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Previous study suggested that female, thin, obese, and older occupants had a higher risk of death and serious injury in motor vehicle crashes. Human body finite element models were a valuable tool in the study of injury biomechanics. The mesh deformation method based on radial basis function(RBF) was an attractive alternative for morphing baseline model to target models. Generally, when a complex model contained many elements and nodes, it was impossible to use all surface nodes as landmarks in RBF interpolation process, due to its prohibitive computational cost. To improve the efficiency, the current technique was to averagely select a set of nodes as landmarks from all surface nodes. In fact, the location and the number of selected landmarks had an important effect on the accuracy of mesh deformation. Hence, how to select important nodes as landmarks was a significant issue. In the paper, an efficient peak point-selection RBF mesh deformation method was used to select landmarks.

To address the need of increasing fuel economy requirements, automotive Original Equipment Manufacturers (OEMs) are increasing the number of turbocharged engines in their powertrain line-ups. The turbine-driven technology uses a forced induction device, which increases engine performance by increasing the density of the air charge being drawn into the cylinder. Denser air allows more fuel to be introduced into the combustion chamber, thus increasing engine performance. During the inlet air compression process, the air is heated to temperatures that can result in pre-ignition resulting and reduced engine functionality. The introduction of the charge air cooler (CAC) is therefore, necessary to extract heat created during the compression process. The present research describes the physics and develops the optimized simulation method that defines the process and gives insight into the development of CACs.

The Wayne State University student team reengineered a mid-sized sedan into a functional plug-in hybrid electric vehicle as participants in the EcoCAR 2 competition sponsored by the US Department of Energy and managed by Argonne National Laboratory. The competition goals included reducing petroleum usage, emissions, and energy consumption through implementing advanced vehicle technologies. During the competition, the team did plug-in charging of the 19 kWh high voltage traction battery, drove in pure electric mode (engine off) until the battery was depleted, then switched to hybrid mode and continued driving by using E85 from the fuel tank. The pure electric mode vehicle driving range was 48 km [30 miles] while pulling an emissions instrumented test trailer and projected to be 58 km [36 miles] without the test trailer load for the competition's city/highway blend drive cycle.

It is well known that thermal management is a key factor in design and performance analysis of Lithium-ion (Li-ion) battery, which is widely adopted for hybrid and electric vehicles. In this paper, an air cooled battery thermal management system design has been proposed and analyzed for mild hybrid vehicle application. Computational Fluid Dynamics (CFD) analysis was performed using CD-adapco's STAR-CCM+ solver and Battery Simulation Module (BMS) application to predict the temperature distribution within a module comprised of twelve 40Ah Superior Lithium Polymer Battery (SLPB) cells connected in series. The cells are cooled by air through aluminum cooling plate sandwiched in-between every pair of cells. The cooling plate has extended the cooling surface area exposed to cooling air flow. Cell level electrical and thermal simulation results were validated against experimental measurements.

Low back pain has a higher prevalence among drivers who have long term history of vehicle operations. Vehicle vibration has been considered to contribute to the onset of low back pain. However, the fundamental mechanism that relates vibration to low back pain is still not clear. Little is known about the relationship between vibration exposure, the biomechanical response, and the physiological responses of the seated human. The aim of this study was to determine the vibration frequency that causes the increase of muscle activity that can lead to muscle fatigue and low back pain. This study investigated the effects of various vibration frequencies on the lumbar and thoracic paraspinal muscle responses among 11 seated volunteers exposed to sinusoidal whole body vibration varying from 4Hz to 30Hz at 0.4 g of acceleration. The accelerations of the seat and the pelvis were recorded during various frequency of vibrations. Muscle activity was measured using electromyography (EMG).

As advanced electronic technology continues to be integrated into in-vehicle and portable devices, it is important to understand how drivers handle multitasking in order to maintain safe driving while reducing driver distraction. NHTSA has made driver distraction mitigation a major initiative. Currently, several types of Detection Response Tasks (DRTs) for assessing selective attention by detecting and responding to visual or tactile events while driving have been under development by an ISO WG8 DRT group. Among these DRTs, the tactile version (TDRT) is considered as a sensitive surrogate measure for driver attention without visual-manual interference in driving, according to the ISO DRT Draft Standard. In our previous study of cognitive demand, our results showed that the TDRT is the only surrogate DRT task with an acute sensitivity to a cognitive demand increase in an auditory-vocal task (i.e., n-Back verbal working memory task).

