Search Results

Traditional ground vehicle architectures comprise of a chassis connected via passive, semi-active, or active suspension systems to multiple ground wheels. Current design-optimizations of vehicle architectures for on-road applications have diminished their mobility and maneuverability in off-road settings. Autonomous Ground Vehicles (AGV) traversing off-road environments face numerous challenges concerning terrain roughness, soil hardness, uneven obstacle-filled terrain, and varying traction conditions. Numerous Active Articulated-Wheeled (AAW) vehicle architectures have emerged to permit AGVs to adapt to variable terrain conditions in various off-road application arenas (off-road, construction, mining, and space robotics). However, a comprehensive framework of AAW platforms for exploring various facets of system architecture/design, analysis (kinematics/dynamics), and control (motions/forces) remains challenging.

The application of virtual engineering methods can streamline the product design process through improved collaboration opportunities among the technical staff and facilitate additive manufacturing processes. A product digital twin can be created using the available computer-aided design and analytical mathematical models to numerically explore the current and future system performance based on operating cycles. The strategic decision to implement a digital twin is of interest to companies, whether the required financial and workforce resources will be worthwhile. In this paper, two metrics are introduced to assist management teams in evaluating the technology potential. The usefulness and time savings metrics will be presented with accompanying definitions. A case study highlights the usefulness metric for the “Deep Orange” prototype vehicle, an innovative off-road hybrid vehicle designed and fabricated at Clemson University.

The integration of sensors, actuators, and real-time control in transportation systems enables intelligent system operation to minimize energy consumption and maximize occupant safety and vehicle reliability. The operating cycle of military ground vehicles can be on- and off-road in harsh weather and adversarial environments, which demands continuous subsystem functionality to fulfill missions. Onboard diagnostic systems can alert the operator of a degraded operation once established fault thresholds are exceeded. An opportunity exists to estimate vehicle maintenance needs using model-based predicted trends and eventually compiled information from fleet operating databases. A digital twin, created to virtually describe the dynamic behavior of a physical system using computer-mathematical models, can estimate the system behavior based on current and future operating scenarios while accounting for past effects.

Multi-material design is one of the trending methods for automakers to achieve lightweighting cost-efficiently and meet stringent regulations and fuel efficiency concerns. Motivated by this trend, the hybrid single-shot (HSS) process has been recently introduced to manufacture thermoset-thermoplastic composites in one single integrated operation. Although this integration is beneficial in terms of reducing the cycle time, production cost, and manufacturing limitations associated with such hybrid structures, it increases the process complexity due to the simultaneous filling, forming, curing, and bonding actions occurring during the process. To overcome this complexity and have a better understanding on the interaction of these physical events, a quick yet accurate simulation of the HSS process based on an experimentally calibrated numerical approach is presented here to elucidate the effect of different process settings on the final geometry of the hybrid part.

Collaborative robots are more and more used in smart manufacturing because of their capability to work beside and collaborate with human workers. With the deployment of these robots, manufacturing tasks are more inclined to be accomplished by multiple humans and multiple robots (MH-MR) through teaming effort. In such MH-MR collaboration scenarios, the task distribution among the multiple humans and multiple robots is very critical to efficiency. It is also more challenging due to the heterogeneity of different agents. Existing approaches in task distribution among multiple agents mostly consider humans with assumed or known capabilities. However human capabilities are always changing due to various factors, which may lead to suboptimal efficiency. Although some researches have studied several human factors in manufacturing and applied them to adjust the robot task and behaviors.

Spark-assisted compression ignition (SACI) leverages flame propagation to trigger autoignition in a controlled manner. The autoignition event is highly sensitive to several parameters, and thus, achieving SACI in production demands a high tolerance to variations in conditions. Limited research is available to quantify the combustion response of SACI to these variations. A simulation study is performed to establish trends, limits, and control implications for SACI combustion over a wide range of conditions. The operating space was evaluated with a detailed chemical kinetics model. Key findings were synthesized from these results and applied to a 1-D engine model. This model identified performance characteristics and potential actuator positions for a production-viable SACI engine. This study shows charge preparation is critical and can extend the low-load limit by strengthening flame propagation and the high-load limit by reducing ringing intensity.

Automotive drive-by-wire systems have enabled greater mobility options for individuals with physical disabilities. To further expand the driving paradigm, a need exists to consider an alternative vehicle steering mechanism to meet specific needs and constraints. In this study, a cellphone steering controller was investigated using a fixed-base driving simulator. The cellphone incorporated the direction control of the vehicle through roll motion, as well as the brake and throttle functionality through pitch motion, a design that can assist disabled drivers by excluding extensive arm and leg movements. Human test subjects evaluated the cellphone with conventional vehicle control strategy through a series of roadway maneuvers. Specifically, two distinctive driving situations were studied: a) obstacle avoidance test, and b) city road traveling test. A conventional steering wheel with self-centering force feedback tuning was used for all the driving events for comparison.

