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The increased prevalence of larger and more energy-dense battery packs for transportation and grid storage applications has resulted in an increasing number of severe battery thermal events. The implications on product reliability, consumer safety, and the surrounding environment are significant. While there are many potential root causes for battery thermal runaway, these events often start within a single battery cell or group of cells that cascade to neighboring cells and other combustible materials, rapidly increasing the hazard profile of the battery pack as more stored energy is released. Reducing these hazards requires preventing severe thermal runaway scenarios by mitigating cell-to-cell propagation through the improved design of both individual cells and battery packs.

The use of Lithium-ion batteries in the transportation sector has its own unique set of requirements such as high-power demands, cooling challenges, and risk of mechanical failure due to crashes. Active and passive components of thermal management systems in battery-powered products are designed to mitigate the effects of thermal runaway events and prevent cell-to-cell propagation. Designing safe battery-powered systems requires an understanding of how the battery pack will behave while undergoing thermal runaway, including critical data such as total energy yielded, rate of energy generation, as well as venting patterns and directions. Details such as thermal runaway energy fractions associated with the cell casing as well as vent gas and ejecta can be used to inform and optimize battery pack designs and the product as a whole. The NASA Fractional Thermal Runaway Calorimeter (FTRC) was created to measure these values.

Electric vehicles (EVs) and the development around them has been rapid in recent years. As the battery is the most essential component of an electric vehicle, a lot of research and analysis has been focused on ensuring safe and reliable performance of batteries. Considering the location, size, and operating conditions for EV batteries, they must be designed with an in-built safety infrastructure keeping in mind certain realistic scenarios such as fire exposure, mechanical vibration, collisions, over-charging, single cell failures, and others. In this paper, we discuss an overview of various EV battery failure mechanisms, present current safety and abuse testing methods and standards associated with such mechanisms and discuss the need for the development and implementation of additional testing standards to better characterize the safety performance of EV battery packs.

The biomechanical injury assessment for an occupant in a planar vehicle-to-vehicle collision often requires a kinematic analysis of impact-related occupant motion. This analysis becomes more complex when the collision force is eccentric to the center of gravity on a struck vehicle because the vehicle kinematics include both translation and potentially significant yaw rotational rates. This study examines the significance of vehicle yaw on occupant kinematics in eccentric (off-center) planar collisions. The paper describes the calculation of the instantaneous center of rotation (ICR) in a yawing vehicle post-impact and explores how mapping this quantity may inform an occupant’s trajectory when using a free particle “occupant” analysis. The study initially analyzed the impact-related occupant motion for all the outboard seat positions in a minivan using several hypothetical examples of eccentric vehicle-to-vehicle crash configurations with varying PDOF, delta-V, and yaw rate.

Prior to developing or modifying the protocol of a performance evaluation test, it is important to identify field relevant conditions. The objective of this study was to assess the distribution of selected crash variables from rear crash field collisions involving modern vehicles. The number of exposed and serious-to-fatally injured non-ejected occupants was determined in 2008+ model year (MY) vehicles using the NASS-CDS and CISS databases. Selected crash variables were assessed for rear crashes, including severity (delta V), impact location, struck vehicle type, and striking objects. In addition, 15 EDRs were collected from 2017 to 2019 CISS cases involving 2008+ MY light vehicles with a rear delta V ranging from 32 to 48 km/h. Ten rear crash tests were also investigated to identify pulse characteristics in rear crashes. The tests included five vehicle-to-vehicle crash tests and five FMVSS 301R barrier tests matching the struck vehicle.

As micromobility devices (i.e., e-bikes, scooters, skateboards, etc.) continue to increase in popularity, there is a growing need to test these devices for varying purposes such as performance assessment, crash reconstruction, and design of new products. Although tests have been conducted across the industry for electric scooters (e-scooters), this paper describes a novel method for crash testing e-scooters with anthropomorphic test devices (ATDs) “riding” them, providing new sources for data collection and research. A sled fixture was designed utilizing a pneumatic crash rail to propel the scooters with an overhead gantry used for stabilization of the ATD until release just prior to impact. The designed test series included impacts with a 5.5-inch curb at varying incidence angles, a stationary vehicle, or a standing pedestrian ATD. Test parameter permutations included changing e-scooter tire sizes, impact speeds, and rider safety equipment.

Interest in rear-seat occupant safety has increased in recent years. Information relevant to rear-seat occupant interior space and kinematics are needed to evaluate injury risks in real-world accidents. This study was conducted to first assess the effect of size and restraint conditions, including belt misuse, on second-row occupant kinematics and to then document key clearance measurements for an Anthropomorphic Test Device (ATD) seated in the second row in modern vehicles from model years 2015-2020. Twenty-two tests were performed with non-instrumented ATDs; three with a 5th percentile female Hybrid III, 10 tests with a 10-year-old Hybrid III, and 9 tests with a 6-year-old Hybrid III. Test conditions included two sled bucks (mid-size car and sport utility vehicle (SUV)), two test speeds (56 and 64 km/h), and various restraint configurations (properly restrained and improperly restrained configurations). Head and knee trajectories were assessed.

