Vehicle Occupants Research Articles

Surgical Fasciotomies for Pediatric Acute Compartment Syndrome, and Overview

Introduction: The goal of treatment is firstly to save the patient's life and secondly to save the damaged climb. Fasciectomy is the only accepted treatment for compartment syndrome and should be performed promptly after the diagnosis is made. The results after fasciectomy are best when there is no delay in treatment. Method: Clinically determined according to the "5 P's" and measured Intracompartmental Pressure (ICP) with P ≥ 30 mmHg. Perform traditional Fasciotomies surgery on all patients. Results: There were four patients; Mean age: 54 months ± 31.749; Girl: 03; Boy: 01; Fall from hight: 2; Sport trauma: 01; Pedestrian in a car accident: 01; Mean - Intracompartmental Pressure (ICP): 53.75 mmHg.The most common mechanisms of injury are pedestrians struck by motor vehicles, falls, sports, and vehicle occupants in motor vehicle crashes. Forearm fractures are the most common cause in the upper extremity, and fractures of the tibia and/or fibula are most common in the lower extremity. Conclusions: Fractures significantly increase the risk of developing compartment syndrome in both forearm and leg fractures. The patients were transferred directly from the emergency room to the operating room, suggesting that the remaining developed compartment syndrome after admission or late diagnosis.

Leveraging electronic device outputs for service quality assessment of public transportation systems: An initial look at the Philippines’ service contracting program through data analytic lens

Electronic devices such as CCTVs and GPS trackers are becoming more prevalent in public utility vehicles. These electronic devices produce data that can be aggregated and processed to generate insights regarding the service quality provided by public transportation systems. We describe a methodology for processing CCTV-produced videos and GPS logs, and utilize it to perform a first order, limited assessment of the Philippines’ Service Contracting Program, which ran during the COVID-19 pandemic. Our analyses uncovered vast discrepancies between data-supported figures and manually-generated estimates provided by the transport operators, especially with regards to vehicle occupancy and total number of commuters served. Our study also uncovered imperfections in the data generated by the electronic devices, which place caveats or limitations on the insights generated by the data analyses. We provide and suggest ways on how the analyses can be modified to take into account such missing data, thus enabling us to come up with educated, reasonable insights despite incomplete input datasets.

Relocation incentives for ride-sourcing drivers with path-oriented revenue forecasting based on a Markov Chain model

Proper positioning of ride-sourcing drivers may improve vacant travel times, waiting times, and matching opportunities. Herein, we evaluate the potential repositioning response of drivers when provided guidance based on estimates of their earnings in a system offering ride-hailing (solo) and ridesplitting (shared) rides. Therefore, we develop a strategy that enumerates the best regional repositioning destination based on the expected number of requests a driver will encounter during the forecast horizon. A mixed continuous-discrete time Markov Chain (MDCTMC) is developed to predict a driver’s activities and the associated revenues. In summary, the developed strategy provides a group of drivers with individualized near-future revenue estimates guiding drivers toward repositioning decisions that are more likely to maximize their earnings. Our main findings indicate that if the operator selects only a fraction of active drivers to provide guidance, these are likely to expect higher earnings than those without guidance. We also show that it manages to decrease the number of unserved requests compared to several state-of-art benchmarks while increasing vehicle occupancy and decreasing the deadheading.

Review of Airbag Injuries: A Sri Lankan Case Series

The deployment of airbags in vehicles has significantly contributed to occupant safety during accidents. This review article discusses their history, evolution, types, chemical composition, mechanisms, defects, safety issues and hazardous practices by vehicle occupants. The evolution of airbags, from early designs to advanced designs is presented highlighting their life-saving impact and defects. The article addresses common hazardous practices by vehicle occupants that could lead to airbag-related injuries such as resting hands or feet on the dashboard. A series of typical and atypical airbag-related injuries from Sri Lanka is given in the latter part of the article. These cases include incidents of metal objects detaching from airbags causing fatal injuries, fractures resulting from improper hand placement during airbag deployment, burns, cranio-facial and dental injuries and so on.

