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In future vehicles (e.g. fuel cell vehicles, hybrid electric vehicles), the electrical system will have an important impact on the mechanical systems in the car (e.g. powertrain, steering). Furthermore, this coupling will become increasingly important over time. In order to develop effective designs and appropriate control systems for these systems, it is important that the plant models capture the detailed physical behavior in the system. This paper will describe models of two electrical components, a battery and a supercapacitor, which have been modeled in two ways: (i) modeling the plant and controller using block diagrams in Simulink and (ii) modeling the plant and controller in Dymola followed by compiling this model to an S-function for simulation in Simulink. Both the battery and supercapacitor model are based on impedance spectroscopy measurements and can be used for highly dynamic simulations.

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.

An experimental study was conducted using a dynamic rollover component test system (ROCS) to study the effects of activating a pyro-mechanical buckle pre-tensioner and an electric retractor on the driver and front right passenger head and pelvis excursions. The ROCS is a unique system capable of producing vehicle responses that replicate four distinct phases of a tripped rollover: trip initiation, roll initiation, free-flight vehicle rotation, and vehicle to ground contact. This component test system consists of a rigid occupant compartment derived from a mid-size SUV with complete 1st row seating and interior trim, a simulated vehicle suspension system and an elastic vehicle-to-ground-contact surface. The ROCS system was integrated with a Deceleration Rollover Sled (DRS). Dynamic responses of the ROCS system, including both the rigid compartment and occupant, were measured and recorded.

Conventional cruise control systems in automotive applications are usually designed to maintain the constant speed of the vehicle based on the desired set-point. It has been shown that fuel economy while in cruise control can be improved using advanced control methods namely adopting the Model Predictive Control (MPC) technology utilizing the road grade preview information and allowance of the vehicle speed variation. This paper is focused on the extension of the Adaptive Nonlinear Model Predictive Controller (ANLMPC) reported earlier by application to the trailer tow use-case. As the connected trailer changes the aerodynamic drag and the overall vehicle mass, it may lead to the undesired downshifts for the conventional cruise controller introducing the fuel economy losses. In this work, the ANLMPC concept is extended to avoid downshifts by translating the downshift conditions to the constraints of the underlying optimization problem to be solved.

This paper presents an advanced yaw stability control system that uses a sensor set including an inertial measurement unit to sense the 6 degrees-of-freedom motions of a vehicle. The full degree of the inertial measurement unit improves and enhances the vehicle motion state estimation over the one in the traditional electronic stability controls. The addition of vehicle state estimation leads to the performance refinement of vehicle stability control that can improve performance in certain situations. The paper provides both detailed system description and test results showing the effectiveness of the system.

For realistic traffic modeling, real-world traffic calibration data is needed. These data include a representative road network, road users count by type, traffic lights information, infrastructure, etc. In most cases, this data is not readily available due to cost, time, and confidentiality constraints. Some open-source data are accessible and provide this information for specific geographical locations, however, it is often insufficient for realistic calibration. Moreover, the publicly available data may have errors, for example, the Open Street Maps (OSM) does not always correlate with physical roads. The scarcity, incompleteness, and inaccuracies of the data pose challenges to the realistic calibration of traffic models. Hence, in this study, we propose an approach based on spatial interpolation for addressing sparsity in vehicle count data that can augment existing data to make traffic model calibrations more accurate.

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.

This paper proposes a method to make diagnostic/prognostic judgment about the health of a tire, in term of its wear, using existing on-board sensor signals. The approach focuses on using an estimate of the effective rolling radius (ERR) for individual tires as one of the main diagnostic/prognostic means and it determines if a tire has significant wear and how long it can be safely driven before tire rotation or tire replacement are required. The ERR is determined from the combination of wheel speed sensor (WSS), Global Positioning sensor (GPS), the other motion sensor signals, together with the radius kinematic model of a rolling tire. The ERR estimation fits the relevant signals to a linear model and utilizes the relationship revealed in the magic formula tire model. The ERR can then be related to multiple sources of uncertainties such as the tire inflation pressure, tire loading changes, and tire wear.

With the emergence of Driving Automation Systems (SAE levels 1-5), the necessity arises for methods of evaluating these systems. However, these systems are much more challenging to evaluate than traditional safety features (SAE level 0). This is because an understanding of the Driving Automation system’s response in all possible scenarios is desired, but prohibitive to comprehensively test. Hence, this paper attempts to evaluate one such system, by modeling its behavior. The model generated parameters not only allow for objective comparison between vehicles, but also provide a more complete understanding of the system. The model can also be used to extrapolate results by simulating other scenarios without the need for conducting more tests. In this paper, low speed automated driving (also known as Traffic Jam Assist (TJA)) is studied. This study focused on the longitudinal behavior of automated vehicles while following a lead vehicle (LV) in traffic jam scenarios.

