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Brake squeal has been a chronic customer complaint, often appearing high on the list of items that reduce customers' satisfaction with their vehicles. Brake squeal can emanate from either a drum brake or a disc brake even though the geometry of the two systems is significantly different. A drum brake generates friction within a cylindrical drum interacting with two semi-circular linings. A disc brake consists of a flat disc and two flat pads. The observed squeal behavior in a vehicle differs somewhat between drum and disc brakes. A drum brake may have a loud noise coming from three or more squeal frequencies, whereas a disc brake typically has one or two major squeal frequencies making up the noise. A good understanding of the operational deflection shapes of the brake components during noise events will definitely aid in design to reduce squeal occurrences and improve product quality.

The transportation sector is facing three revolutions: shared mobility, electrification, and autonomous driving. To inform decision making and guide smart transportation system development at the city-level, it is critical to model and evaluate how travelers will behave in these systems. Two key components in such models are (1) individual travel demands with high spatial and temporal resolutions, and (2) travelers’ sociodemographic information and trip purposes. These components impact one’s acceptance of autonomous vehicles, adoption of electric vehicles, and participation in shared mobility. Existing methods of travel demand generation either lack travelers’ demographics and trip purposes, or only generate trips at a zonal level. Higher resolution demand and sociodemographic data can enable analysis of trips’ shareability for car sharing and ride pooling and evaluation of electric vehicles’ charging needs.

The performance of structure-borne road NVH can be cascaded down to three major systems: 1) vehicle body structure, 2) chassis/suspension, 3) tire/wheel. The forces at the body attachment points are controlled by the isolation efficiency of the chassis/suspension system and the excitation at the spindle/knuckle due to the tire/road interaction. The chassis force transmissibility is a metric to quantify the isolation efficiency. This paper presents a new experimental methodology to estimate the chassis force transmissibility from a fully assembled vehicle. For the calculation of the transmissibility, the spindle force/moment estimation and the conventional Noise Path Analysis (NPA) methodologies are utilized. A merit of the methodology provides not only spindle force to body force transmissibility but also spindle moment to body force transmissibility. Hence it enables us to understand the effectiveness of the spindle moments on the body forces.

The world urbanization is growing rapidly, bringing many challenges for people to move in dense metropolitan regions. Public transportation is not able to attend the whole demand, and individual transportation modes are struggling with traffic congestion and stringent regulations to reduce its attractiveness, such as the license plate restriction in São Paulo. On the other hand, enablers like smartphones mass penetration, GPS connected services and shared economy have opened space to a whole new range of possible solutions to improve people perception on urban mobility. This work aims to evaluate the modal choice behavior models and understand the success factor of current mobility solutions in the city of São Paulo. The data available through origin/destination researches will be used to validate the models used in this work.

Plug in hybrid electric vehicles (PHEVs) have gained interest over last decade due to their increased fuel economy and ability to displace some petroleum fuel with electricity from power grid. Given the complexity of this vehicle powertrain, the energy management plays a key role in providing higher fuel economy. The energy management algorithm on PHEVs performs the same task as a hybrid vehicle energy management but it has more freedom in utilizing the battery energy due to the larger battery capacity and ability to be recharged from the power grid. The state of charge (SOC) profile of the battery during the entire driving trip determines the electric energy usage, thus determining overall fuel consumption.

Many decisions need to be made when test track data is used to set up Squeak & Rattle evaluations of subsystems or components. These decisions are judgment-based so different people with different backgrounds and experience levels will make different decisions - few of which can be called right or wrong - but they are different which causes problems. Squeak & Rattle evaluation has become more scientific in recent years as subjective evaluation has been replaced by quantitative methods like N10 Loudness and shakers have become quiet. It is the authors' contention that the variations caused by different judgment calls can no longer be tolerated. Therefore a methodical process was developed which assures that different people will get the same results from the same set of test track data.

The traditional analysis of squeal noise for drum brakes is done in a separate approach, with CAE and laboratory/experimental techniques done independently or in a non-iterative sequential manner. In this paper, an innovative approach of directing the frequency response testing based on CAE is used and the overall process is embedded in a system approach. The drum brake design was changed to accomplish higher loads in a car. The initial results of the tests came out noise during the vehicle test. After retrieving the noisy parts from the vehicle, it was tested for frequency response, but in a directional manner suggested by the CAE model. This new approach hasn't been done before in industry practice. The CAE identified that two modes (around the noise frequency) swapped their orders compared to the old design and suggested design changes. The new design was evaluated with a mocked up prototype. This was followed by getting cast parts and testing them for frequency response.