Application of Acoustic-solid Coupling Theory in New Energy Vehicle Noise Control

The development of new energy vehicles has attracted much attention due to the strong promotion and popularisation of the concept of low carbon and environmental protection, and the increasing demand for environmental protection in cars. Although these vehicles meet people’s requirements for resource and environmental protection, the noise generated during the driving process affects the comfort of the vehicle occupants and the concentration of the vehicle driver. To address this problem, the research proposes to improve the noise control technology of new energy vehicles based on acoustic-solid coupling theory and to test the practical application effect of this technology. The test results show that the maximum acceleration of vibration at the roof, floor, axle head, and spring of the new energy vehicle are 1.48 m/s2, 1.02 m/s2, 0.079 m/s2, and 0.020 m/s2 respectively, which are lower than the maximum acceleration before the use of this technology. The maximum sound pressure at the windscreen and side window glass of the new energy vehicle is 80 dB(A) and 73 dB(A) after the use of this technology. The maximum sound pressure at the driver’s ear was 62 dB(A) and 77 dB(A) when the vehicle was driven on different road surfaces, which were lower than the sound pressure values before use. In summary, the research proposes to improve the noise control technology of new energy vehicles based on the sound-solid coupling theory, which can have the effect of reducing the noise value generated by new energy vehicles and improving the comfort of users.

Looking back in the rearview: Insights into Queensland’s rear-end crashes

Objective Rear-end crashes cost the most out of any crash type to the Compulsory Third Party insurance scheme of Queensland. Rear-end crashes are also one of the most common types of crashes, peaking as the most common type of crash in Queensland in 2019. This study investigated the environmental, driver, and vehicle characteristics associated with rear-end collisions in Queensland, Australia. Methods A totle of 367,230 crashes in the Queensland crash database between 2001 and 2021 were used to identify crash trends in Queensland, particularly related to rear-end crashes. For crashes between 2015 and 2021, additional information was gathered and allowed further analysis of factors contributing to rear-end crashes using the quasi-induced exposure method. Two binary classification tree models were used. Model 1 investigated the environmental characteristics that predicted a crash being a rear-end or not. Model 2 investigated the controller and vehicle characteristics that predict a rear-end crash-involved vehicle to be either the striking (at-fault) or struck (not-at-fault) vehicle. Results Model 1 indicated that rear-end crashes were overrepresented in urban areas and major cities and where speed limits exceeded 50 km/h. Model 2 indicated that occupants of struck vehicles (not at-fault) were more likely to be severely injured than the striking (at-fault) vehicles in rear-end crashes. License type and vehicle type also influenced the frequency and severity of rear-end crashes. Conclusion Rear-end crashes can be unjust in that the not-at-fault party is typically more severely injured. Results from the current study suggest that keeping speed limits no higher than 50 km/h could help reduce the severity of rear-end crashes. Increased enforcement of safe following distances could also assist in preventing road trauma as a result of rear-end crashes.

Influence of Traction Battery Arrangement on Risk of Thermal Runaway and Loads Suffered by Electric Vehicle Occupant during Side Collision

In the current electric vehicles, the purpose of the traction battery is to store energy. When designing this battery, different parameters are considered to arrange the battery/module/cells in the mechanically and thermally safest configuration. Moreover, the battery layout must produce correct dynamic behavior during collisions. In the present study, different battery configurations plus added energy absorbers were analyzed. To achieve this, an internal combustion vehicle modeled with finite elements was applied as the reference model. The structural behavior of the different battery configurations in the event of a side collision was examined. First, the safest arrangement was established with respect to both cabin intrusion and thermal runaway propagation. Second, the safest arrangement that guarantees the safety of the occupants in the event of a side collision was analyzed using MADYMO. This software includes experimentally validated dummies that allow insight into the stresses experienced by occupants. The results of the analysis showed that battery pack inclusion in the vehicle increases the stiffness of the car floor, resulting in fewer intrusions into the passenger compartment. Therefore, safety of the occupants is increased. However, none of the configurations analyzed showed sufficient safety against thermal runaway. This study contains sufficient contributions to the new body of knowledge, since there is no study that analyzes the safest configuration in terms of battery behavior with respect to intrusion into the passenger compartment and the effect of thermal runaway, together with the fact that this is the safest configuration for occupants after analyzing the injuries they experience in a side collision for the different configurations.

