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The current approach for new Advanced Driver Assistance System (ADAS) and Connected and Automated Driving (CAD) function development involves a significant amount of public road testing which is inefficient due to the number miles that need to be driven for rare and extreme events to take place, thereby being very costly also, and unsafe as the rest of the road users become involuntary test subjects. A new development, evaluation and demonstration method for safe, efficient, and repeatable development, demonstration and evaluation of ADAS and CAD functions called Vehicle-in-Virtual –Environment (VVE) was recently introduced as a solution to this problem. The vehicle is operated in a large, empty, and flat area during VVE while its localization and perception sensor data is fed from the virtual environment with other traffic and rare and extreme events being generated as needed.

This paper discusses the development of the 1997 Jeep Cherokee model for the National Advanced Driving Simulator's planned vehicle dynamics software, NADSdyna. Recursive rigid body formalism called the Real Time Recursive Dynamics (RTRD) developed by the University of Iowa is used to model the front and rear suspension mechanisms. To complement vehicle dynamics for simulator applications, subsystems that include tires, aerodynamics, powertrain, brake, and steering are added to the rigid body dynamics model. These models provide high fidelity driving realism to simulate severe handling maneuvers in real time. The soundness of the model does not only depend on the mathematics of the model, but also on the validity of the parameters. Therefore, this paper discusses thoroughly the methodology of parameters estimation. A generic model of cruise control is included.

The paper discusses the development of a vehicle dynamics model and model validation of the 2003 Ford Expedition in CarSim. The accuracy of results obtained from simulations depends on the realism of the model which in turn depends on the measured data used to define the model parameters. The paper describes the tests used to measure the vehicle data and also gives a detailed account of the methodology used to determine parameters for the CarSim Ford Expedition model. The vehicle model was validated by comparing simulation results with experimental testing. Bounce and Roll tests in CarSim were used to validate the suspension and steering kinematics and compliances. Field test data of the Sine with Dwell maneuver was used for the vehicle model validation. The paper also discusses the development of a functional electronic stability control system and its effect on vehicle handling response in the Sine with Dwell maneuver.

The paper discusses the development of a model of the 2003 Ford Expedition using ADAMS View and its validation with experimental data. The front and rear suspensions are independent double A-arm type suspensions modeled using rigid links and ideal joints. The suspension springs and shock absorbers are modeled as force elements. The plots comparing the experimental tests and the simulation results are shown in this paper. Quasi-static roll and bounce tests are used to validate the suspension characteristics of the model while the Sine with Dwell and Slowly Increasing Steer maneuvers are used to validate the vehicle handling and tire-road interaction characteristics of the model. This paper also details the incorporation of an ESC model, originally developed by Kinjawadekar et al. [2] for CarSim, with the ADAMS model. The ESC is modeled in Simulink and co-simulated with the ADAMS vehicle model. Plots validating the ESC model with experimental data are also included.

This research focused on developing a methodology for a vehicle dynamics model of a passenger vehicle outfitted with an aftermarket Automated Driving System software package using only literature and track based results. This package consisted of Autoware.AI (Autoware ®) operating on Robot Operating System 1 (ROS™) with C++ and Python ®. Initial focus was understanding the basics of ROS and how to implement test scenarios in Python to characterize the control systems and dynamics of the vehicle. As understanding of the system continued to develop, test scenarios were adapted to better fit system characterization goals with identification of system configuration limits. Trends from on-track testing were identified and paired with first-order linear systems to simulate physical vehicle responses to given command inputs. Sub-models were developed and simulated in MATLAB ® with command inputs from on-track testing.

The tractor trailer models discussed in this paper were for a real-time hardware-in-the-loop (HIL) simulation to test heavy truck electronic stability control (ESC) systems [1]. The accuracy of the simulation results relies on the fidelity and accuracy of the vehicle parameters used. However in this case where hardware components are part of the simulation, their accuracy also affects the proper working of the simulation and ESC unit. Hence both the software and hardware components have to be validated. The validation process discussed in this paper is divided into two sections. The first section deals with the validation of the TruckSim vehicle model, where experimental data is compared with simulation results from TruckSim. Once the vehicle models are validated, they are incorporated in the HIL simulation and the second section discusses the validation of the whole HIL system with ESC.

The aim of this paper is to describe a unified approach to modeling the energy efficiency and power flow characteristics of energy storage and energy conversion elements used in hybrid vehicles. Hybrid vehicle analysis and design is concerned with the storage of energy in three domains - chemical, mechanical, and electrical - and on energy conversions between these domains. The paper presents the physical and mathematical basis of this modeling approach, as well as a modular simulator that embodies the same basic principles. The use of the simulator as an analysis tool is demonstrated through the conceptual design of a sport-utility hybrid drivetrain.

