composite, forming the core of the mold shell. Because the cristobalite/epoxy composite displayed much higher thermal expansion than CF/epoxy did, thermal stresses could arise due to this discrepancy in the course of heating.
Journal Article

LSPI Durability, a Study of LSPI over the Life of a Vehicle

2018-03-01
Abstract Increasingly stringent emissions standards and the related efforts to increase vehicle fuel economy have forced the development and implementation of many new technologies. In the light-duty, passenger vehicle segment, one key strategy has been downsized, down-sped, boosted engines. Gasoline direct injection, coupled with turbocharging, have allowed for a drastic reduction in engine size while maintaining or improving engine performance. However, obtaining more power from a smaller engine has produced some consequences. One major consequence is the uncontrolled combustion known as Low Speed Pre-Ignition (LSPI). LSPI and the high energy knocking event which frequently follows have been known to result in fractured pistons and catastrophic engine failure. The propensity at which LSPI occurs has been linked to engine oil formulation.
Journal Article

Parasitic Battery Drain Problems and AUTOSAR Acceptance Testing

2018-04-18
Abstract Battery Drain problems can occur in the vehicle due to improper network management between electronic control units (ECUs). Aim of this paper is to identify the factors that cause transmission and cease of transmission of a network management message of an ECU along with its application messages that controls the sleep/wake-up performance of other ECUs in the network. Strategy used here is, based on the root cause analysis of problems found in Display unit in vehicle environment, the functional CAN signals impacting sleep/wake-up behavior is re-mapped along with the state flow transition of AUTOSAR NM Algorithm. A re-defined test case design and simulation for vehicle model is created. Especially it focuses on validating the impact of functional CAN signals on DUT’s sleep/wake-up performance.
Journal Article

Analysis of Evaporative and Exhaust-Related On-Board Diagnostic (OBD) Readiness Monitors and DTCs Using I/M and Roadside Data

2018-03-01
Abstract Under contract to the EPA, Eastern Research Group analyzed light-duty vehicle OBD monitor readiness and diagnostic trouble codes (DTCs) using inspection and maintenance (I/M) data from four states. Results from roadside pullover emissions and OBD tests were also compared with same-vehicle I/M OBD results from one of the states. Analysis focused on the evaporative emissions control (evap) system, the catalytic converter (catalyst), the exhaust gas recirculation (EGR) system and the oxygen sensor and oxygen sensor heater (O2 system). Evap and catalyst monitors had similar overall readiness rates (90% to 95%), while the EGR and O2 systems had higher readiness rates (95% to 98%). Approximately 0.7% to 2.5% of inspection cycles with a “ready” evap monitor had at least one stored evap DTC, but DTC rates were under 1% for the catalyst and EGR systems, and under 1.1% for the O2 system, in the states with enforced OBD programs.
Journal Article

3D Scene Reconstruction with Sparse LiDAR Data and Monocular Image in Single Frame

2017-09-23
Abstract Real-time reconstruction of 3D environment attributed with semantic information is significant for a variety of applications, such as obstacle detection, traffic scene comprehension and autonomous navigation. The current approaches to achieve it are mainly using stereo vision, Structure from Motion (SfM) or mobile LiDAR sensors. Each of these approaches has its own limitation, stereo vision has high computational cost, SfM needs accurate calibration between a sequences of images, and the onboard LiDAR sensor can only provide sparse points without color information. This paper describes a novel method for traffic scene semantic segmentation by combining sparse LiDAR point cloud (e.g. from Velodyne scans), with monocular color image. The key novelty of the method is the semantic coupling of stereoscopic point cloud with color lattice from camera image labelled through a Convolutional Neural Network (CNN).
Journal Article

Obstacle Avoidance for Self-Driving Vehicle with Reinforcement Learning

2017-09-23
Abstract Obstacle avoidance is an important function in self-driving vehicle control. When the vehicle move from any arbitrary start positions to any target positions in environment, a proper path must avoid both static obstacles and moving obstacles of arbitrary shape. There are many possible scenarios, manually tackling all possible cases will likely yield a too simplistic policy. In this paper reinforcement learning is applied to the problem to form effective strategies. There are two major challenges that make self-driving vehicle different from other robotic tasks. Firstly, in order to control the vehicle precisely, the action space must be continuous which can’t be dealt with by traditional Q-learning. Secondly, self-driving vehicle must satisfy various constraints including vehicle dynamics constraints and traffic rules constraints. Three contributions are made in this paper.
Journal Article