Hybrid electric vehicle (HEV) is one of the most highly pursued technologies for improving energy efficiency while reducing harmful emissions. Thermal modeling and control play an ever increasing role with HEV design and development for achieving the objective of improving efficiency, and as a result of additional thermal loading from electric powertrain components such as electric motor, motor controller and battery pack. Furthermore, the inherent dual powertrains require the design and analysis of not only the optimal operating temperatures but also control and energy management strategies to optimize the dynamic interactions among various components. This paper presents a complete development process and simulation results for an efficient modeling approach with integrated control strategy for the thermal management of plug-in HEV in parallel-through-the road (PTTR) architecture using a flexible-fuel engine running E85 and a battery pack as the energy storage system (ESS).

The Wayne State University (WSU) EcoCAR2 student team is investigating powertrain optimizations as a part of their participation in the EcoCAR2 design competition for the conversion of a 2013 Chevrolet Malibu into a plug-in hybrid. EcoCAR2 is the current three-year Department of Energy (DoE) Advanced Vehicle Technical Competition (AVTC) for 15 select university student teams competing on designing, building, and then optimizing their Plug-In Hybrid conversions of GM donated vehicles. WSU's powertrain design provides for approximately 56-64 km (35-40 miles) of electric driving before the Internal Combustion Engine (ICE) powertrain is needed. When the ICE is started, the ICE traditionally goes through a cold start with the engine, transmission, and final drive all at ambient temperature. The ICE powertrain components are most efficient when warmed up to their normal operating temperature, typically around 90-100 °C.

Vehicle weight-driven design comes amid rising higher fuel efficiency standards and must meet the criteria—pass proving ground (PG) test events that are equivalent to customer usage. Computer-aided engineering (CAE) fatigue analysis for PG is a successful push behind to digitally simulate vehicle durability performance with high fidelity. The need for vehicle weight reduction often arises in the vehicle development final phases when CAE methods, time, and tangible cost-effective opportunities are limited or nonexistent. In this research, a new CAE methodology is developed to identify opportunities for lightweight hole placement in the chassis structure and deliver a cost-effective lightweight solution with no additional impact on fatigue life. The successful application of this new methodology exhibits the effectiveness of the truck frame, which is the key chassis structure to support the body, suspension, and powertrain.

The adoption of lithium-ion batteries in vehicle electrification is fast growing due to high power and energy demand on hybrid and electric vehicles. However, the battery overall performance changes with time through the vehicle life. This paper investigates the electric vehicle battery cell aging under different usages. Battery cell experimental data including open circuit voltage and internal resistance is utilized to build a typical electric vehicle model in the AVL-Cruise platform. Four driving cycles (WLTP, UDDS, HWFET, and US06) with different ambient temperatures are simulated to acquire the battery cell terminal currents. These battery cell terminal current data are inputs to the MATLAB/Simulink battery aging model. Simulation results show that battery degrades quickly in high ambient temperatures. After 15,000 hours usage in 50 degrees Celsius ambient temperature, the usable cell capacity is reduced up to 25%.

Due to the variation of compartment design and occupant’s posture in self-driving cars, there is a new and major challenge for occupant protection. In particular, the studies on occupant restraint systems used in the self-driving car have been significantly delayed compared to the development of the autonomous technologies. In this paper, a numerical study was conducted to investigate the effectiveness of three typical restraint systems on the driver protection in three different scenarios.

There is little agreement in the field of driving safety as to how to define cognitive distraction, much less how to measure it. Without a definition and metric, it is impossible to make scientific and engineering progress on determining the extent to which cognitive distraction causes crashes, and ways to mitigate it if it does. We show here that different studies are inconsistent in their definitions of cognitive distraction. For example, some definitions do not include cellular conversation, while others do. Some definitions confound cognitive distraction with visual distraction, or cognitive distraction with cognitive workload. Other studies define cognitive distraction in terms of a state of the driver, and others in terms of tasks that may distract the driver. It is little wonder that some studies find that cognitive distraction is a negligible factor in causing crashes, while others assert that cognitive distraction causes more crashes than drunk driving.

