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Today’s advanced vehicles have high degree of interaction due to numerous sensors, actuators and also with complex communication within the control units. In order to hack a vehicle, it has to be within a certain range of communication. Here, we discuss the On-Board Diagnostic (OBD) regulations for next generation BEV/HEV, its vulnerabilities and cybersecurity threats that come with hacking. We propose three cybersecurity attack detection and defense methods: Cyber-Attack detection algorithm, Time-Based CAN Intrusion Detection Method and, Feistel Cipher Block Method. These control methods autonomously diagnose a cybersecurity problem in a vehicle’s onboard system using an OBD interface, such as OBD-II when a fault caused by a cyberattack is detected, All of this is achieved in an internal communication network structure. The results discussed here focus on the first detection method that is Cyber-Attack detection algorithm.

This paper presents experimental investigations of determining and analyzing low-frequency, low-SNR (Signal to Noise Ratio) noise sources of an automobile by using a new technology known as Sound Viewer. Such a task is typically very difficult to do especially at low or even negative SNR. The underlying principles behind the Sound Viewer technology consists of a passive SODAR (Sonic Detection And Ranging) and HELS (Helmholtz Equation Least Squares) method. The former enables one to determine the precise locations of multiple sound sources in 3D space simultaneously over the entire frequency range consistent with a measurement microphone in non-ideal environment, where there are random background noise and unknown interfering signals. The latter enables one to reconstruct all acoustic quantities such as the acoustic pressure, acoustic intensity, time-averaged acoustic power, radiation patterns, etc.

Previous study suggested that female, thin, obese, and older occupants had a higher risk of death and serious injury in motor vehicle crashes. Human body finite element models were a valuable tool in the study of injury biomechanics. The mesh deformation method based on radial basis function(RBF) was an attractive alternative for morphing baseline model to target models. Generally, when a complex model contained many elements and nodes, it was impossible to use all surface nodes as landmarks in RBF interpolation process, due to its prohibitive computational cost. To improve the efficiency, the current technique was to averagely select a set of nodes as landmarks from all surface nodes. In fact, the location and the number of selected landmarks had an important effect on the accuracy of mesh deformation. Hence, how to select important nodes as landmarks was a significant issue. In the paper, an efficient peak point-selection RBF mesh deformation method was used to select landmarks.

Fiber composite materials are widely used in many industrial applications - specially in automotive, aviation and consumer goods. Introducing light-weighting material solutions to reduce vehicle mass is driving innovative materials research activities as polymer composites offer high specific stiffness and strength compared to contemporary engineering materials. However, there are issues related to high production volume, automation strategies and handling methods. The state of the art for the production of these light-weight flexible textile or composite fiber products is setting up multi-stage manual operations for hand layups. Material handling of flexible textile/fiber components is a process bottleneck. Consequently, the long term research goal is to develop semi-automated pick and place processes for flexible materials utilizing collaborative robots within the process. Collaborative robots allow for interactive human-machine tasks to be conducted.

Natural fiber-reinforced composites are currently gaining increasing attention as potential substitutes to pervasive synthetic fiber-reinforced composites, particularly glass fiber-reinforced plastics (GFRP). The advantages of the former category of composites include (a) being conducive to occupational health and safety during fabrication of parts as well as handling as compared to GFRP, (b) economy especially when compared to carbon fiber-reinforced composites (CFRC), (c) biodegradability of fibers, and (d) aesthetic appeal. Jute fibers are especially relevant in this context as jute fabric has a consistent supply base with reliable mechanical properties. Recent studies have shown that components such as tubes and plates made of jute-polyester (JP) composites can have competitive performance under impact loading when compared with similar GFRP-based structures.

In this paper, we present a project being conducted at Yalong Educational Equipment Company on control of educational robots using discrete event system theory. An educational robot is a programmable robot to be used by students for training and learning. To model a robot, we divide the robot into nine physical modules. Each module is modeled as an automaton. Parallel composition is used to obtain the entire model. The robot can be programmed to perform sequences of basic tasks. We investigate six basic tasks and use supervisors to control and achieve the tasks. Desired languages are obtained for all tasks and supervisory control theory is used to synthesize supervisors. To reduce computational complexity, modular/coordinated supervisors are used

There has been a keen interest in recent times on implementation of lightweight materials in vehicles to bring down the unladen weight of a vehicle for enhancing fuel efficiency. Fiber-reinforced composites comprise a class of such materials. As sustainability is also a preoccupation of current product development engineers including vehicle designers, bio-composites based on natural fibers are receiving a special attention. Keeping these motivations of lower effective density, environment friendliness and occupational safety in mind, woven jute fabric based composites have been recently studied as potential alternatives to glass fiber composites for structural applications in automobiles. In the past, mechanical characterization of jute-polyester composites were restricted to obtaining their stress-strain behaviors under quasi-static conditions.

