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The use of virtual prototyping early in the design stage of a product has gained popularity due to reduced cost and time to market. The state of the art in vehicle simulation has reached a level where full vehicles are analyzed through simulation but major difficulties continue to be present in interfacing the vehicle model with accurate powertrain models and in developing adequate formulations for the contact between tire and terrain (specifically, scenarios such as tire sliding on ice and rolling on sand or other very deformable surfaces). The proposed work focuses on developing a ground vehicle simulation capability by combining several third party packages for vehicle simulation, tire simulation, and powertrain simulation. The long-term goal of this project consists in promoting the Digital Car idea through the development of a reliable and robust simulation capability that will enhance the understanding and control of off-road vehicle performance.

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.

Road vehicles can expend a significant amount of energy in undesirable vertical motions that are induced by road bumps, and much of that is dissipated in conventional shock absorbers as they dampen the vertical motions. Presented in this paper are some of the results of a study aimed at determining the effectiveness of efficiently transforming that energy into electrical power by using optimally designed regenerative electromagnetic shock absorbers. In turn, the electrical power can be used to recharge batteries or other efficient energy storage devices (e.g., flywheels) rather than be dissipated. The results of the study are encouraging - they suggest that a significant amount of the vertical motion energy can be recovered and stored.

As connectivity and sensing technologies become more mature, automated vehicles can predict future driving situations and utilize this information to drive more energy-efficiently than human-driven vehicles. However, future information beyond the limited connectivity and sensing range is difficult to predict and utilize, limiting the energy-saving potential of energy-efficient driving. Thus, we combine a conventional speed optimization planner, developed in our previous work, and reinforcement learning to propose a real-time intelligent speed optimization planner for connected and automated vehicles. We briefly summarize the conventional speed optimization planner with limited information, based on closed-form energy-optimal solutions, and present its multiple parameters that determine reference speed trajectories.

In a frontal automotive crash, the driver's foot is usually stepping on the brake pedal as an instinctive response to avoid a collision. The tensile force generated in the Achilles tendon produces a compressive preload on the tibia. If there is intrusion of the toe board after the crash, an additional external force is applied to the driver's foot. A series of dynamic impact tests using human cadaveric specimens was conducted to investigate the combined effect of muscle preloading and external force. A constant tendon force was applied to the calcaneus while an external impact force was applied to the forefoot by a rigid pendulum. Preloading the tibia significantly increased the tibial axial force and the combination of these forces resulted in five tibial pylon fractures out of sixteen specimens.

The recovery of braking energy through regenerative braking is a key enabler for the improved efficiency of Hybrid Electric Vehicles, Plug-in Hybrid Electric, and Battery Electric Vehicles (HEV, PHEV, BEV). However, this energy is often treated in a simplified fashion, frequently using an overall regeneration efficiency term, ξrg [1], which is then applied to the total available braking energy of a given drive-cycle. In addition to the ability to recapture braking energy typically lost during vehicle deceleration, hybrid and plug-in hybrid vehicles also allow for reduced or zero engine fueling during vehicle decelerations. While regenerative braking is often discussed as an enabler for improved fuel economy, reduced fueling is also an important component of a hybrid vehicle's ability to improve overall fuel economy.

Finite element simulations are widely used for simulating disc brake squeal and the aim of this paper is to further increase the understanding of the effect of insulators. An earlier paper has presented an experimental technique for measuring the properties of the viscoelastic materials [1] and it has been shown how these data can be used in simulating brake response [2]. This paper deals with the sensitivity of a FE brake model to frequency dependent shim material properties and it is documented that with the current options for modeling shims in complex eigenvalue analysis it is only possible to accurately simulate response in a narrow frequency range. A procedure to find optimized parameters for a current damping model is discussed. The best α and β values for a Rayleigh damping model is found by obtaining a least square best fit in a frequency range of interest.

