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A major barrier, preventing RFSSW from use by manufacturers, is the long cycle time that has been historically associated with making a weld. In order for RFSSW to become a readily implementable welding solution, cycle times must be reduced to an acceptable level, similar to that of well developed, competing spot joining processes. In the present work, an investigation of the RFSSW process is conducted to evaluate factors that have traditionally prevented the process from achieving fast cycle times. Within this investigation, the relationship between cycle time and joint quality is explored, as is the meaning and measurement of cycle time in the RFSSW process. Claims and general sentiment found in prior literature are challenged regarding the potential for high-speed RFSSW joints to be made.

For one of the advanced sensing technologies for the autonomous driving, we have been working on the new vision system. It focuses on detecting the small object at far ranges. It enables to detour a vehicle by avoiding small object. This system is based on the high-resolution mono-camera with narrow FOV and the algorithms for object-detection and lane-detection. Since we have already proposed the system for the traffic cones, we proceed to a new algorithm for an unknown object with arbitrary shape. It can detect the object and estimate its range by using the information on the lane even though the shape and dimension of the object are unknown. Here the system architecture and how the algorithm to detect the object and estimate its range are described. The algorithm is at first validated by a computer-generated image. And then it is applied to real images. For the cones, the accuracy was +/- 4 [m] for the ranges between 50 and 150 [m].

With the rapid development of artificial intelligence, the autonomous vehicles (AV) have attracted considerable attention in the automotive industry. However, different factors negatively impact the adoption of the AVs, delaying their successful commercialization. Accretion of atmospheric icing, especially wet snow, on AV sensors causes blockage on their lenses, making them prone to lose their sight, in turn, increasing potential chances of accidents. In this study, two different designs are proposed in order to prevent snow accretion on the lenses of AVs via air flow across the lens surface. In both designs, lenses made of plain glass and superhydrophobic coated glass surfaces are tested. While some researchers have shown promise of water repellency on superhydrophobic surfaces, more snow accretion is observed on the superhydrophobic surfaces, when compared to the plain glass lenses.

With the increase of car ownership and the complex and crowded parking environment, it is difficult for drivers to complete the parking operation quickly and accurately, which may cause traffic accidents such as vehicle collisions and road jams because of poor parking skills. The emergence of an automatic parking system can help drivers park safely and reduce the occurrence of safety accidents. In this paper, the neural network identifier on the control method of an adaptive integral derivative of a neural network is proposed for an automatic parallel parking system with front-wheel steering is studied by using MATLAB/Simulink environment, and the simulation is carried out. Firstly, according to vehicle parameters and obstacle avoidance constraints, the minimum parking space, and parking starting position are calculated. Meanwhile, the path planning of parallel parking spaces is carried out by quintic polynomial.

This paper is focused on modeling and control of a heterogeneous traffic network consisting of human-driven and autonomous vehicles. In this paper, we consider the autonomous vehicles as controllable agents while the human-driven vehicles are considered as rational but non-controllable agents. The fundamental traffic diagram for such heterogeneous traffic networks is developed wherein the capacity and jam density of the road is determined as a function of the penetration rate and the headways of autonomous and human-driven vehicles. A cost function is defined to maximize the average flow-rate within the network. Considering the rationality of the human-driven vehicles as well as the controllability of the autonomous vehicles, a series of constraints are imposed on the cost function. We employed an extremum seeking control approach to determine the optimal flow-rate between the sub-networks so that the mobility of the network improves.

Hyundai Motor Company mass-produced the world's first fingerprint entry and start system. This paper is a study on the evaluation method to develop and verify the optimal fingerprint authentication algorithm for vehicle usage conditions. Currently, fingerprint sensors and algorithms in the IT industry have been developed for the electronic devices, and are not suitable for the harsh environment of the vehicle and the vehicle life cycle for more than 10 years. In order to optimize the fingerprint sensor and algorithm for the vehicle, this study consisted of 3way test methods. As a result, the fingerprint system could be optimized for the vehicle and the recognition rate and security could be optimized according to the sensor authentication level. Through this study, the door handle recognition rate was improved by 25% and the start button recognition rate by 10%, and the fingerprint entry and start system was mass-produced with security level that satisfies the immobilizer regulations.