In this paper, a new technology for the design of silent transaxles is developed, where topography optimization is adopted and an artificial parameter called β is proposed as an objective function, representing an upper bound of the surface velocity. The strategy of the optimization is to minimize β while getting the surface velocities less than β. as the constraints. A numerical example of reducing transaxle's radiated noise by using the new optimization technology is given in the paper. In the example, an entire Ford transaxle system was modeled numerically, where most internal components were included. First a modal frequency velocity analysis was conducted. Then an acoustic power analysis based on the Acoustic Transfer Vector (ATV) was carried out. Finally, a topography optimization based on the β - method for the transaxle was performed to minimize the radiated noise.

Air-conditioning (A/C) induced moan is a very commonly observed phenomenon in automotive refrigerant systems. Since most of the automotive A/C systems cycle ON/OFF four to six times every minute, the A/C induced moan is quite readily audible under engine idle and even while driving, especially under lower engine/vehicle speeds. It is not unusual for an A/C compressor to moan or not, on some vehicle/s under certain operating conditions. Most of the OEMs resolve or suppress the A/C moan potential to barely audible levels. However, under some unique and extreme operating conditions, A/C moan is quite readily induced and often results in customer complaints. This paper discusses A/C moan related root-causes, sources and paths of propagation. A systematic diagnostic test-procedure is also described to diagnose and develop the needed most cost-effective design-fixes. Finally, based on this case-study - some objective targets are recommended to suppress the A/C moan to acceptable levels.

Automated driving is currently one of the most active areas of research worldwide. While the general progress in developing specific algorithms for perception, planning and control tasks is very advanced, testing and validation of the resulting functions is still challenging due to the large number of possible scenarios and generation of ground-truth. Currently, real world testing and simulations are used in combination to overcome some of these challenges. While real world testing does not suffer from imperfect sensor models and environments, it is expensive, slow and not accurately repeatable and therefore unable to capture all possible scenarios. However, simulation models are not sophisticated enough to fully replace real world testing. In this paper, we propose a workflow that is capable of augmenting real sensor-level data with simulated sensor data.

In this paper, a CAE methodology based on a multiphysics approach for engine gear noise evaluation is reviewed. The method comprises the results and outputs from several different analytical domains to perform the noise risk assessment. The assessment includes the source-path analysis of the gear-induced rattling and whining noise. The vibration data from the exterior surface of the engine is extended through acoustic analysis to perform the engine noise simulation and to identify acoustic hot spots contributing to the noise. The study includes simulations under different engine loading conditions with results presented in both time and frequency domains. Various sensitivity analyses involving different gear geometries and micro-geometries are investigated as well. Finally, the simulation results from three different engines are compared vis-a-vis.

For Automated Vehicles (AVs) to be successful, they must integrate into society in a way that makes everyone confident in how AVs work to serve people and their communities. This integration requires that AVs communicate effectively, not only with other vehicles, but with all road users, including pedestrians and cyclists. One proposed method of AV communication is through an external human-machine interface (eHMI). While many studies have evaluated eHMI solutions, few have considered their compliance with relevant Federal Motor Vehicle Safety Standards (FMVSS) and their scalability. This study evaluated the effectiveness of a lightbar eHMI to communicate AV intent by measuring user comprehension of the eHMI and its impact on pedestrians’ trust and acceptance of AVs.

This paper proposes a low-cost but indirect method for occupancy detection and occupant counting purpose in current and future automotive systems. It can serve as either a way to determine the number of occupants riding inside a car or a way to complement the other devices in determining the occupancy. The proposed method is useful for various mobility applications including car rental, fleet management, taxi, car sharing, occupancy in autonomous vehicles, etc. It utilizes existing on-board motion sensor measurements, such as those used in the vehicle stability control function, together with door open and closed status. The vehicle’s motion signature in response to an occupant’s boarding and alighting is first extracted from the motion sensors that measure the responses of the vehicle body. Then the weights of the occupants are estimated by fitting the vehicle responses with a transient vehicle dynamics model.

