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There has been a keen interest in recent times on implementation of lightweight materials in vehicles to bring down the unladen weight of a vehicle for enhancing fuel efficiency. Fiber-reinforced composites comprise a class of such materials. As sustainability is also a preoccupation of current product development engineers including vehicle designers, bio-composites based on natural fibers are receiving a special attention. Keeping these motivations of lower effective density, environment friendliness and occupational safety in mind, woven jute fabric based composites have been recently studied as potential alternatives to glass fiber composites for structural applications in automobiles. In the past, mechanical characterization of jute-polyester composites were restricted to obtaining their stress-strain behaviors under quasi-static conditions.

Adhesively bonded steel hat section components have been experimentally studied in the past as a potential alternative to traditional hat section components with spot-welded flanges. One of the concerns with such components has been their performance under axial impact loading as adhesive is far more brittle as compared to a spot weld. However, recent drop-weight impact tests have shown that the energy absorption capabilities of adhesively bonded steel hat sections are competitive with respect to geometrically similar spot-welded specimens. Although flange separation may take place in the case of a specimen employing a rubber toughened epoxy adhesive, the failure would have taken place post progressive buckling and absorption of impact energy.

Vehicle safety systems may use occupant physiological information, e.g., occupant heights and weights to further enhance occupant safety. Determining occupant physiological information in a vehicle, however, is a challenging problem due to variations in pose, lighting conditions and background complexity. In this paper, a novel occupant height estimation approach is presented. Depth information from a depth camera, e.g., Microsoft Kinect is used. In this 3D approach, first, human body and frontal face views (restricted by the Pitch and Roll values in the pose estimation) based on RGB and depth information are detected. Next, the eye location (2D coordinates) is detected from frontal facial views by Haar-cascade detectors. The eye-location co-ordinates are then transferred into vehicle co-ordinates, and seated occupant eye height is estimated according to similar triangles and fields of view of Kinect.

Cold starting problems of diesel engines are caused mainly by the failure of the auto-ignition process or the subsequent combustion of the rest of the charge. The problems include long cranking periods and combustion instability leading to an increase in fuel consumption in addition to the emission of undesirable unburned hydrocarbons which appear in the exhaust as white smoke. The major cause of these problems is the low temperature and pressure of the charge near the end of the compression stroke and/or the poor ignition quality of the fuel. This paper presents the results of an experimental investigation of cold starting of a high speed diesel engine with ULSD (Ultra Low Sulphur Diesel) and JP8 (Jet Propulsion) fuels at ambient temperature (25°C). A detailed analysis is made of the autoignition and combustion of the two fuels in the first few cycles in the cold start transient. In addition, a comparison is made between these processes for the two fuels during idle operation.

Numerical simulations of diesel reacting jets in a simulated engine environment were carried out to study the effect of oxygen concentration on the ignition delay time and lift-off length dynamics. A recently developed mechanism, direct integration of chemistry, and well established Lagrangian-Eulerian spray model were utilized for 3-D turbulent spray combustion simulation under engine like conditions. The simulations are able to provide a time-history of chemical species including formaldehyde CH2O intermediates and hydroxide OH radicals to facilitate development of auto-ignition and lift off length numerical diagnostics. A range of important operating points including variations in the oxygen concentration, rail pressure, and injection duration were examined. The purpose of conducting the parametric studies is to investigate the consistency of the results and provide a more comprehensive analysis than a single point condition.

The superior fuel economy of direct injection internal combustion engines (diesel and gasoline) is related to use of a high compression ratio to auto-ignite the fuel and the overall lean combustible mixture. Two of the major problems in diesel engine emissions are the NOx and soot emissions, which are caused by the heterogeneity of the charge and the properties of the diesel fuel. Conventional Direct Injection Spark Ignition Gasoline engines don't have these problems because of the fuel properties particularly its volatility. However, its efficiency and specific power output are limited by the knock, knock produced preignition and the sporadic preignition phenomenon. The Gasoline Direct Injection Compression Ignition (GDICI) engine combines the superior features of the two engines by increasing the compression ratio and use of gasoline as a fuel.

Computational human body models, especially detailed finite element models are suitable for investigation of human body kinematic responses and injury mechanism. A real-world lateral vehicle-tree impact accident was reconstructed by using finite element method according to the accident description in the CIREN database. At first, a baseline vehicle FE model was modified and validated according to the NCAP lateral impact test. The interaction between the car and the tree in the accident was simulated using LS-Dyna software. Parameters that affect the simulation results, such as the initial pre-crash speed, impact direction, and the initial impact location on the vehicle, were analyzed. The parameters were determined by matching the simulated vehicle body deformations and kinematics to the accident reports.