This paper proposes a platform to conduct rapid development, simulation and test of autonomous driving vehicles. By combining the advantages of rapid prototyping and software development, the proposed platform could automatically generate codes and download them into domain controllers, therefore the efficiency of development process of the core functions of ADAS can be largely improved. The platform is made up of scene simulation, vehicle dynamics simulation software, a rapid prototyping system, a chassis drive-by-wire control and road-load simulation system. Meaningful tasks including key algorithm development, MIL simulations, domain controller based HIL tests and the development of drive-by-wire systems can all be accomplished by the platform.

Operation of an autonomous vehicle (AV) carries risk if it acts on inaccurate information about itself or the environment. The perception system is responsible for interpreting the world and providing the results to the path planning and other decision systems. The perception system performance is a result of the operating state of the sensors, e.g. is a sensor in fault or being adversely affected by the weather or environmental conditions, and approach to sensor measurement interpretation. We propose a trailing horizon switched system observer that minimizes the difference between reference tracking values developed from sensor fusion performed at an upper level and the values from a potentially faulty sensor based upon the convex combination of different sensor observation model outputs; the sensor observations models are associated with different sensor operating errors.

Developing of innovative technologies and materials to meet the requirements of environmental legislation on vehicle emissions has paramount importance for researchers and industries. Therefore, improvement of engine efficiency and fuel saving of modern internal combustion engines (ICEs) is one of the key factors, together with the weight reduction. Thermoplastic composite materials might be one of the alternative materials to be employed to produce engine components to achieve these goals as their properties can be engineered to meet application requirements. Unidirectional carbon fiber reinforced PolyEtherImide (CF/PEI) thermoplastic composite is used to design engine connecting rod and wrist pin, applying commercial engine data and geometries. The current study is focused on some elements of the crank mechanism as the weight reduction of these elements affects not only the curb weight of the engine but the overall structure.

Fatigue testing is a specialized form of mechanical testing that is performed by applying cyclic loading to a coupon or structure. Two common forms of fatigue testing are load controlled high cycle and strain controlled low cycle fatigue. Some strain measurement device, such as extensometers, strain gage, that are often used as a feedback sensor on strain controlled fatigue test. However, in applications where strain controlled fatigue testing could face some extreme conditions as well as high temperature and unusual sizing which requires the strain measurement to be nondestructive and full field. While digital image correlation (DIC), an advanced optical measurement technique, has a decent solution on challenges of fatigue testing measurement. The problem is how to turn DIC from a measurement system to a feedback controller unit. Due to the developments in camera and computation techniques, the sequential process can now be performed as a parallel process.

There are a large number of uncertainties in engineering design, and the accumulated uncertainties will enlarge the overall failure probability of the structure system. Therefore, structural design considering uncertainties has good guiding significance for improving the reliability of engineering structures. To address this issue, the dynamic-static structural topology optimization is established and reliability-based topology optimization with decoupling format is conducted in this study. The design point which satisfying the constraint of the target reliability indicator is obtained according to the reliability indicators of the first-order reliability method, and the uncertain design variables are modified into a deterministic variable according to the sensitivity information.

Rollover crashes are complex events that generate motions in all six degrees of freedom (6DOF). Directly quantifying the angular rotations from video can be difficult and vehicle orientation as a function of time is often not reported for staged rollover crashes. Our goal was to evaluate the ability of using a match-moving technique and consumer-grade video cameras to quantify the roll, pitch and yaw angles and angular velocities of a rollover crash. We staged a steer-induced rollover of an SUV at 106 km/h. The vehicle was fitted with tri-axial accelerometers and angular rate sensors, and five consumer-grade video cameras (2 on tripods, 2 on drones, 1 handheld, ~30 fps) captured the event. Roll, pitch and yaw angles were determined from the video using specialized software.