Anti-vehicular (AV) landmines and improvised explosive devices (IED) have accounted for more than half of the United States military hostile casualties and wounded in Operation Iraqi Freedom (OIF) (Department of Defense Personnel & Procurement Statistics, 2009). The lower extremity is the predominantly injured body region following an AV mine or IED blast accounting for 26 percent of all combat injuries in OIF (Owens et al., 2007). Detonations occurring under the vehicle transmit high amplitude and short duration axial loads onto the foot-ankle-tibia region of the occupant causing injuries to the lower leg. The current effort was initiated to develop lower extremity injury criteria for occupants involved in underbelly blast impacts. Eighteen lower extremity post mortem human specimens (PMHS) were instrumented with an implantable load cell and strain gages and impacted at one of three incrementally severe AV axial loading conditions.

This paper describes the results of a project to develop a MADYMO occupant model for predicting thoracolumbar (TL) spine injuries during frontal impacts in the Indianapolis-type racing car (ITRC) environment and to study the effect of seat back angle, shoulder belt mounting location, leg hump, and spinal curvature on the thoracolumbar region. The newly developed MADYMO Race Car Driver Model (RCDM) is based on the Hybrid III, 50th percentile male model, but it has a multi-segmented spine adapted from the MADYMO Human Facet Model (HFM) that allows it to predict occupant kinematics and intervertebral loads and moments along the entire spinal column. Numerous simulations were run using the crash pulses from seven real-world impact scenarios and a 70 G standardized crash pulse. Results were analyzed and compared to the real-world impacts and CART HANS® model simulations.

Many metrics have been used in an attempt to predict the effects of secondary tasks on driving behavior. Such metrics often give rise to seemingly paradoxical results, with one metric suggesting increased demand and another metric suggesting decreased demand for the same task. For example, for some tasks, drivers maintain their lane well yet detect events relatively poorly. For other tasks, drivers maintain their lane relatively poorly yet detect events relatively well. These seeming paradoxes are not time-accuracy trade-offs or experimental artifacts, because for other tasks, drivers do both well. The paradoxes are resolved if driver demand is modeled in two orthogonal dimensions rather than a single “driver workload” dimension. Principal components analysis (PCA) was applied to the published data from four simulator, track, and open road studies of visual-manual secondary task effects on driving.

The seatbelt system, originally designed for protecting occupants in frontal crashes, has been reported to be inadequate for preventing occupant head-to-roof contact during rollover crashes. To improve the effectiveness of seatbelt systems in rollovers, in this study, we reviewed previous literature and proposed vertical head excursion corridors during static inversion and dynamic rolling tests for human and Hybrid III dummy. Finite element models of a human and a dummy were integrated with restraint system models and validated against the proposed test corridors. Simulations were then conducted to investigate the effects of varying design factors for a three-point seatbelt on vertical head excursions of the occupant during rollovers. It was found that there were two contributing parts of vertical head excursions during dynamic rolling conditions.

Lead-acid batteries have dominated the automotive conventional electric system, particularly in the functions of starting (S), lighting (L) and ignition (I) for decades. However, the low energy-to-weight ratio and the low energy-to-volume ratio makes the lead-acid SLI battery relatively heavy, large, and shallow Depth of Discharge (DOD). This could be improved by replacing the lead-acid battery by the lithium-ion polymer battery. The lithium-ion polymer battery can provide the same power with lightweight, compact volume, and deep DOD for engine idle elimination using start-stop function that is a basic feature in electric-drive vehicles. This paper presents the modeling and validation of a lithium-ion battery for SLI application. A lithium-metal-oxide based cell with 3.6 nominal voltage and 20Ah capacity is used in the study. A simulation model of lithium-ion polymer battery pack (14.4V, 80Ah) with battery management system is built in the MATLAB/Simulink environment.

It is recognized that the heavier vehicles, the more emissions, thus the more imperative to electrify. In this study, long haul heavy-duty trucks are referred as HDTs, which are recognized as one of the hard-to-electrify vehicle segments, though the automotive industry has gained trending advantages of electrifying both light-duty cars and SUVs. Since big rigs such as Class 8 HDTs have significant road-block challenges for electrification due to the demanding long-hour work cycles in all weathers, this study focuses on quantifying those electrification challenges by taking advantage of the public data of Class 8 tractors & trailers. Tesla Semi is the research target though its vehicle spec data is sorted out with fragmentary information in the public domain. The key task is to analyze the battery capacity requirements due to environmental temperature and inherent aging over the lifespan.