This paper details the development of the control algorithms to characterize the behavior of an electrohydraulic actuated dry clutch used in the powertrain of the Wayne State University EcoCAR 3 Pre-Transmission Parallel hybrid vehicle. The paper describes the methodology and processes behind the development of the clutch physical model and electronic control unit to support the calibration of the vehicle’s hybrid supervisory controller. The EcoCAR 3 competition challenges sixteen North American universities to re-engineer the 2016 Chevrolet Camaro to reduce its environmental impact without compromising its performance and consumer acceptability. The team is in final stages of Year Two competition, which focuses on the powertrain components integration into the selected hybrid architecture. The dry clutch used by the team to enable the coupling between the engine and the electric motor is a key component of the Pre-Transmission Parallel configuration.

This paper details the development of a test-bench simulation to characterize the behavior of an electro-hydraulic actuated dry clutch used in a pre-transmission parallel hybrid powertrain architecture of Wayne State University EcoCAR 3. Engage and disengage systems play a crucial role in a pre-transmission parallel hybrid architecture. The most common device used to meet the purpose of physically connecting internal combustion engine and electric powertrains is a dry clutch. Its own characteristics and capabilities allow its usage for this application. The transition between the pure electric and hybrid modes is dictated by the main control strategy. Therefore, the engaging system will be widely used when switching from charge depleting to charge sustaining mode, and vice versa. In addition, when torque is required from both sources for higher performance, the clutch will be responsible for mechanically connecting both torque sources.

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.

The Dimensional Model of Driver Demand is extended to include Auditory-Vocal (i.e., pure “voice” tasks), and Mixed-Mode tasks (i.e., a combination of Auditory-Vocal mode with visual-only, or with Visual-Manual modes). The extended model was validated with data from 24 participants using the 2014 Toyota Corolla infotainment system in a video-based surrogate driving venue. Twenty-two driver performance metrics were collected, including total eyes-off-road time (TEORT), mean single glance duration (MSGD), and proportion of long single glances (LGP). Other key metrics included response time (RT) and miss rate to a Tactile Detection Response Task (TDRT). The 22 metrics were simplified using Principal Component Analysis to two dimensions. The major dimension, explaining 60% of total variance, we interpret as the attentional effects of cognitive demand. The minor dimension, explaining 20% of total variance, we interpret as physical demand.

This paper details the first year of modeling and simulation, and powertrain control development for the Wayne State University EcoCAR 3 vehicle. Included in this paper are the processes for developing simulation platforms, plant models and electronic control units to support the supervisory control system development. The EcoCAR 3 competition challenges sixteen North American universities to re-engineer the 2016 Chevrolet Camaro to reduce its environmental impact without compromising its performance and consumer acceptability. The team is in the final stages of competition Year One, which, as the “non-vehicle year,” focuses on the preliminary design, simulation, and hybrid modes selection for the team’s selected vehicle architecture. The team chose a Pre-Transmission Parallel Plug-in Hybrid Electric Vehicle (PHEV) architecture for its performance capability, multiplicity of operational modes, and drivetrain configuration that retains the vehicle’s rear-wheel drive configuration.

The objective of the research into modeling and simulation was to provide an improvement to the Wayne State EcoCAR 2 team’s math-based modeling and simulation tools for hybrid electric vehicle powertrain analysis, with a goal of improving the simulation results to be less than 10% error to experimental data. The team used the modeling and simulation tools for evaluating different outcomes based on hybrid powertrain architecture changes (hardware), and controls code development and testing (software). The first step was model validation to experimental data, as the plant models had not yet been validated. This paper includes the results of the team’s work in the U.S. Department of Energy’s EcoCAR 2 Advanced vehicle Technical Competition for university student teams to create and test a plug-in hybrid electric vehicle for reducing petroleum oil consumption, pollutant emissions, and Green House Gas (GHG) emissions.

At the collision moment, a driver’s lower extremity will be in different foot position, which leads to the different posture of the lower extremity with various muscle activations. These will affect the driver’s injury during collision, so it is necessary to investigate further. A simulated collision scene was constructed, and 20 participants (10 male and 10 female) were recruited for the test in a driving simulator. The braking posture and muscle activation of eight major muscles of driver’s lower extremity (both legs) were measured. The muscle activations in different postures were then analyzed. At the collision moment, the right leg was possible to be on the brake (male, 40%; female, 45%), in the air (male, 27.5%; female, 37.5%) or even on the accelerator (male, 25%; female, 12.5%). The left leg was on the floor all along.