The operational safety of automated driving system (ADS)-equipped vehicles (AVs) needs to be quantified for an understanding of risk, requiring the measurement of parameters as they relate to AVs and human driven vehicles alike. In prior work by the Institute of Automated Mobility (IAM), operational safety metrics were introduced as part of an operational safety assessment (OSA) methodology that provide quantification of behavioral safety of AVs and human-driven vehicles as they interact with each other and other road users. To calculate OSA metrics, the data capture system must accurately and precisely determine position, velocity, acceleration, and geometrical relationships between various safety-critical traffic participants. The design of an infrastructure-based system that is intended to capture the data required for calculation of OSA metrics is addressed in this paper.

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.

Obesity rates are increasing among the general population. This study investigates the effect of obesity on ejection and injury risk in rollover crashes through analysis of field accident data contained in the National Automotive Sampling System-Crashworthiness Data System (NASS-CDS) database. The study involved front outboard occupants of age 15+ years in 1994+ model year vehicle rollover crashes. Occupants were sorted into two BMI groups, normal (18.5 kg/m2 ≤ BMI < 25.0 kg/m2) and obese (BMI ≥30 kg/m2). Complete and partial ejection risks were first assessed by seating location relative to roll direction and belt use. The risk of serious-to-fatal injuries (MAIS 3+F) in non-ejected occupants were then evaluated. The overall risk for complete ejection was 2.10% ± 0.43% when near-sided and 2.65% ± 0.63% when far-sided, with a similar risk for both the normal and obese BMI groups.

This study assesses vehicle and occupant responses in six vehicle-to-vehicle high-speed rear impact crash tests conducted at the Exponent Test and Engineering Center. The struck vehicle delta Vs ranged from 32 to 76 km/h and the vehicle centerline offsets varied from 5.7 to 114 cm. Five of the six tests were conducted with Hybrid III ATDs (Anthropometric Test Device) with two tests using the 50th male belted in the driver seat, one test with an unbelted 50th male in the driver seat, one test with a 95th male belted in the driver seat, and one with the 5th female lap belted in the left rear seat. All tests included vehicle instrumentation and three tests included ATD instrumentation. The ATD responses were analyzed and compared to corresponding IARVs (injury assessment reference values). Ground-based and onboard vehicle videos were synchronized with the vehicle kinematic data and biomechanical responses.

While nearly 50 percent of occupants in side-impact collisions are in vehicles that experience a velocity change (delta-V) below 15.0 kph (9.3 mph), full scale crash testing research at these delta-Vs is limited. Understanding occupant kinematics in response to these types of side impacts can be important to the design of side-impact safety countermeasures, as well as for evaluating potential interactions with interior vehicle structures and/or with other occupants in the vehicle. In the current study, two full-scale crash tests were performed utilizing a late-model, mid-size sedan with disabled airbags. The test vehicle was impacted by a non-deformable moving barrier on the driver side at an impact speed of 10.0 kph (6.2 mph) in the first test and then on the passenger side at an impact speed of 21.6 kph (13.4 mph) in the second test, resulting in vehicle lateral delta-Vs of 6.1 kph (3.8 mph) and 14.0 kph (8.7 mph), respectively.

The purpose of this research is to document representative examples of control inputs and body positioning experienced riders use to control a motorcycle through maneuvers representative of those encountered during real-world operation. There is limited publicly available data that tracks the magnitude or direction of steering head rotation, steering torque input, etc. used by a rider to initiate and exit a turn as well as maintaining directional control during maneuvers ranging from slow parking lot turns to high speed lane changes. Using Exponent’s Test and Engineering Center (TEC) track and skid pad, a course was defined that included several maneuvers at various speeds and radii. A previous paper [1] investigated the influence of rider kinematics (weight shift) on motorcycle control.

This study assesses the exposure distribution and injury rate (MAIS 4+F) to front-outboard non-ejected occupants by crash severity, belt use and head restraint type and damage in rear impacts using 1997-2015 NASS-CDS data. Rear crashes with a delta V <24 km/h (15 mph) accounted for 71% of all exposed occupants. The rate of MAIS 4+F increased with delta V and was higher for unbelted than belted occupants with a rate of 11.7% ± 5.2% and 6.0% ± 1.5% respectively in 48+ km/h (30 mph) delta V. Approximately 12% of front-outboard occupants were in seats equipped with an integral head restraint and 86% were with an adjustable head restraint, irrespective of crash severity. The overall injury rate was 0.14% ± 0.05% and 0.22% ± 0.06%, respectively. It was higher in cases where the head restraint was listed as “damaged”. Thirteen cases involving a lap-shoulder belted occupant in a front-outboard seat in which “damage” to the adjustable head restraint was identified.

