Search Results

The handling of flexible components creates a unique problem set for pick and place automation within automotive production processes. Fabrics and woven textiles are examples of flexible components used in car interiors, for air bags, as liners and in carbon-fiber layups. These textiles differ greatly in geometry, featuring complex shapes and internal slits with varying material properties such as drape characteristics, crimp resistance, friction, and fiber weave. Being inherently flexible and deformable makes these materials difficult to handle with traditional rigid grippers. Current solutions employ adhesive, needle-based, and suction strategies, yet these systems prove a higher risk of leaving residue on the material, damaging the weave, or requiring complex assemblies. Pincer-style grippers are suitable for rigid components and offer strong gripping forces, yet inadvertently may damage the fabric, and introduce wrinkles / folded-over edges during the release process.

Automotive Open System Architecture (AUTOSAR) is a system-level standard that is formed by the worldwide partnership of automotive manufacturers and suppliers who are working together to develop a standardized Electrical and Electronic (E/E) framework and architecture for automobiles. The AUTOSAR methodology has two main activities: system configuration and the Electronic Control Unit (ECU) configuration. The system configuration is the mapping of the software components to the ECUs based on the system requirements. The ECU configuration (EC) process is an important part of the ECU software integration and generation. ECU-specific information is extracted from the system configuration description, and all the necessary information for the implementation such as tasks, scheduling, and assignments of the runnables to tasks and configuration of the Basic Software (BSW) modules are performed. The EC process involves configuring every single module of the AUTOSAR.

Automotive Open System Architecture (AUTOSAR) is a system-level standard that is formed by the worldwide partnership of the automotive manufacturers and suppliers who are working together to develop a standardized Electrical and Electronic (E/E) framework and architecture for automobiles. The AUTOSAR methodology has two main activities: system configuration and the Electronic Control Unit (ECU) configuration. The system configuration is the mapping of the software components to the ECUs based on the system requirements. The ECU configuration process is an important part of the ECU software integration and generation. ECU specific information is extracted from the system configuration description and all the necessary information for the implementation such as tasks, scheduling, assignments of the runnables to tasks and configuration of the Basic Software (BSW) modules, are performed. The ECU configuration process involves configuring every single module of the AUTOSAR architecture.

For internal combustion engine systems, lean and diluted combustion is an important technology applied for fuel efficiency improvement. Because of the thermodynamic boundary conditions and the presence of in-cylinder flow, the development of a well-sustained flame kernel for lean combustion is a challenging task. Reliable spark discharge with the addition of enhanced delivered energy is thus needed at certain time durations to achieve successful combustion initiation of the lean air-fuel mixture. For a conventional transistor coil ignition system, only limited amount of energy is stored in the ignition coil. Therefore, both the energy of the spark discharge and the duration of the spark discharge are bounded. To break through the energy limit of the conventional transistor coil ignition system, in this work, an adaptive spark ignition system is introduced. The system has the ability to reconstruct the conductive ion channels whenever it is interrupted during the spark discharge.

Light-weighting fiber composite materials introduced to reduce vehicle mass and known as innovative materials research activities since they provide high specific stiffness and strength compared to contemporary engineering materials. Nonetheless, there are issues related automation strategies and handling methods. Material handling of flexible textile/fiber components is a process bottleneck and it is currently being performed by setting up multi-stage manual operations for hand layups. Consequently, the long-term research objective is to develop semi-automated pick and place processes for flexible materials utilizing collaborative robots within the process. The immediate research is to experimentally validate innovatively designed grippers for efficient material pick and place tasks.

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.

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.

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.

Gantry robots are mainly employed for applications requiring large workspace, with limited higher manipulability in one direction than the others. The Gantries offer very good mechanical stiffness and constant positioning accuracy, but low dexterity. Common gantries are CNC machines with three translational joints XYZ (3DOF) and usually with an attached wrist (+3DOF). The translational joints are used to move the tool in any position in the 3D workspace. The wrist is used to orient the tool by rotation about X, Y and Z axis. This standard kinematic structure (3T3R) produces a rectangular workspace. In this paper a full kinematic model for a 6DOF general CNC (gantry) machine is presented, along with the Jacobian matrix and singularity analysis. Using Denavit-Hartenberg convention, firstly, the general kinematic structure is presented, in order to assign frames at each link. The forward kinematic problem is solved using Maple 17 software.