It’s important to predict human actions in the industry assembly process. Foreseeing future actions before they happened is an essential part for flexible human-robot collaboration and crucial to safety issues. Vision-based human action prediction from videos provides intuitive and adequate knowledge for many complex applications. This problem can be interpreted as deducing the next action of people from a short video clip. The history information needs to be considered to learn these relations among time steps for predicting the future steps. However, it is difficult to extract the history information and use it to infer the future situation with traditional methods. In this scenario, a model is needed to handle the spatial and temporal details stored in the past human motions and construct the future action based on limited accessible human demonstrations.

Fuel efficiency improvement in automobiles has been a topic of great interest over the past few years, especially with the introduction of the new CAFE 2025 standards. Although there are multiple ways of improving the fuel efficiency of an automobile, lightweighting is one of the most common approaches taken by many automotive manufacturers. Lightweighting is even more significant in electric vehicles as it directly affects the range of the vehicle. Amidst this context of lightweighting, the use of composite materials as alternatives to metals has been proven in the past to help achieve substantial weight reduction. The focus of using composites for weight reduction has however been typically limited to major structural components, such as BiW and closures, due to high material costs. Secondary structural components which contribute approximately 30% of the vehicle weight are usually neglected by these weight reduction studies.

Adiabatic heating during plastic straining can slow the diffusionless shear transformation of austenite to martensite in steels that exhibit transformation induced plasticity (TRIP). However, the extent to which the transformation is affected over a strain rate range of relevance to automotive stamping and vehicle impact events is unclear for most third-generation advanced high strength TRIP steels. In this study, an 1180MPa minimum tensile strength TRIP steel with carbide-free bainite is evaluated by measuring the variation of retained austenite volume fraction (RAVF) in fractured tensile specimens with position and strain. This requires a combination of servo-hydraulic load frame instrumented with high speed stereo digital image correlation for measurement of strains and ex-situ synchrotron x-ray diffraction for determination of RAVF in fractured tensile specimens.

The automotive industry is aggressively pursuing fuel efficiency improvements through hybridization of production vehicles, and there are an increasing number of racing series adopting similar architectures to maintain relevance with current passenger car trends. Hybrid powertrains offer both performance and fuel economy benefits in a motorsport setting, but they greatly increase control complexity and add additional degrees of freedom to the design optimization process. The increased complexity creates opportunity for performance gains, but simulation based tools are necessary since hybrid powertrain design and control strategies are closely coupled and their optimal interactions are not straightforward to predict. One optimization-related advantage that motorsports applications have over production vehicles is that the power demand of circuit racing has strong repeatability due to the nature of the track and the professional skill-level of the driver.

Emerging autonomous driving technologies, with emergency navigating capabilities, necessitates innovative vehicle steering methods for operators during unanticipated scenarios. A reconfigurable “plug and play” steering system paradigm enables lateral control from any seating position in the vehicle’s interior. When required, drivers may access a stowed steering input device, establish communications with the vehicle steering subsystem, and provide direct wheel commands. Accordingly, the provision of haptic steering cues and lane keeping assistance to navigate roadways will be helpful. In this study, various steering devices have been investigated which offer reconfigurability and haptic feedback to create a flexible driving environment. A joystick and a robotic arm that offer multiple degrees of freedom were compared to a conventional steering wheel.

This paper aims to present an enhanced fuzzy sliding-mode control scheme with variable rate reaching law for semi-active vehicle suspension systems, which can reduce chattering phenomena in high frequency compared with the sliding-mode controller with traditional exponent reaching law. First, an ideal-skyhook damping suspension system is taken as reference model; then the new control law is synthesized by employing the fuzzy logic control while considering the sliding-mode reaching segment characteristics, which can dynamically change the reaching rate to suppress chattering in closed-loop control systems; finally, simulation analysis is conducted under both random road and bump road surface, the results verified the effectiveness and feasibility of the proposed control scheme.