Predicting head injury metrics during low- to moderate-speed frontal collisions using computational simulations

ObjectivesSubjective reports of mild traumatic brain injury (mTBI) are common following low-energy motor-vehicle collisions. Biomechanical analyses are useful in providing a quantitative means for determining the likelihood of sustaining mTBI. While occupant dynamics in low-speed rear impacts have been extensively investigated, peer-reviewed studies on occupant dynamics during low-speed frontal collisions are sparse. The objective of this study is to present a validated computational method to quantify the biomechanical response of the head in low- and moderate-speed frontal collisions. Data and methodsThis study used data from a previously-published series of four instrumented in-line front-to-rear staged collisions using 2014 Honda Accord sedans at closing velocities of approximately 7.4 kph (test L1), 12.7 kph (test L2), 21.7 kph (test L3), and 33.6 kph (test L4) kph. A model of the test vehicle occupant compartment was created using the MAthematical DYnamic MOdeling (MADYMO) software using methods previously described. Crash pulse data from L4 were applied to the MADYMO model. Seat belt parameters were optimized to achieve reasonable agreement between simulation results and test data for relevant head injury metrics (linear head acceleration [LHA], angular head acceleration [AHA], and HIC15). Crash pulses from the other tests in the series (L1, L2, and L3) were then applied to the model and peak values for LHA, AHA, and HIC15 were compared to the physical test data to demonstrate validation. ResultsThe optimization of seat belt and seat parameters within the MADYMO model resulted in accurate prediction of ATD dynamics demonstrated in Test L4. The simulation-predicted peak LHA was within 0.2 g of the test value, peak AHA was within 64 rad/s2, and HIC15 was within 0.46. When applied to the remainder of the tests (L1, L2, and L3), the optimized model showed excellent accuracy in predicting peak LHA and HIC15. When compared to the physical test data, the simulation-predicted values for LHA were within 0.4 g or less and the HIC15 values were within 0.4 or less across all tests. The model generally over-predicted AHA, particularly for the lower-severity collisions (L1 and L2). ConclusionsWe have demonstrated a reliable methodology for developing a biomechanical computational model to predict head injury metrics in low- to moderate-speed frontal collisions. This approach can be particularly valuable in forensic investigations of real-world crashes. Pre-existing crash test data can be used in conjunction with exemplar vehicle information to validate a MADYMO model. Appropriate crash pulse data from classical accident reconstruction techniques, event data recorders, or simulations can then be applied to the model to accurately predict head dynamics for real-world vehicle occupants without the need for full-scale staged crash tests.

Locating Method for Pick-up and Drop-off Spots for Shared Autonomous Vehicle-based Mobility Services

To provide safety to users and not disturb traffic flow, autonomous vehicles in shared on-demand mobility services cannot stop everywhere; thus, pick-up and drop-off (PUDO) spots must be dedicated or established for them. Our research objective is to propose a method to locate the PUDO spots for shared autonomous vehicle-based mobility services as this topic has been barely studied. The number of required PUDO spots is calculated, and the location is chosen considering the urban environment, walking radius, vehicle occupancy, and time for boarding and alighting among other parameters. Different from some methods applied to shared mobility, we consider the existing infrastructure (e.g., parking spaces) as potential locations for PUDO spots. The method is applied to a study case, demonstrating the applicability and providing the main findings: (i) the required number of PUDO spots decreases if willingness to walk increases; (ii) with a 3-min walking radius, 83% of curbside parking spaces can be repurposed, and 100% is reached with a 10-min walking radius; (iii) the minimum of 55% of curbside parking spaces can be repurposed with 10-min walking radius and without locating PUDO spots in private parking. Using our method, cities can determine the quantity of PUDO spots and their locations, being prepared in advance for the required changes in the existing infrastructure as well as the freed-up space to be repurposed.

Kinematic response of seated male volunteers in various reclined postures on a sled subjected to a braking pulse

Vehicle occupants expect greater postural flexibility with the introduction of highly automated vehicles, such as reclined postures. Experiments have been conducted with post mortem human subjects to study the risk of injury under impact conditions in reclined postures. However, the influence of the pre-crash phase on the kinematics in reclined postures has not yet been thoroughly studied. The aim of the present study is to investigate human responses under low g braking conditions focusing on different backrest angles in a generic sled environment.Three 50th percentile male volunteers were recruited to participate in a sled experiment. Each of them was subjected to a total of fourteen trials under a braking pulse with a maximum acceleration of 0.7 g for 700 ms. Different sitting postures were investigated: from 23° to 45°, 60° and 75° backrest tilt with respect to the vertical axis. In addition, two different seat pan tilt angles were considered: a 16° tilt angle for 23°, 45° and 60° backrest inclination and a 36° tilt angle for 60° and 75° backrest inclination. Measurements of volunteer kinematics, muscle activation and interaction forces between the volunteers and the sled, among others, were acquired.Initial results show a significant reduction in maximum forward head displacement from the upright to the reclined postures (p < 0.02), with the exception of the 45° reclined posture. However, no significant difference in maximum head displacement was found between the different reclined postures (p > 0.1). Seat pan tilt angle did significantly influence forward head excursion when considering the same seatback inclination (p < 0.01).It is of great importance to investigate occupant kinematics during the pre-crash phase to understand its influence on the potential injuries that may occur with a reclined posture in the event of a collision.