This paper examines the neck tension force (Fz) of the BioRid II dummy in the IIHS (Insurance Institute of Highway Safety) rear impact mode. The kinematics of the event is carefully reviewed, followed by a detailed theoretical analysis, paying particular attention to the upper neck tension force. The study reveals that the neck tension should be approximately 450N due to the head inertia force alone. However, some of the tests conducted by IIHS had neck tension forces as high as 1400N. The theory of head hooking and torso downward pulling is postulated in the paper, and various publicly available IIHS rear impact tests are examined against the theory. It is found in the analysis that in many of those tests with high neck tension forces, the locus of the head restraint reaction force travels on the dummy's skull cap, and eventually moves down underneath the skull cap, which causes “hooking” of the head on the stacked-up head restraint foam.

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.

Blunt impacts to the back of the torso can occur in vehicle crashes due to interaction with unrestrained occupants, or cargo in frontal crashes, or intrusion in rear crashes, for example. Six pendulum tests were conducted on the back of an instrumented 50th percentile male Hybrid III ATD (Anthropomorphic Test Device) to determine kinematic and biomechanical responses. The impact locations were centered with the top of a 15-cm diameter impactor at the T1 or at T6 level of the thoracic spine. The impact speed varied from 16 to 24 km/h. Two 24 km/h tests were conducted at the T1 level and showed repeatability of setup and ATD responses. The 16 and 24 km/h tests at T1 and T6 were compared. Results indicated greater head rotation, neck extension moments and neck shear forces at T1 level impacts. For example, lower neck extension was 2.6 times and 3.8 times greater at T1 versus T6 impacts at 16 and 24 km/h, respectively.

Hardware-in-the-Loop (HIL) test system-based development has been used throughout Ford Motor Company for some time. The development of control strategies for Hybrid Electric Vehicle (HEV) Electronic Control Units (ECU) has benefited from HIL-based testing. It has proven to be an efficient tool for HEV software strategy development, implementation and validation. The Ford HEV HIL system is a very flexible tool able to simulate the whole HEV control system. Ford's HEV HIL system is based on the capabilities of MathWorks tools, dSPACE ControlDesk1, and ATI Vision2 tools and has demonstrated excellent performance. Comprehensive strategy validation is probably the most time consuming and the most routine task for mature vehicle programs. The goal of this paper is to demonstrate how this task is automated for HEV programs at Ford Motor Company.

Oil formulation has been varied to modify oil viscosity characteristics; the effect on the rubbing friction losses of a 2.4litre diesel engine has been investigated for a range of temperatures from -20 to around 60°C. The aims of the study were first, to examine the extent to which viscosity alone determined the effect of formulation changes, and second, to define an effective viscosity to relate changes in viscosity due to formulation and temperature to changes in engine friction. This effective viscosity is based on cold cranking simulator measurements at -30°C, high temperature high shear viscosity at 150°C and kinematic viscosity measurements at three intermediate temperatures to define the variation with temperature. The effective viscosity has been described using a modified Vogel equation, which is presented.

The unpleasant noise (creak) originated from latch-striker interaction, perceived mainly when the vehicle is submitted to uneven road conditions is generated by stick-slip phenomenon mainly due materials incompatibility of contact surfaces. Generally, eliminate this incompatibility is unfeasible due technical and/or economics constrains; this scenario makes it necessary to act in other fronts to neutralize the effects of that incompatibility. Reduce the coefficient of friction from one of contact surfaces is an alternative that can be easily applied at striker through a thin thickness coating with that property.

Analysis of road accidents has shown that an important portion of fatal crashes involving Commercial Vehicles are caused by rollovers. ESC systems in Commercial Vehicles can reduce rollovers, severe understeer or oversteer conditions and minimize occurrences of jackknifing events. Several studies have estimated that this positive effect of ESC on road safety is substantial. In Europe, Electronic Stability Control (ESC) is expected to prevent by far the most fatalities and injuries: about 3,000 fatalities (-14%), and about 50,000 injuries (-6%) per year. In Europe, Electronic Stability Control Systems is mandatory for all vehicles (since Nov. 1st, 2011 for new types of vehicle and Nov. 1st, 2014 for all new vehicles), including Commercial Vehicles, Buses, Trucks and Trailers.