The Hybrid Cellular Automaton (HCA) algorithm is a generative design approach used to synthesize conceptual designs of crashworthy vehicle structures with a target mass. Given the target mass, the HCA algorithm generates a structure with a specific acceleration-displacement profile. The extended HCA (xHCA) algorithm is a generalization of the HCA algorithm that allows to tailor the crash response of the vehicle structure. Given a target mass, the xHCA algorithm has the ability to generate structures with different acceleration-displacement profiles and target a desired crash response. In order to accomplish this task, the xHCA algorithm includes two main components: a set of meta-parameters (in addition target mass) and surrogate model technique that finds the optimal meta-parameter values. This work demonstrates the capabilities of the xHCA algorithm tailoring acceleration and intrusion through the use of one meta-parameter (design time) and the use of Kriging-assisted optimization.

Vehicle suspension parts are subjected to variable road loads, manufacturing process variation and high installation loads in assembly process. These parts must be robust to usage conditions to function properly in the field. Design for Six Sigma (DFSS) tools and Taguchi Method were used to optimize initial rear suspension trailing arm design. Project identified key control factor/design parameters, to improve part robustness at the lowest cost. Optimized design performs well under higher road loads and meets stringent durability requirements. This paper evokes use of Taguchi Method to design robust rear suspension trailing arm and study effect of selected design parameters on robustness, stress level/durability and part cost.

This paper presents a novel Kalman filter based road grade estimation method using measurements from an accelerometer, a gyroscope and a velocity sensor. The accelerometer measures the longitudinal proper acceleration of the vehicle, and the accelerometer measurement is almost drift free but it is heavily corrupted by the accelerometer noise. The gyroscope measures the pitch rate of the vehicle, and the gyroscope measurement is quite clean but it is substantially disturbed by the gyroscope bias. The velocity sensor measures the longitudinal velocity of the vehicle, and the velocity sensor measurement is also considerably corrupted by the measurement noise. The developed Kalman filter based estimation method uses the models of the sensors and their outputs, and fuses the sensor measurements to optimally estimate the road grade. The simulation results show that the developed method is very effective in producing an accurate road grade estimate.

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.

The current indication strategies of gear shifting indication system for manual transmission vehicles are developed based on the gear shifting strategies of the automatic transmission vehicles. In this paper, it is found that the gear shifting frequency of automatic transmission vehicles is significantly higher than that of manual transmission vehicles based on the collected driving data of several automatic transmission and manual transmission vehicles, which increases the fatigue of drivers.

Severe crevice corrosion occurring at the joint of cylinder head/gasket/mono-block from lightweight engines causes accelerated dissolution of lightweight material, in particular, in the cylinder head. It facilitates the linking of cooling vessels with the combustion chambers or oil vessels in both the cylinder head and monoblock. It is conductive to combustion of coolant or oil, and contamination of oil with coolant or vice versa, which is considered as catastrophic engine failure. Since crevice corrosion is dependent of assembly characteristics, coolant and engine operation conditions, full-scale tests are the most frequent alternative for this type of evaluations. Nonetheless, they are very long and expensive, and sometimes, unreliable. Alternatively, the standard procedure ASTM-G78 is widely used to evaluate accelerated crevice corrosion of different metallic materials under certain specified immersion conditions using a corrosive media.

Two vehicles with ORVR system which are met with the US standard were studied. A comparative of refueling emissions test under different refueling rate and different refueling temperature were studied. The HC chemical analysis was carried out for the fuel gas emission from a sample car. The results show that with the increase of the refueling rates, the refueling emissions decline at first, and then gradually stabilize; with the increase of the refueling temperature, the results of refueling emissions show a gradual increase. Under the condition of 37 L / min refueling flow rate and 20 °C fuel temperature, 14 kinds of alkanes are emitted from the fuel, in which isobutane, isopentane and n-pentane are the highest emissive components, accounting for 57.66% of the total amount of VOCs.

Vehicle autonomy is critically dependent on an accurate identification and mathematical representation of road and lane geometries. Many road lane identification systems are ad hoc (e.g., machine vision and lane keeping systems) or utilize finely-discretized path data and vehicle tracking systems such as GPS. A novel Midwest Discrete Curvature (MDC) method is proposed in which geodetic road data is parsed along road directions and digitally stored in a road data matrix. Road data is discretized to geospatial points and curvature and road tangent vectorization, which can be utilized to generate consistent, mathematically-defined road profiles with deterministic boundary conditions, consistent non-holonomic boundary constraints, and a smooth, differentiable path which connects critical road coordinates.