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Autonomous vehicles are currently a subject of great interest and there is heavy research on creating and improving algorithms for detecting objects in their vicinity. A ROS-based deep learning approach has been developed to detect objects using point cloud data. With encoded raw light detection and ranging (LiDAR) and camera data, several basic statistics such as elevation and density are generated. The system leverages a simple and fast convolutional neural network (CNN) solution for object identification and localization classification and generation of a bounding box to detect vehicles, pedestrians and cyclists was developed. The system is implemented on an Nvidia Jetson TX2 embedded computing platform, the classification and location of the objects are determined by the neural network. Coordinates and other properties of the object are published on to various ROS topics which are then serviced by visualization and data handling routines.

Whole field displacement/strain measurement of automotive components can be done efficiently by digital image correlation based technique. Inverse problems with this kind of input data, such as the identification of damage parameters/effective modulus in different part of a component, can be pursued by either virtual fields method or finite element model updating. In this paper, the two methods are applied to the identification of a tension plate with a circular hole, and different aspects of the two methods are discussed. It is found that the success of virtual fields method relies on the choice of a set of optimal virtual displacement fields; finite element model updating, on the other hand, can be applied to any geometry and any load condition, and can also be applied to problems where only limited number of measurements are available. However, its performance relies on the choice of optimization algorithms.

A vehicle undergoing longitudinal or lateral accelerations experiences load transfer, dynamically changing the normal load carried by each tire. Conventional braking systems are designed only to work adequately over a large range of conditions, but often ignore the dynamic state of the tire's normal load. Fortunately, new developments in braking system hardware give designers more control over the application of braking pressures. By identifying the tires that carry increased normal load, and biasing the braking system toward those tires, total braking force can be increased. The purpose of this research is to investigate advantages of open-loop load transfer based active brake pressure distribution. By estimating the tractive ability of the tires as a function of measurable vehicle conditions, brake pressure can be applied in proportions appropriate for the current dynamic state of the vehicle, referred to as Active Brake Proportioning (ABP).

Heavy traffic volume makes tailgating a common picture on the road today. Wake interference, particularly in the scenario when a relatively small sedan drives into the wake of a large truck, may raise some serious highway safety concerns. In this paper, the characteristics of the separation bubble of model trucks with various degrees of details are studied. The objective is to find out the impact of truck model details on the characteristics of the wake bubble. Our wind tunnel results revealed that the degree of model detail has a significant effect on the wake bubble; the bubble length increases with model details.

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.

The implementation of fuel cell-battery hybrid vehicles requires a supervisory control strategy that manages the power distribution between the fuel cell and the energy storage device (i.e., battery). Several advanced control methods have already been developed and published in literature. However, most control methods have been developed for different vehicle types and using different mathematical models. The performance of these power management methods have not been directly compared for the same application. This study aims at obtaining direct analytical comparisons, which will provide useful insight in selecting a power management method for fuel cell-battery hybrid vehicles.

The paper describes a study conducted by the University of Windsor Vehicle Dynamics and Control Research Group into the stability of coupled vehicles, e.g., truck-trailer combinations. Several instabilities associated with truck-trailer combinations have been well documented, and have been predicted using mathematical models. Despite having relatively low complexity the classic truck-trailer model, a simple two body, three degree of freedom, linear model has been used extensively in coupled vehicle stability analyses. The aim of the presented work was to extend the conventional coupled vehicle analysis with a set of more elaborate mathematical models evaluating various vehicle configurations. Using in-house multibody dynamics software the linearized equations of motion of three dimensional models were automatically generated for various coupled vehicle configurations with general and military applications. Stability analyses were conducted over a range of expected operating speeds.

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.

Electric power steering (EPS) systems have been used to replace hydraulic power steering systems in vehicles. How to enhance the safety and reliability while reducing the manufacturing cost of EPS systems is still of strong interest to the automotive industry. In this paper, modeling analysis is conducted for advanced control of electric power steering system. Specifically, a mathematical model is proposed for a column-mounted EPS system and then a simplified model for control design purpose is proposed. Issues that need to be addressed, such as noise/ disturbance attenuation as well as potential fault detection/tolerance are analyzed. Simulation using CarSim™ is also presented for an optimal control design using the simplified model as an example to validate the proposed ideas.

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.

A numerical study is performed to investigate the transient heat transfer and flow characteristics of aluminum oxide (Al2O3) nanoparticles dispersed in 50:50 ethylene glycol/water (EG/W) base fluid in a multipass crossflow minichannel heat exchanger. The time dependent thermal responses of the system in a laminar regime are predicted by solving the conservation equations using the finite volume method and SIMPLE algorithm. The transient regime is caused by a step change of nanofluid mass flow rate at the inlet of the minichannel heat exchanger. This step change can be analogous with a thermostat operation. In this study, three volume fractions up to 3 percent of Al2O3 nanoparticles dispersed to the base fluid EG/W are modeled and analyzed. In the numerical simulation, Al2O3-EG/W nanofluid is considered as a homogenous single-phase fluid. An analysis of the transient response for the variation of nanofluids volume concentrations is conducted.

Industrial robotic arms and manipulators are systems that offer technological advances in automation, production, and logistical processes. Therefore, it is vital to understand and analyze the reachability and dexterity of such manipulators. This paper presents a reconfigurable algorithm for evaluation and 3D visual representation of the total workspace and singularity space of two and three degrees of freedom open-ended kinematic chains. A manipulator's performance is greatly depreciated at or near singular regions which may occur as subset(s) in its complete workspace. It is therefore crucial to understand the functional workspace of a manipulator for an enhanced performance in an industrial setting. The implementation of this algorithm requires two inputs namely; the joint type(s), rotational (R) or translational (T), and the Denavit-Hartenberg (D-H) parameters of the manipulator.

Amid all nondestructive testing (NDT) methods Ultrasound is considered the most practically feasible modality for quality assessment and detection of defects in automobile industry. Pattern recognition of the ultrasonic signals gives us important information about the interrogated object. This information includes size, geometric shape and location of the defect zone. However, this would not be straightforward to extract this information from the backscattered echoes due to the overlapping signals and also the presence of noise. Here in this study, we suggest a new method for classification of different defects in inspection of adhesively bonded joint. At the first step of this method, the problem of parameter estimation of the reflected echoes is defined in a Maximum Likelihood Estimation (MLE) framework. Then a space alternating generalized Expectation Maximization (SAGE) algorithm is implemented to solve the MLE problem.