In this paper, an approach to analyze voice recognition data to understand how customers use voice recognition systems is explored. The analysis will help identify ASR failures and usability related issues that customers encounter while using the voice recognition system. This paper also examines the impact of these failures on the individual speech domains (media control, phone, navigation, etc.). Such information can be used to improve the current voice recognition system and direct the design of future systems. Infotainment system logs, audio recordings of the voice interactions, their transcriptions and CAN bus data were identified to be rich sources of data to analyze voice recognition usage. Infotainment logs help understand how the system interpreted or responded to customer commands and at what confidence level.

The chain link and sprocket tooth impact during a meshing has been identified as the most significant noise source in a chain drive system. This paper first presents the theoretical derivation of the chain drive natural frequencies and mode shapes using the equations of motion from a stationary undamped chain drive system. The theoretical derivation shows the existence of three types of chain resonances, namely the transverse strand resonance, the longitudinal chain sprocket coupled resonance and the longitudinal chain stress wave type resonance. The chain-sprocket meshing noise is amplified when the chain sprocket meshing frequency corresponds to any one of the above mentioned chain drive system resonances. These theoretical results are then validated by a chain drive system CAE model using ABAQUS to identify the chain drive system resonances.

The business environment is ever changing, several innovations have allowed companies to transcend borderlines and become global entities. While the opportunities are numerous so are the challenges. In this fiercely competitive global marketplace, success requires companies to pay closer attention to supplier relations. The relationship between an automotive industry and its suppliers is an example of it, so the application of CAE (Computer Aided Engineering) superelement technique may improve, in terms of NVH (Noise, Vibration and Harshness), the vehicle development efficiency, without compromising confidentiality directives. Most of NVH requirements must be tracked through Transfer Functions (TFs) analyses at response points located on the Trimmed-Body Finite Element Model (FEM), as for example: Point Mobility, Vibration Transfer Function (VTF) and Acoustic Transfer Function (ATF).

Because of the need to safely vent exhaust gases, most engine dynamometer facilities are not well suited to measuring engine exhaust orifice noise. Depending on the location of the dyno facility within the building, the exhaust system may need to be extended in order to properly vent the exhaust fumes. This additional ducting changes the acoustic modes of the exhaust system which will change the measured orifice noise. Duct additions downstream of the original orifice location also alter the termination impedance such that in-duct pressure measurements with and without the extended exhaust system can vary significantly. In order to minimize the effect of the building's exhaust system on the desired engine exhaust system measurements, the present approach terminates the engine exhaust into a large enclosed volume or surge tank before venting the gases into the building's ventilation system.

Vehicle wind noise testing is usually done at elaborate tunnel facilities with minimal tunnel background noise, Techniques to reduce the tunnel noise, such as acoustic panels or improved fan systems, translate into higher costs for wind noise testing. We introduce an innovative procedure using an adaptive filtering algorithm to separate the tunnel noise from the wind noise inside the cabin of the vehicle. This new technique is capable of artificially reducing the tunnel background noise at low frequencies. Such a procedure has the potential to dramatically improve the wind noise testing capability of any wind tunnel, without the need for costly acoustic treatments.

Autonomous vehicles are expected to change our lives with significant applications like on-demand, shared autonomous taxi operations. Considering that most vehicles in a fleet are parked and hence idle resources when they are not used, shared on-demand services can utilize them much more efficiently. While ride hailing of autonomous vehicles is still very costly due to the initial investment, a shared autonomous vehicle fleet can lower its long-term cost such that it becomes economically feasible. This requires the Shared Autonomous Vehicles (SAV) in the fleet to be in operation as much as possible. Motivated by these applications, this paper presents a simulation environment to model and simulate shared autonomous vehicles in a geo-fenced urban setting.

The interaction of Connect and Automated vehicles (CAV) with regular vehicles in the traffic stream has been extensively researched. Most studies, however, focus on calibrating driver behavior models for CAVs based on various levels of automation and driver aggressiveness. Other related studies largely focus on the coordination of CAVs and infrastructure like traffic signals to optimize traffic. However, the effects of different strategic flow management of CAVs in the traffic stream in the comparative scenario-based analysis is understudied. Thus, this study develops a framework and simulations for integrating CAVs in a corridor section. We developed a calibrated model with CAVs for a corridor section in Corktown, Michigan, and simulate how dedicated CAV lane operations can be implemented without significant change in existing infrastructure.