Seat Belt Use in the US by Pregnant Motor Vehicle Occupants

This cross-sectional study assesses patterns of seat belt use among pregnant, nonpregnant, and male occupants.

Squeak and rattle noise prediction in vehicle acoustics

AbstractSqueak and rattle belong to unintended noise audible by occupants of a vehicle. This noise negatively affects the perceived built quality, leading to nonbuying decisions, high warranty costs, and poor brand reputation. Therefore, vehicle manufacturers seek to prevent the emergence of such noise, preferably in the early development phase and during production at the latest. This causes substantial monetary and temporal expenditure, which must be minimized. Rattle is defined as repeated impact. The underlying physical phenomenon is impulsive short‐duration contact normal to the surface. Squeak, in contrast, originates from an in‐contact motion in the tangential direction and is a friction‐induced stick‐slip phenomenon. State‐of‐the‐art numerical squeak and rattle prediction is based on linear analysis resulting in an empirical noise risk index. However, quantification of noise and assessment of audibility is not possible. The reason is the nonlinearity of the contact forces. Hence, the actual system response is not calculable with a linear approach. Mathematically, the nature of both excitation events is nonlinear due to frictional contact and nonsmooth due to short impulsive behavior in time. This makes linear simplification and a solution process in the time domain challenging. Both events appear periodically, leading to an oscillation characterized by fundamental and higher harmonics. Due to this periodic character, squeak and rattle phenomena fulfill the prerequisite for applying the harmonic balance method (HBM) to solve the governing nonlinear equation of motion. The more harmonics considered, the more precise the modeling and the dynamic response prediction. In addition, the alternating frequency/time domain method (AFT) allows for switching between the frequency and the time domain during the iterative solution process. Thus, the nonlinear contact forces can be evaluated in the time domain. The equation‐solving process results in the calculation of surface velocities. This gives way to determining a proxy for the emitted sound power of the oscillatory system. The simulation method based on combining HBM and AFT was validated on test rigs for squeak and rattle noise. The industrial applicability of this simulation approach was demonstrated numerically and experimentally on an actual vehicle part showing promising results. Thereby, important steps in nonlinear structural dynamics and vehicle acoustics were made toward a calm, smooth, and enjoyable ride for vehicle occupants.

Measuring the Level of Road Safety through Road Safety Audit– A Case Study from Himalayan Expressway

National Highways (NH) carry the major portion of the total traffic in India. Road safety on NH is therefore of paramount importance. In the present study, a road safety audit has been performed for a 4-lane NH using Star Rating method. VIDA software developed by International Road Assessment Programme (IRAP) is used for finding the Star Rating of the road sections. This safety rating has been determined for four road user types: Vehicle occupant, Motorcyclist, Pedestrian and Bicyclist. The purpose of the study is to measure the level of road safety and lower the severity level by proposing countermeasures. The case study is a 5(km) section of NH-5 from Sanwara toll plaza to Jabali in the state of Himachal Pradesh in India. Encroachment on the land, roadside activities, insufficient infrastructure, imperfections in the geometric design, and non-motorized access were some of the severe safety flaws identified through the study process. The Star Rating results indicated that among all the road user types, the vehicle occupant is much safer than the others.

Designing for Collaborative Non-Driving Related Activities in Future Cars: Fairness and Team Performance

With the gradual transition towards assisted and automated driving, the car will transform into a more social environment where passengers and drivers engage in Non-Driving-Related Activities (NDRA). To support collaboration among occupants in future vehicles, research suggests interactive systems controlled by several users at once. In this paper, we explore five concepts for the collaborative performance of NDRA with the use-case of music playlist creation. While prior work investigated the effect on social connectedness, we expand insights towards team performance and fairness. Results from a mixed-subject experiment (N=27) show that the concepts have major consequences on team performance and fairness. Certain concepts can promote or hinder coordination effectiveness and, in turn, impact intra-vehicular collaboration. Our observations also indicate that fairness is key to fostering social collaboration in AVs, while it does not naturally define a high team performance. Subsequently, we provide recommendations to guide future designs of collaborative NDRAs in vehicles.