Integrated Positioning Method for Intelligent Vehicle Based on GPS and UWB

2017-09-23
Abstract Knowledge of intelligent vehicle absolute position is a vital premise for the implementation of decision programming, kinematic and dynamics control. In order to achieve high accuracy positioning and reduce running cost as much as possible under all operating conditions, this paper proposed an integrated positioning method based on GPS and Ultra Wide Band(UWB) for intelligent vehicle’s navigation and position system. In this method, GPS and UWB are alternately active according to the confidence level of GPS signal. When the vehicle is traveling in a wide-open area and GPS signal is well received, the positioning results of Dead Reckoning system are corrected by the low frequency positioning output from GPS. During the correcting process, in order to realize the better fusion of measurement data, a simplified federal Kalman filter was designed by using indirect method.
Journal Article

Efficient Lane Detection Using Deep Lane Feature Extraction Method

2017-09-23
Abstract In this paper, an efficient lane detection using deep feature extraction method is proposed to achieve real-time lane detection in diverse road environment. The method contains three main stages: 1) pre-processing, 2) deep lane feature extraction and 3) lane fitting. In pre-processing stage, the inverse perspective mapping (IPM) is used to obtain a bird's eye view of the road image, and then an edge image is generated using the canny operator. In deep lane feature extraction stage, an advanced lane extraction method is proposed. Firstly, line segment detector (LSD) is applied to achieve the fast line segment detection in the IPM image. After that, a proposed adaptive lane clustering algorithm is employed to gather the adjacent line segments generated by the LSD method. Finally, a proposed local gray value maximum cascaded spatial correlation filter (GMSF) algorithm is used to extract the target lane lines among the multiple lines.
Journal Article

Personalized Controller Design for Electric Power Steering System Based on Driver Behavior

2017-09-23
Abstract Electric power steering (EPS) system is a kind of dynamic control system for vehicle steering, which can amplify the driver steering torque inputs to the vehicle to improve steering comfortable and performance, but the present EPS can’t cater to the driving habits of different people. In this paper, a personalized EPS controller is designed based on the driver behavior, which combines real-time driver behavior identification strategy with personalized assistance characteristic. Firstly, the driver behavior data acquisition system is designed and established, based on which, the input data of different kinds of drivers along with vehicle signals are collected under typical working conditions, then the identification of driver behavior online is realized using the BP neural network.
Journal Article

Optimal Electric Vehicle Design Tool Using Genetic Algorithms

2018-04-18
Abstract The proposed approach present the development of a computer tool that allows, in the first phase, the modeling of the electric vehicle power chain. This phase is based on a library developed under the Matlab-Simulink simulation environment. This library contains all the components of the power chain; it offers the selection of the desired configuration of each component. In the second phase, the tool solves the autonomy optimization problem. This problem is resolved by a program based on genetic algorithms. This program permits to optimize the configuration parameters maximizing the vehicle autonomy of the chosen chain. This tool is based on a graphical interface developed under the Matlab simulation environment.
Journal Article

Automated ASIL Allocation and Decomposition according to ISO 26262, Using the Example of Vehicle Electrical Systems for Automated Driving

2018-04-18
Abstract ISO 26262 needs to be considered when developing safety-relevant E/E systems within the automotive industry. One part of the development process according to ISO 26262 is the derivation of the safety requirements for component functions. Here, one attribute of the safety requirements is the Automotive Safety Integrity Level (ASIL). The ASIL at a component level can be determined using ASIL allocation and decomposition. Considering complex systems such as vehicle electrical systems, countless possibilities can be identified for how the ASILs at a component level can be assigned in line with safety goals. In terms of efficiency, manual assignment is not expedient. Therefore, an algorithm for automated assignment of the ASILs will be introduced which considers constraints based on a fault tree analysis. The function of the approach will be demonstrated using the example of a vehicle electrical system from an automated vehicle.
Journal Article

Experimental Study on the Internal Resistance and Heat Generation Characteristics of Lithium Ion Power Battery with NCM/C Material System

2018-04-18
Abstract Heat generation characteristics of lithium ion batteries are vital for both the optimization of the battery cells and thermal management system design of battery packs. Compared with other factors, internal resistance has great influence on the thermal behavior of Li-ion batteries. Focus on a 3 Ah pouch type battery cell with the NCM/C material system, this paper quantitatively evaluates the battery heat generation behavior using an Extended Volume-Accelerating Rate Calorimeter in combination with a battery cycler. Also, internal resistances of the battery cell are measured using both the hybrid pulse power characteristic (HPPC) and electro-chemical impedance spectroscopy (EIS) methods. Experimental results show that the overall internal resistance obtained by the EIS method is close to the ohmic resistance measured by the HPPC method. Heat generation power of the battery cell is small during discharge processes lower than 0.5 C-rate.
Journal Article