Following the development of new technologies in Vehicle Thermal Management aiming to both enhancing the MAC System efficiency and reducing the thermal load to be managed, a prediction tool based on the AMEsim platform was developed at Advanced PD EMEA. This tool is dedicated to predict the effect of the implementation of sensors monitoring both the relative humidity and the carbon dioxide (CO2) concentration (taking into account passengers' generated moisture and CO2). This model implemented with the usual comfort inputs (CO2 and RH acceptable ranges) considers the system variables influencing the comfort and predicts the increase of both RH and CO2 concentration in the cabin compartment in any driving cycle depending on the number of occupants.

In this study the capabilities of a semi-active suspension and an active roll suspension are evaluated for comparison with a passive suspension. The vehicle used is a utility truck modeled as a multi-body system in ADAMS/Car while the ECU (electronic control unit) is built in Matlab/Simulink. Cosimulation is used in linking the vehicle model with the controller by exchanging the input and output values of each sub-system with one another. For the simulation models considered, results indicate that for a fish-hook cornering maneuver the semi-active suspension is limited in increasing vehicle performance while the active roll suspension significantly improves it. Further analysis is needed to confirm these findings.

Low temperature combustion (LTC), though effective to reduce soot and oxides of nitrogen (NOx) simultaneously from diesel engines, operates in narrowly close to unstable regions. Adaptive control strategies are developed to expand the stable operations and to improve the fuel efficiency that was commonly compromised by LTC. Engine cycle simulations were performed to better design the combustion control models. The research platform consists of an advanced common-rail diesel engine modified for the intensified single cylinder research and a set of embedded real-time (RT) controllers, field programmable gate array (FPGA) devices, and a synchronized personal computer (PC) control and measurement system.

The paper describes a ‘virtual motorsports’ event developed by the University of Windsor Vehicle Dynamics and Control Research Group. The event was a competitive project-based component of a Vehicle Dynamics course offered by the University's Department of Mechanical, Automotive, & Materials Engineering. The simulated race was developed to provide fourth year automotive engineering students with design and race experience, similar to that found in Formula SAE®or SAE Baja®, but within the confines of a single academic semester. The project, named ‘Formula463’, was conducted entirely within a virtual environment, and encompassed design, testing, and racing of hi-fidelity virtual vehicle models. The efficacy of the Formula463 program to provide students with a design experience using model based simulation tools and methods has been shown over the past two years. All of the software has been released under a General Public License and is freely available on the authors website.

A number of cylinder-pressure derived parameters including the crank angles of maximum pressure, maximum rate of pressure rise, and 50% heat released are considered as among the desired feedback for cycle-by-cycle adaptive control of diesel combustion. For real-time computation of these parameters, the heat release analyses based on the first law of thermodynamics are used. This paper intends to identify the operating regions where the simplified heat release approach provides sufficient accuracy for control applications and also highlights those regions where its use can lead to significant errors in the calculated parameters. The effects of the cylinder charge-to-wall heat transfer and the temperature dependence of the specific heat ratio on the model performance are reported. A new computationally efficient algorithm for estimating the crank angle of 50% heat released with adequate accuracy is proposed for computation in real-time.

Heat-release and cylinder pressure based adaptive fuel-injection control tests were performed on a modern common-rail diesel engine to improve the engine operation in the low-temperature combustion (LTC) region. A single shot injection strategy with heavy amount of exhaust gas recirculation (EGR) was used to modulate the in-cylinder charge conditions to achieve the low-temperature combustion. Adaptive fuel-injection techniques were used to anchor the cylinder pressure characteristics in the desired crank angle window and thereby stabilize the engine operation. The response of the adaptive control to boost, fueling, and engine speed variations was also tested. A combination of adaptive fuel-injection and automatic boost/back-pressure controls had helped to make the transient emissions comparable to the steady-state LTC emissions.

The purpose of this study is to determine the feasibility of simulating an active suspension using cosimulation. The vehicle used is a utility truck created in ADAMS/View while the E.C.U. (electronic control unit) is implemented in Simulink for both a fully-active and semi-active controller. The LQR (Linear Quadratic Regulator) is used for the fully-active system while the semi-active system uses a switching law adopted from Karnopp et al. {1}. Nonlinear and linear vehicle models are compared and the influence of suspension bushings is examined. All simulations undertaken are geared towards evaluating the ride capabilities of such systems.

Neural networks are flexible modeling tools that can be used in conjunction with multi-body dynamics models to better predict nonlinear behaviour of components. This paper focuses on a process that incorporates a neural network model of a nonlinear damping force into a single degree of freedom mass-spring-damper model. Software tools and their interaction are specified. The verification of this process is the focal point of this paper and is a necessary step before further correlation studies can be performed on more complex component representations.