Perception in adverse weather conditions is one of the most prominent challenges for automated driving features. The sensors used for mid-to-long range perception most impacted by weather (i.e., camera and LiDAR) are susceptible to data degradation, causing potential system failures. This research series aims to better understand sensor data degradation characteristics in real-world, dynamic environmental conditions, focusing on adverse weather. To achieve this, a dataset containing LiDAR (Velodyne VLP-16) and camera (Mako G-507) data was gathered under static scenarios using a single vehicle target to quantify the sensor detection performance. The relative position between the sensors and the target vehicle varied longitudinally and laterally. The longitudinal position was varied from 10m to 175m at 25m increments and the lateral position was adjusted by moving the sensor set angle between 0 degrees (left position), 4.5 degrees (center position), and 9 degrees (right position).

The pia-arachnoid complex (PAC) covering the brain plays an important role in the mechanical response of the brain due to impact or inertial loading. The mechanical properties of the bovine PAC under tensile loading have been characterized previously. However, the transverse properties of this structure, such as shear and normal traction which are equally important to understanding the skull/brain interaction under traumatic loading, have not been investigated. These material properties are essential information needed to adequately define the material model of the PAC in a finite element (FE) model of human brain. The purpose of this study was to determine, experimentally, the material properties of the PAC under normal traction loading. PAC specimens were obtained from freshly slaughtered bovine subjects from various locations.

This two-part paper provides a systematic approach for identifying the fundamental causes of both low and high frequency brake squeal using advanced analytical and experimental methods. Also shown are methods to develop solutions to reduce or eliminate squeal by investigating effective structural countermeasures. Part I presented here is focused on low frequency squeal (2.2 & 5.5 kHz). In order to better understand the mechanism of squeal generation, this study started with the component modal alignment analysis around problem frequencies based on the component EMA (Experimental Modal Analysis) data in free-free condition. Then, the brake system EMA was conducted to gain insight into the potential system modes which caused the squeal. The last step of the brake squeal diagnosis utilized the ODS (Operational Deflection Shape) result to identify the key components involved in the squeal event.

This paper applies the existing techniques used in the CAE simulation for calculation of potential high frequency (>10 kHz) squeal from disc brake system. The goal is to investigate the component interaction at the system level. A simulated dynamometer process is developed using stability analysis at different pressures and friction coefficient combinations. From the identified squealing condition, coupled with measured ODS, dynamic characteristics at system level are tracked to the components contribution based on the mode merging phenomenon as the system turns unstable due to friction coupling. The component contribution is based on the strain energy of the component in the system mode and MAC between mode components in free condition and system real modes. Special focus on rotor dynamics is discussed and its effect on system instability at high frequency range.

The modal characteristics of a brake pad are important factors affecting brake squeal. The most frequently used counter-measures for eliminating or reducing squeal, especially at high frequency, are the modification of: the modal frequencies, damping, contact modal shapes or patterns of a pad by making a chamfer or slot, or selecting a different under-layer, lining material or insulator. This paper describes the development of the methods for the measurement of pad modal characteristics such as modal damping, frequency and contact mode shape. It provides comparison among three methods: accelerometer-hammer, laser-hammer, and laser/non-contact shaker with test data and CAE simulation. Subsequently, laser/non-contact shaker was used to evaluate the process capability of pad manufacturing in terms of modal damping and natural frequency. This method was also employed to investigate the effect of pad chamfer, under-layer and the insulator on pad modal characteristics.

This paper details the use of experimental and test data based analytical techniques to resolve brake squeal. External excitation was applied to the brake system during operation on an inertia dynamometer and FRF measurements were taken. The operating conditions were varied with respect to disc velocity and brake line pressure. An experimental modal analysis under operating (EMA-OC) was performed on a disc brake, with a 2.6 kHz squeal, during squealing and non-squealing operational conditions. Two modes close in frequency to the 2.6 kHz squeal were identified from modal analysis of the brake system in a non-squealing operational condition which were not individually present during squealing conditions. These two modes were assumed to be the modes which couple due to friction and thus produce squeal in operation. A sensitivity analysis was then conducted on the modal model obtained from an EMA-OC non-squealing operational case.