Improper fit in a vehicle will affect a driver’s ability to reach the steering wheel and pedals, view the roadway and instrument gauges, and allow vehicle safety features to protect the driver during a crash. CarFit® is a community outreach program to educate older drivers on proper “fit” within their personal vehicle. A subset of measurements from CarFit® were used to quantify the “fit” of 97 older drivers over 60 and 20 younger drivers, ages 30-39, in their personal vehicles. Binary, logistic regression was used to assess the likelihood of drivers meeting the CarFit® measurement criteria prior to and after CarFit® education. The results showed older drivers were five times more likely than younger drivers to meet the CarFit® criteria for line of sight above the steering wheel, suggesting that younger drivers would also benefit from CarFit® education.

The ability to independently transfer into and out of a vehicle is essential for many wheelchair users to achieve driving independence. The purpose of the current study is to build upon the previous exploratory study that investigated the transfer strategies of wheelchair users by observing YouTube videos. This observational study videotaped five wheelchair users transferring from their wheelchairs into two research vehicles, a small and mid-size sedan that were equipped with a 50mm grid. The goal of this study was to use these videos and vehicle grids to precisely identify ingress and egress motions as well as “touch points” in a controlled setting with a small sample of five male wheelchair users. Using the videos from multiple different camera perspectives, the participants’ ingress and egress transfers were coded, documenting the touch points and step-by-step action sequences.

The advancements in automation, big data computing and high bandwidth networking has expedited the realization of Industrial Internet of Things (IIoT). IIoT has made inroads into many sectors including automotive, semiconductors, electronics, etc. Particularly, it has created numerous opportunities in the automotive manufacturing sector to realize the new aura of platform concepts such as smart material flow control. This paper provides a thought provoking application of IIoT in automotive composites body shop. By creating a digital twin for every physical part, we no longer need to adhere to the conventional manufacturing processes and layouts, thus opening up new opportunities in terms of equipment and space utilization. The century-old philosophy of the assembly line might not be the best layout for vehicle manufacturing, thus proposing a novel assembly grid layout inspired from a colony of ants working to accomplish a common goal.

In the next 20 years fully autonomous vehicles are expected to be in the market. The advance on their development is creating paradigm shifts on different automotive related research areas. Vehicle interiors design and human vehicle interaction are evolving to enable interaction flexibility inside the cars. However, most of today’s vehicle manufacturers’ autonomous car concepts maintain the steering wheel as a control element. While this approach allows the driver to take over the vehicle route if needed, it causes a constraint in the previously mentioned interaction flexibility. Other approaches, such as the one proposed by Google, enable interaction flexibility by removing the steering wheel and accelerator and brake pedals. However, this prevents the users to take control over the vehicle route if needed, not allowing them to make on-route spontaneous decisions, such as stopping at a specific point of interest.

This paper outlines a real-time hierarchical control allocation algorithm for multi-axle land vehicles with independent hub motor wheel drives. At the top level, the driver’s input such as pedal position or steering wheel position are interpreted into desired global state responses based on a reference model. Then, a locally linearized rigid body model is used to design a linear quadratic regulator that generates the desired global control efforts, i.e., the total tire forces and moments required track the desired state responses. At the lower level, an optimal control allocation algorithm coordinates the motor torques in such a manner that the forces generated at tire-road contacts produce the desired global control efforts under some physical constraints of the actuation and the tire/wheel dynamics. The performance of the proposed control system design is verified via simulation analysis of a 3-axle heavy vehicle with independent hub-motor drives.

Low pressure (LP) and cooled EGR systems are capable of increasing fuel efficiency of turbocharged gasoline engines, however they introduce control challenges. Accurate exhaust pressure modeling is of particular importance for real-time feedforward control of these EGR systems since they operate under low pressure differentials. To provide a solution that does not depend on physical sensors in the exhaust and also does not require extensive calibration, a coupled temperature and pressure physics-based model is proposed. The exhaust pipe is split into two different lumped sections based on flow conditions in order to calculate turbine-outlet pressure, which is the driving force for LP-EGR. The temperature model uses the turbine-outlet temperature as an input, which is known through existing engine control models, to determine heat transfer losses through the exhaust.

A state of the art proprietary method for aluminum-to-aluminum joining in the automotive industry is Resistance Spot Welding. However, with spot welding (1) structural performance of the joint may be degraded through heat-affected zones created by the high temperature thermal joining process, (2) achieving the double-sided access necessary for the spot welding electrodes may limit design flexibility, and (3) variability with welds leads to production inconsistencies. Self-piercing rivets have been used before; however they require different rivet/die combinations depending on the material being joined, which adds to process complexity. In recent years the introductions of screw products that combine the technologies of friction drilling and thread forming have entered the market. These types of screw products do not have these access limitations as through-part connections are formed by one-sided access using a thermo-mechanical flow screwdriving process with minimal heat.