Many published studies have characterized walking and running speeds of young children. However, there is a paucity of data on the cycling speeds of very young children (4 to 5 years old). The purpose of this study was to obtain an estimate of cycling speed for boys and girls both who are learning to ride bicycles (i.e., younger children who still ride with training wheels) and who have already learned to ride bicycles (i.e., slightly older children who no longer use training wheels). A sample of 32 child riders (17 boys, 15 girls; 17 four-year-olds who still ride with training wheels, 15 five-year-olds who do not) were asked to ride a short pre-defined distance at their usual speed when riding, and again at their highest speed. We found that while age and experience can differentiate riders, there were only small differences between boys’ and girls’ speeds in either age group.

Low- to moderate-speed motor vehicle collisions are a common crash type and are sometimes associated with injury complaints. Understanding occupant motion (kinematics) in response to low- and moderate-speed motor vehicle collisions is important for evaluating occupant interactions with interior vehicle structures, including the restraint systems, with the ultimate goal of assessing injury potential. Furthermore, quantitative occupant kinematic data from full-scale crash testing of late-model passenger vehicles is limited for collisions at low- to moderate-speeds. The current study reports kinematic data from full-scale frontal and rear-end crash tests of late-model, mid-size sedans with delta-Vs ranging from 6.0 to 19.0 kph (3.7 to 11.8 mph) and 5.6 to 19.5 kph (3.5 to 12.1 mph), respectively. For each test vehicle, the motion of a Hybrid III 50th-percentile male anthropomorphic test device (ATD) restrained in the driver seat was recorded using high-speed onboard video.

Lane Departure Warning (LDW) systems, along with other types of Advanced Driver Assistance Systems (ADAS), are becoming more common in passenger vehicles, with the general aim of improving driver safety through automation of various aspects of the driving task. Drivers have generally reported satisfaction with ADAS with the exception of LDW systems, which are often rated poorly or even deactivated by drivers. One potential contributor to this negative response may be an increase in the cognitive load associated with lane-keeping when LDW is in use. The present study sought to examine the relationship between LDW, lane-keeping behavior, and concurrent cognitive load, as measured by performance on a secondary task. Participants drove a vehicle equipped with LDW in a demarcated lane on a closed-course test track with and without the LDW system in use over multiple sessions.

Unintended acceleration events due to pedal misapplication have been shown to occur more frequently in older vs. younger drivers. While such occurrences are well documented, the nature of these movement errors is not well-characterized in common pedal error scenarios: namely, on-road, non-emergency stopping or slowing maneuvers. It is commonly assumed that drivers move in a ballistic or “direct hit” trajectory from the accelerator to the brake pedal. However, recent simulator studies show that drivers do not always move directly between pedals, with older drivers displaying more variable foot trajectories than younger drivers. Our study investigated pedal movement trajectories in older drivers ages 67.9 ± 5.2 years (7 males, 8 females) during on-road driving in response to variable traffic light conditions. Three different sedans and a pick-up truck were utilized.

As a result of the development of Event Data Recorders (EDR) and the recent FMVSS regulation 49 CFR 563, today’s automobiles provide a limited subset of electronic data measurements of a vehicle’s state before and during a crash. Prior to this data, the only information available about the vehicle movements before or during a collision had come from physical evidence (e.g. tire marks), witnesses, aftermarket camera systems on vehicles, and ground-based cameras that were monitoring vehicle traffic or used for security surveillance. Today’s vehicles equipped with Advanced Driver Assistance Systems (ADAS) have vehicle-based sensors that measure information about the environment around a vehicle including other vehicles, pedestrians, and fixed wayside objects.

Fires involving cars, trucks, and other highway vehicles are a common concern for emergency responders. In 2013 alone, there were approximately 188,000 highway vehicle fires. Fire Service personnel are accustomed to responding to conventional vehicle (i.e., internal combustion engine [ICE]) fires, and generally receive training on the hazards associated with those vehicles and their subsystems. However, in light of the recent proliferation of electric drive vehicles (EDVs), a key question for emergency responders is, “what is different with EDVs and what tactical adjustments are required when responding to EDV fires?” The overall goal of this research program was to develop the technical basis for best practices for emergency response procedures for EDV battery incidents, with consideration for suppression methods and agents, personal protective equipment (PPE), and clean-up/overhaul operations.