2-D CFAR Procedure of Multiple Target Detection for Automotive Radar

2017-09-23
Abstract In Advanced Driver Assistant System (ADAS), the automotive radar is used to detect targets or obstacles around the vehicle. The procedure of Constant False Alarm Rate (CFAR) plays an important role in adaptive targets detection in noise or clutter environment. But in practical applications, the noise or clutter power is absolutely unknown and varies over the change of range, time and angle. The well-known cell averaging (CA) CFAR detector has a good detection performance in homogeneous environment but suffers from masking effect in multi-target environment. The ordered statistic (OS) CFAR is more robust in multi-target environment but needs a high computation power. Therefore, in this paper, a new two-dimension CFAR procedure based on a combination of Generalized Order Statistic (GOS) and CA CFAR named GOS-CA CFAR is proposed. Besides, the Linear Frequency Modulation Continuous Wave (LFMCW) radar simulation system is built to produce a series of rapid chirp signals.
Journal Article

A Centrally Managed Identity-Anonymized CAN Communication System*

2018-05-16
Abstract Identity-Anonymized CAN (IA-CAN) protocol is a secure CAN protocol, which provides the sender authentication by inserting a secret sequence of anonymous IDs (A-IDs) shared among the communication nodes. To prevent malicious attacks from the IA-CAN protocol, a secure and robust system error recovery mechanism is required. This article presents a central management method of IA-CAN, named the IA-CAN with a global A-ID, where a gateway plays a central role in the session initiation and system error recovery. Each ECU self-diagnoses the system errors, and (if an error happens) it automatically resynchronizes its A-ID generation by acquiring the recovery information from the gateway. We prototype both a hardware version of an IA-CAN controller and a system for the IA-CAN with a global A-ID using the controller to verify our concept.
Journal Article

Anomaly-Based Intrusion Detection Using the Density Estimation of Reception Cycle Periods for In-Vehicle Networks

2018-05-16
Abstract The automotive industry intends to create new services that involve sharing vehicle control information via a wide area network. In modern vehicles, an in-vehicle network shares information between more than 70 electronic control units (ECUs) inside a vehicle while it is driven. However, such a complicated system configuration can result in security vulnerabilities. The possibility of cyber-attacks on vehicles via external services has been demonstrated in many research projects. As advances in vehicle systems (e.g., autonomous drive) progress, the number of vulnerabilities to be exploited by cyber-attacks will also increase. Therefore, future vehicles need security measures to detect unknown cyber-attacks. We propose anomaly-based intrusion detection to detect unknown cyber-attacks for the Control Area Network (CAN) protocol, which is popular as a communication protocol for in-vehicle networks.
Journal Article

Classification of Contact Forces in Human-Robot Collaborative Manufacturing Environments

2018-04-02
Abstract This paper presents a machine learning application of the force/torque sensor in a human-robot collaborative manufacturing scenario. The purpose is to simplify the programming for physical interactions between the human operators and industrial robots in a hybrid manufacturing cell which combines several robotic applications, such as parts manipulation, assembly, sealing and painting, etc. A multiclass classifier using Light Gradient Boosting Machine (LightGBM) is first introduced in a robotic application for discriminating five different contact states w.r.t. the force/torque data. A systematic approach to train machine-learning based classifiers is presented, thus opens a door for enabling LightGBM with robotic data process. The total task time is reduced largely because force transitions can be detected on-the-fly. Experiments on an ABB force sensor and an industrial robot demonstrate the feasibility of the proposed method.
Journal Article

Increased Thread Load Capability of Bolted Joints in Light Weight Design

2017-06-29
Abstract Within the scope of today’s product development in automotive engineering, the aim is to produce lighter and solid parts with higher capabilities. On the one hand lightweight materials such as aluminum or magnesium are used, but on the other hand, increased stresses on these components cause higher bolt forces in joining technology. Therefore screws with very high strength rise in importance. At the same time, users need reliable and effective design methods to develop new products at reasonable cost in short time. The bolted joints require a special structural design of the thread engagement in low-strength components. Hence an extension of existing dimensioning of the thread engagement for modern requirements is necessary. In the context of this contribution, this will be addressed in two ways: on one hand extreme situations (low strength nut components and high-strength fasteners) are considered.
Journal Article

Lightweight Carbon Composite Chassis for Engine Start Lithium Batteries

2018-03-07
Abstract The supersession of metallic alloys with lightweight, high-strength composites is popular in the aircraft industry. However, aviation electronic enclosures for large format batteries and high power conversion electronics are still primarily made of aluminum alloys. These aluminum enclosures have attractive properties regrading structural integrity for the heavy internal parts, electromagnetic interference (EMI) suppression, electrical bonding for the internal cells, and/or electronics and failure containment. This paper details a lightweight carbon fiber composite chassis developed at Meggitt Sensing Systems (MSS) Securaplane, with a copper metallic mesh co-cured onto the internal surfaces resulting in a 50% reduction in weight when compared to its aluminum counterpart. In addition to significant weight reduction, it provides equal or improved performance with respect to EMI, structural and flammability performance.
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