The ‘boundary of space’ model representing all possible positions which may be occupied by a mechanism during its normal range of motion (for all positions and orientations) is called the work envelope. In the robotic domain, it is also known as the robot operating envelope or workspace. Several researchers have investigated workspace boundaries for different degrees of freedom (DOF), joint types and kinematic structures utilizing many approaches. The work envelope provides essential boundary information, which is critical for safety and layout concerns, but the work envelope information does not by itself determine the reach feasibility of a desired configuration. The effect of orientation is not captured as well as the coupling related to operational parameters. Included in this are spatial occupancy concerns due to linking multiple kinematic chains, which is an issue with multi-tasking machine tools, and manufacturing cells.

When performing trajectory planning for robotic applications, there are many aspects to consider, such as the reach conditions, joint and end-effector velocities, accelerations and jerk conditions, etc. The reach conditions are dependent on the end-effector orientations and the robot kinematic structure. The reach condition feasibility is the first consideration to be addressed prior to optimizing a solution. The ‘functional’ work space or work window represents a region of feasible reach conditions, and is a sub-set of the work envelope. It is not intuitive to define. Consequently, 2D solution approaches are proposed. The 3D travel paths are decomposed to a 2D representation via radial projections. Forward kinematic representations are employed to define a 2D boundary curve for each desired end effector orientation.

This study investigated driver glances while engaging in infotainment tasks in a stationary vehicle while surrogate driving: watching a driving video recorded from a driver’s viewpoint and projected on a large screen, performing a lane-tracking task, and performing the Tactile Detection Response Task (TDRT) to measure attentional effects of secondary tasks on event detection and response. Twenty-four participants were seated in a 2014 Toyota Corolla production vehicle with the navigation system option. They performed the lane-tracking task using the vehicle’s steering wheel, fitted with a laser pointer to indicate wheel movement on the driving video. Participants simultaneously performed the TDRT and a variety of infotainment tasks, including Manual and Mixed-Mode versions of Destination Entry and Cancel, Contact Dialing, Radio Tuning, Radio Preset selection, and other Manual tasks. Participants also completed the 0-and 1-Back pure auditory-vocal tasks.

A collaborative robot or cobot is a robot that can safely and effectively interact with human workers while performing industrial tasks. The ability to work alongside humans has increased the importance of collaborative robots in the automation industry, as this unique feature is a much needed property among robots nowadays. Rethink Robotics has pioneered this unique discipline by building many robots including the Baxter Robot which is exclusive not only because it has collaborative properties, but because it has two arms working together, each with 7 Degrees Of Freedom. The main goal of this research is to validate the kinematic equations for the Baxter collaborative robot and develop a unified reconfigurable kinematic model for the Left and Right arms so that the calculations can be simplified.

Hat-sections, single and double, made of steel are frequently encountered in automotive body structural components. These components play a significant role in terms of impact energy absorption during vehicle crashes thereby protecting occupants of vehicles from severe injury. However, with the need for higher fuel economy and for compliance to stringent emission norms, auto manufacturers are looking for means to continually reduce vehicle body weight either by employing lighter materials like aluminum and fiber-reinforced plastics, or by using higher strength steel with reduced gages, or by combinations of these approaches. Unlike steel hat-sections which have been extensively reported in published literature, the axial crushing behavior of hat-sections made of fiber-reinforced composites may not have been adequately probed.

Path planning and re-planning for serial 6 degree of freedom (DOF) robotic systems is challenging due to complex kinematic structure and application conditions which affects the robot's tool frame position, orientation and singularity avoidance. These three characteristics represent the key elements for production planning and layout design of the automated manufacturing systems. The robot trajectory represents series of connected points in 3D space. Each point is defined with its position and orientation related to the robot's base frames or predefined user frame. The robot will move from point to point using the desired motion type (linear, arc, or joint). The trajectory planning requires first to check if robot can reach the selected part(s). This can be simply done by placing the part(s) inside the robot's work envelope. The robot's work envelope represents a set of all robots' reachable points without considering their orientation.

Shell Elements based Parametric Frame Modeling is a powerful CAE tool, which can generate robust frame design concept optimized for NVH and durability quickly when combined with Taguchi Design of Experiments. The scalability of this modeling method includes cross members length/location/section/shape, frame rail segments length/section and kick in/out/up/down angle, and access hole location & size. In the example of the D. O. E. study, more than fifteen parameters were identified and analyzed for frequency and weight. The upper and lower bounds were set for each design parameter based on package and manufacturing constraints. Sixteen Finite Element frame were generated by parametrically updating the base model, which shows this modeling method is comparatively convenient. Sensitivity of these sixteen parameters to the frequency and weight was summarized through statics, so the favorable design alternative can be achieved with the major parameters' combination.