It has been discussed in numerous prior studies that in-neutral coasting, or sailing, can accomplish considerable amount of fuel saving when properly used. The driving maneuver basically makes the vehicle sail in neutral gear when propulsion is unnecessary. By disengaging a clutch or shifting the gear to neutral, the vehicle may better utilize its kinetic energy by avoiding dragging from the engine side. This strategy has been carried over to series production recently in some of the vehicles on the market and has become one of the eco-mode features available in current vehicles. However, the duration of coasting must be long enough to attain more fuel economy benefit than Deceleration Fuel Cut-Off (DFCO) - which exists in all current vehicle powertrain controllers - can bring. Also, the transients during shifting back to drive gear can result in a drivability concern.

Autonomous vehicle technology has been developing rapidly in recent years. Vehicle parametric uncertainty in the vehicle model, variable time delays in the CAN bus based sensor and actuator command interfaces, changes in vehicle sped, sensitivity to external disturbances like side wind and changes in road friction coefficient are factors that affect autonomous driving systems like they have affected ADAS and active safety systems in the past. This paper presents a robust control architecture for automated driving systems for handling the abovementioned problems. A path tracking control system is chosen as the proof-of-concept demonstration application in this paper. A disturbance observer (DOB) is embedded within the steering to path error automated driving loop to handle uncertain parameters such as vehicle mass, vehicle velocities and road friction coefficient and to reject yaw moment disturbances.

Typically, the combustion analysis for S.I. engines is limited to the determination of the apparent heat release from in-cylinder pressure measurements, effectively using a single zone approach with constant properties determined at some average temperature. In this paper, we follow an approach consistent with the engine modeling approach (i.e., reverse modeling) to extract heat release rate from combustion pressure data. The experimental data used here solely consists of quantities measured in a typical engine dynamometer tests, namely the crank-angle resolved cylinder pressure, as well as global measurements of the A/F ratio, engine speed, load, EGR, air mass flow rate and temperature and exhaust emissions. We then perform a two-zone, crank-angle resolved analysis of the pressure data using variable composition and properties.

The 2nd Automotive CFD Prediction workshop (AutoCFD2) was organized to improve the state-of-the-art in automotive aerodynamic prediction. It is the mission of the workshop organizing committee to drive the development and validation of enhanced CFD methods by establishing publicly available standard test cases for which high quality on- and off-body wind tunnel test data is available. This paper reports on the AutoCFD2 workshop for the Ford DrivAer test case. Since its introduction, the DrivAer quickly became the quasi-standard for CFD method development and correlation. The Ford DrivAer has been chosen due to the proven, high-quality experimental data available, which includes integral aerodynamic forces, 209 surface pressures, 11 velocity profiles and 4 flow field planes. For the workshop, the notchback version of the DrivAer in a closed cooling, static floor test condition has been selected.

Fiber reinforced structural composites will play a key role in the development of the next generation of transportation vehicles (passenger cars, vans, light trucks and heavy trucks) due to their high strength-to-weight and stiffness-to-weight ratio compared to metals. An integrated assessment of the durability, reliability, and affordability of these materials is critical to facilitate the inclusion of these materials into new designs. The result of this assessment should provide information to find the balance between the three performance measures. This paper describes a method to develop this assessment in the fabrication of sheet molding compound (SMC) parts, and discusses the concept of Preform Insert Assembly (PIA) for improved affordability in the manufacturing of composite parts.

This year, in the third year of FutureTruck competition, the Ohio State University team has taken the challenge to convert a 2002 Ford Explorer into a more fuel efficient and environmentally friendly SUV. This goal was achieved by use of a post-transmission, charge sustaining, parallel hybrid diesel-electric drivetrain. The main power source is a 2.5-liter, 103 kW advanced CIDI engine manufactured by VM Motori. A 55 kW Ecostar AC induction electric motor provides the supplemental power. The powertrain is managed by a state of the art supervisory control system which optimizes powertrain characteristics using advanced energy management and emission control algorithms. A unique driver interface implementing advanced telematics, and an interior designed specifically to reduce weight and be more environmentally friendly add to the utility of the vehicle as well as the consumer appeal.

The Ohio State University EcoCAR 3 team is building a plug-in hybrid electric vehicle (PHEV) post-transmission parallel 2016 Chevrolet Camaro. With the end-goal of improving fuel economy and reducing tail pipe emissions, the Ohio State Camaro has been fitted with a 32 kW alternator-starter belt coupled to a 119 kW 2.0L GDI I4 engine that runs on 85% ethanol (E85). The belted alternator starter (BAS) which aids engine start-stop operation, series mode and torque assist, is powered by an 18.9 kWh Lithium Iron Phosphate energy storage system, and controlled by a DC-AC inverter/controller. This report details the modeling, calibration, testing and validation work done by the Ohio State team to fast track development of the BAS system in Year 2 of the competition.