This paper illustrates the importance of road vibration in the study of disc thickness variation generation in disc brake rotors, showing that laboratory conditions must include vibration as well as realistic reproductions of speeds, pressures, and inertia, etc. Such conditions are made possible with the Bosch Road Load Dynamometer (RLD). A related paper, Road Load Dynamometer: Combining Brake Dynamometry with Multi-Axis Road Vibration, SAE 2003-01-1638, showed that the RLD could accurately and repeatedly reproduce field conditions, but did not contain disc thickness variation (DTV) generation data. This paper contrasts rotor wear data for a controlled experiment on the RLD, with and without vibrational input. In the control group, DTV generation data comparable to vehicle test results were recreated. In the experimental group, similar hardware was subjected to the same tests except for the absence of vibration input.

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.

Connected automated vehicles (CAVs) are quickly becoming a reality, and their potential ability to communicate with each other and the infrastructure around them has big potential impacts on future mobility systems. Perhaps one of the most important impacts could be on network wide energy consumption. A lot of research has already been performed on the topic of eco-driving and the potential fuel and energy consumption benefits for CAVs. However, most of the efforts to date have been based on simulation studies only, and have only considered conventional vehicle powertrains. In this study, experimental data is presented for the potential eco-driving benefits of two specific intersection approach scenarios, for four different powertrain types.

The effects of several faults on different parameters in a distributor injection system are studied both theoretically and experimentally. The faults imposed on a healthy system are: fuel leaks between the pump and injector, improper adjustment of the injector opening pressure, a broken or missing injector spring, plugged nozzle holes, and a stuck-closed needle. The injector parameters examined include maximum fuel pressures reached at different locations in the system, needle lift, injection lag, and injection rate.

This research investigates the energy savings achieved through eco-driving controls in connected and automated vehicles (CAVs), with a specific focus on the influence of powertrain characteristics. Eco-driving strategies have emerged as a promising approach to enhance efficiency and reduce environmental impact in CAVs. However, uncertainty remains about how the optimal strategy developed for a specific CAV applies to CAVs with different powertrain technologies, particularly concerning energy aspects. To address this gap, on-track demonstrations were conducted using a Chrysler Pacifica CAV equipped with an internal combustion engine (ICE), advanced sensors, and vehicle-to-infrastructure (V2I) communication systems, compared with another CAV, a previously studied Chevrolet Bolt electric vehicle (EV) equipped with an electric motor and battery.

Automated driving functionalities delivered through Advanced Driver Assistance System (ADAS) have been adopted more and more frequently in consumer vehicles. The development and implementation of such functionalities pose new challenges in safety and functional testing and the associated validations, due primarily to their high demands on facility and infrastructure. This paper presents a rather unique Vehicle-in-the-Loop (VIL) test setup and methodology compared those previously reported, by combining the advantages of the hardware-in-the-loop (HIL) and traditional chassis dynamometer test cell in place of on-road testing, with a multi-agent real-time simulator for the rest of test environment.

Over the past decade there has been significant development in Automated Driving (AD) with continuous evolution towards higher levels of automation. Higher levels of autonomy increase the vehicle Dynamic Driving Task (DDT) responsibility under certain predefined Operational Design Domains (in SAE level 3, 4) to unlimited ODD (in SAE level 5). The AD system should not only be sophisticated enough to be operable at any given condition but also be reliable and safe. Hence, there is a need for Automated Vehicles (AV) to undergo extensive open road testing to traverse a wide variety of roadway features and challenging real-world scenarios. There is a serious need for accurate Ground Truth (GT) to locate the various roadway features which helps in evaluating the perception performance of the AV at any given condition. The results from open road testing provide a feedback loop to achieve a mature AD system.