The goal of optimization in vehicle design is often blurred by the myriads of requirements belonging to attributes that may not be quite related. If solutions are sought by optimizing attribute performance-related objectives separately starting with a common baseline design configuration as in a traditional design environment, it becomes an arduous task to integrate the potentially conflicting solutions into one satisfactory design. It may be thus more desirable to carry out a combined multi-disciplinary design optimization (MDO) with vehicle weight as an objective function and cross-functional attribute performance targets as constraints. For the particular case of vehicle body structure design, the initial design is likely to be arrived at taking into account styling, packaging and market-driven requirements.

Biomechanical surrogates are used in various forms to study head impact response in automotive applications and for assessing helmet performance. Surrogate headforms include those from the National Operating Committee on Standards for Athletic Equipment (NOCSAE) and the many variants of the Hybrid III. However, the response of these surrogates to loading at the chin and how that response may affect the loads transferred from the jaw to the rest of the head are unknown. To address part of that question, the current study compares the chin impact response performance of select human surrogates to that of the cadaver. A selection of Hybrid III and NOCSAE based surrogates with fixed and articulating jaws were tested under drop mass impact conditions that were used to describe post mortem human subject (PMHS) response to impacts at the chin (Craig et al., 2008). Results were compared to the PMHS response with cumulative variance technique (Rhule et al., 2002).

The short NiTi fiber-reinforced NiTi/Al6061-SiC composite was recently developed through the U.S. Army SBIR Phase-II program [1]. The objectives of this project are to use short NiTi fiber reinforcement to induce compressive stress through shape memory effect, to use silicon carbide (SiC) particulate reinforcement to enhance the mechanical properties of the aluminum matrix, to gain fundamental knowledge of short NiTi fiber-reinforced aluminum matrix composite, and eventually to improve fatigue resistance, impact damage tolerance and fracture toughness of the composite. The fatigue life, damage and fracture behavior of TiNi/Al6061-SiC, TiNi/Al6061, Al6061-SiC composites as well as monolithic Al6061 alloy were investigated under fully reversed cyclic loading. It was found that fatigue life of NiTi/Al6061-SiC composite, in term of the cycles, increased by two orders of magnitude, compared to monolithic Al6061 alloy

Lean Six Sigma is an approach that is gaining momentum both in manufacturing and service industries. Design for Lean Six Sigma (DFLSS) is an outgrowth of the DFSS and Lean Six Sigma approaches. The essence of DFLSS is to ensure design quality and predictability during the early design phases and the approach employs a structured integrated product development methodology and a comprehensive set of robust tools to drive product quality, innovation, faster time to market, and lower product costs. When it comes to automotive Product Development, applying lean principles and DFSS together becomes more of a challenge within the existing PD system. While the benefits of DFLSS present an attractive proposition in a fiercely competitive market it brings its own challenges as to how to deploy it for maximum benefits. This paper examines the challenges, potential and opportunities for DFLSS in the automotive industry and presents a vision for integrating it in to the Product Development System.

This paper describes the diagnostics of noise sources and characteristics of a full-size gasoline engine during its run-up using Helmholtz Equation Least Squares (HELS) method based nearfield acoustical holography (NAH). The acoustic pressures are measured using an array of 56 microphones conformal to the contours of engine surfaces at very close range. Measurements are collected near the oil pan, front and intake sides. The data thus collected are taken as input to HELS program, and the acoustic pressure mappings on the oil pan, front and intake surfaces are calculated. These reconstructed acoustic quantities clearly demonstrate the “hot spots” of sound pressures generated by this gasoline engine during its run-up and under a constant speed condition. These acoustic pressure mappings together with order-tracking spectrograms allow for identification of the peak amplitudes of acoustic pressures on a targeted surface as a function of the frequency and engine rpm.

A composite of an aluminum matrix reinforced by short TiNi shape memory alloy (SMA) fibers was fabricated. The processing and thermomechanical behaviors of the composite TiNi/Al6061 were investigated experimentally and analytically. Optimal hot-pressing conditions of TiNi/Al6061 processing were identified. The shape memory effect (SME) was activated by prestraining the composite at the temperature between Ms and As, followed by heating up to Af. SME on mechanical properties, such as microhardness, yield stresses of the composite, were investigated. A computational model for the strengthening mechanism of the short fiber metal matrix composite was utilized to analyze SME on yield stress of the composite. Yield stress of the composite as a function of prestrain was predicted numerically and verified experimentally.