Most do not consider there to be a risk in pushing on, bumping into or falling against an elevator door from the hallway side. However, the lack of the elevator cars presence alone, and the potential for severe injury or even death make this seemingly mundane situation potentially critical. Standards exist relative to such situations, and past and current designs attempt to account for this possibility, still people get injured interacting with these doors every year. In order to evaluate a real-world elevator door system's ability to withstand the quasi-static and impactive loads that can be placed on it by the general public during its life, both intentionally and unintentionally, a predictive tool is needed. This work represents the combination of empirical laboratory testing and numerical modeling of a typical elevator door system exposed to quasi-static and dynamic loading.

This paper describes a systematic approach to identify the best sensor combination by performing sensor placement analysis to detect and isolate clutch stuck-off faults in Automatic Transmissions (AT) based on structural analysis. When an engaged clutch in the AT loses pressure during operation, it is classified as a clutch stuck-off fault. AT can enter in neutral state because of these faults; causing loss of power at wheels. Identifying the sensors to detect and isolate these faults is important in the early stage of the AT development. A universal approach to develop a structural model of an AT is presented based on the kinematic relationships of the planetary gear set elements. Sensor placement analysis is then performed to determine the sensor locations to detect and isolate the clutch stuck-off faults using speed sensors and clutch pressure sensors. The proposed approach is then applied to a 10-Speed AT to demonstrate its effectiveness.

Previously-reported draw-bend tests showed large discrepancies in springback angles from those predicted by two-dimensional finite element modeling (FEM). In some cases, the predicted angle was several times the measured angle. With more careful 3-D simulation taking into account anticlastic curvature, a significant discrepancy persisted. In order to evaluate the role of the Bauschinger Effect in springback, a transient hardening model was constructed based on novel tension-compression tests for for three sheet materials: drawing-quality steel (baseline material), high-strength low-alloy steel, and 6022-T4 aluminum alloy. This model reproduces the main features of hardening following a strain reversal: low yield stress, rapid strain hardening, and, optionally, permanent softening or hardening relative to the monotonic hardening law. The hardening law was implemented and 3-D FEM was carried out for comparison with the draw-bend springback results.

With the advent of increasing autonomous vehicles on public roads, the safety of vulnerable road users such as pedestrians, cyclists, etc. has never been more important. These especially include Blind or Visually Impaired (BVI) pedestrians who face difficulty in making confident decisions in road crossings without the help of accessible pedestrian signals (APS). This paper addresses some of the safety measures that can be taken to improve and assess the safety of BVI pedestrians in a controlled environment like a BVI school campus where autonomous vehicles are operated. The majority of research on autonomous vehicle safety does not consider the edge cases of encounters with BVI pedestrians. Based on this motivation, requirements and characteristics of Non-BVI and BVI pedestrians have been stated along with the motion models used to predict their future movements. Existing tools based on Bayesian multi-model filters were used for pedestrian tracking and motion predictions.

Automated Driving Systems (ADS) make the driving experience safer, more efficient, and comfortable by performing complex maneuvers, preempting potential risky situations, or taking over the driver’s tasks in critical situations. Innovation acceptance research for Advanced Driver Assistance Systems (ADAS) illustrates the increasing demand for safety and comfort as the two prime movers of the ADAS market. Since ADAS technologies have significant impact on human lives, extensive testing and validation throughout the design process is indispensable. Due to complexity of systems, cost of testing, and safety of test engineers, a significant chunk of ADAS calibration and validation needs to be done virtually. Although simulation-based verification and validation (V&V) is not new, the test descriptions, modeling and simulation framework are not yet well established. Off-the-shelf software tools have different architectures, simulation procedures, data standardizations, and tradeoffs.

Interest in pedestrian head injury has prompted a need to measure the potential of head injury resulting from vehicular impacts. A variety of head impactors have been developed to fulfill this measurement need. A protocol has been developed by the International Harmonization Research Activity (IHRA) to use head impactor measurements to predict head injury. However, the effect of certain characteristics of the various head impactors on the measurement procedure is not well understood. This includes the location of the accelerometers within the head-form and testing the head-form under the variety of conditions necessary to establish its global performance. To address this problem, a simple model of the IHRA head-form has been developed. This model was created using MADYMO© and consists of a solid sphere with a second sphere representing the vinyl covering. Stiffness and damping characteristics of the vinyl covering were determined analytically from drop test data of an IHRA head-form.