To help predict the injury responses of child pedestrians and occupants in traffic incidents, finite element (FE) modeling has become a common research tool. Until now, there was no whole-body FE model for 10-year-old (10 YO) children. This paper introduces the development of two 10 YO whole-body pediatric FE models (named CHARM-10) with a standing posture to represent a pedestrian and a seated posture to represent an occupant with sufficient anatomic details. The geometric data was obtained from medical images and the key dimensions were compared to literature data. Component-level sub-models were built and validated against experimental results of post mortem human subjects (PMHS). Most of these studies have been mostly published previously and briefly summarized in this paper. For the current study, focus was put on the late stage model development.

With increasing interest to reduce the dependency on gasoline and diesel, alternative energy source like compressed natural gas (CNG) is a viable option for internal combustion engines. Spark-ignited (SI) CNG engine is the simplest way to utilize CNG in engines, but direct injection (DI) Diesel-CNG dual-fuel engine is known to offer improvement in combustion efficiency and reduction in exhaust gases. Dual-fuel engine has characteristics similar to both SI engine and diesel engine which makes the combustion process more complex. This paper reports the computational fluid dynamics simulation of both DI dual-fuel compression ignition (CI) and SI CNG engines. In diesel-CNG dual-fuel engine simulations and comparison to experiments, attention was on ignition delay, transition from auto-ignition to flame propagation and heat released from the combustion of diesel and gaseous fuel, as well as relevant pollutants emissions.

In this work, a pseudo three-dimensional coupled thermal-electrochemical model is established to estimate the heat generation and temperature profiles of a lithium ion battery as functions of the state of the discharge. Then, this model is used to investigate the effectiveness of active and passive thermal management systems. The active cooling system utilizes cooling plate and water as the working fluid while the passive cooling system incorporates a phase change material (PCM). The thermal effects of coolant flow rate examined using a computational fluid dynamics model. In the passive cooling system, Paraffin wax used as a heat dissipation source to control battery temperature rise. The effect of module size and battery spacing is studied to find the optimal weight of PCM required. The results show that although the active cooling system has the capability to reduce the peak temperatures, it leads to a large temperature difference over the battery module.

The present work is concerned with the objective of design optimization of an automotive front end structure meeting both occupant and pedestrian safety requirements. The main goal adopted here is minimizing the mass of the front end structure meeting the safety requirements without sacrificing the performance targets. The front end structure should be sufficiently stiff to protect the occupant by absorbing the impact energy generated during a high speed frontal collision and at the same time it should not induce unduly high impact loads during a low speed pedestrian collision. These two requirements are potentially in conflict with each other; however, there may exist an optimum design solution, in terms of mass of front end structure, that meets both the requirements.

Periprosthetic fractures refer to the fractures that occur in the vicinity of the implants of joint replacement arthroplasty. Most of the fractures during an automotive frontal collision involve the long bones of the lower limbs (femur and tibia). Since the prevalence of persons living with lower limb joint prostheses is increasing, periprosthetic fractures that occur during vehicular accidents are likely to become a considerable burden on health care systems. It is estimated that approximately 4.0 million adults in the U.S. currently live with Total Knee Replacement (TKR) implants. Therefore, it is essential to study the injury patterns that occur in the long bone of a lower limb containing a total knee prosthesis. The aim of the present study is to develop an advanced finite element model that simulates the possible fracture patterns that are likely during vehicular accidents involving occupants who have knee joint prostheses in situ.

This paper represents the development of a new design methodology based on data mining theory for decision making in vehicle crashworthy components (or parts) development. The new methodology allows exploring the big crash simulation dataset to discover the underlying complicated relationships between vehicle crash responses and design variables at multi-levels, and deriving design rules based on the whole vehicle safety requirements to make decisions towards the component and sub-component level design. The method to be developed will resolve the issue of existing design approaches for vehicle crashworthiness, i.e. limited information exploring capability from big datasets, which may hamper the decision making and lead to a nonoptimal design. A preliminary design case study is presented to demonstrate the performance of the new method. This method will have direct impacts on improving vehicle safety design and can readily be applied to other complex systems.