Internet of things enabled parking management system using long range wide area network for smart city

As the Internet of Things (IoT) evolves, it paves the way for vital smart city applications, with the Smart Parking Management System (SPMS) standing as a prime example. This research introduces a novel IoT-driven SPMS that leverages Long Range Wide Area Network (LoRaWAN) technology, termed as IoT-SPMS-LoRaWAN, to surmount typical restrictions related to communication range, energy usage, and implementation cost seen in traditional systems. IoT-SPMS-LoRaWAN features intelligent sensing nodes that incorporate an Arduino UNO microcontroller and two sensors—a triaxial magnetic sensor and a waterproof ultrasonic sensor. These components collaboratively detect vehicle occupancy and transmit this data to the server via a LoRaWAN gateway. Notably, the integration of LoRa technology enables extensive network coverage and energy efficiency. Users are provided with real-time updates on parking availability via the accessible AllThingsTalk Maker graphical user interface. Additionally, the system operates independently, sustained by a solar-powered rechargeable battery. Practical testing of IoT-SPMS-LoRaWAN under various scenarios validates its merits in terms of functionality, ease of use, reliable data transmission, and precision. Its urban implementation is expected to alleviate traffic congestion, optimize parking utilization, and elevate awareness about available parking spaces among users. Primarily, this study enriches the realm of smart city solutions by enhancing the efficiency of parking management and user experience via IoT.

Parking Lot Occupancy Detection with Improved MobileNetV3.

In recent years, parking lot management systems have garnered significant research attention, particularly concerning the application of deep learning techniques. Numerous approaches have emerged for tackling parking lot occupancy challenges using deep learning models. This study contributes to the field by addressing a critical aspect of parking lot management systems: accurate vehicle occupancy determination in specific parking spaces. We propose an advanced solution by harnessing an optimized MobileNetV3 model with custom architectural enhancements, trained on the CNRPark-EXT and PKLOT datasets. The model processes individual parking space patches from real-time video feeds, providing occupancy classification for each patch, identifying occupied or available spaces. Our architectural modifications include the integration of a convolutional block attention mechanism in place of the native attention module and the adoption of blueprint separable convolutions instead of the traditional depth-wise separable convolutions. In terms of performance, our proposed model exhibits superior results when benchmarked against state-of-the-art methods. Achieving an exceptional area under the ROC curve (AUC) value of 0.99 for most experiments with the PKLot dataset, our enhanced MobileNetV3 showcases its exceptional discriminatory power in binary classification. Benchmarked against the CarNet and mAlexNet models, representative of previous state-of-the-art solutions, our proposed model showcases exceptional performance. During evaluations using the combined CNRPark-EXT and PKLot datasets, the proposed model attains an impressive average accuracy of 98.01%, while CarNet achieves 97.03%. Beyond achieving high accuracy and precision comparable to previous models, the proposed model exhibits promise for real-time applications. This work contributes to the advancement of parking lot occupancy detection by offering a robust and efficient solution with implications for urban mobility enhancement and resource optimization.

A Comprehensive Analysis of Real-Time Car Safety Belt Detection Using the YOLOv7 Algorithm

Using a safety belt is crucial for preventing severe injuries and fatalities during vehicle accidents. In this paper, we propose a real-time vehicle occupant safety belt detection system based on the YOLOv7 (You Only Look Once version seven) object detection algorithm. The proposed approach aims to automatically detect whether the occupants of a vehicle have buckled their safety belts or not as soon as they are detected within the vehicle. A dataset for this purpose was collected and annotated for validation and testing. By leveraging the efficiency and accuracy of YOLOv7, we achieve near-instantaneous analysis of video streams, making our system suitable for deployment in various surveillance and automotive safety applications. This paper outlines a comprehensive methodology for training the YOLOv7 model using the labelImg tool to annotate the dataset with images showing vehicle occupants. It also discusses the challenges of detecting seat belts and evaluates the system’s performance on a real-world dataset. The evaluation focuses on distinguishing the status of a safety belt between two classes: “buckled” and “unbuckled”. The results demonstrate a high level of accuracy, with a mean average precision (mAP) of 99.6% and an F1 score of 98%, indicating the system’s effectiveness in identifying the safety belt status.

Effects of Advanced Driver Assistance Systems on Impact Velocity and Injury Severity: An Exploration of Data from the Crash Investigation Sampling System

This paper presents an exploratory analysis of advanced driver assistance systems (ADAS) features and safety outcomes using National Highway Transportation Safety Administration’s Crash Investigation Sampling System (CISS) database. In this database, we found improved safety outcomes associated with the presence of three ADAS features: lane departure warning, forward collision warning, and blind spot detection. In particular, vehicles with ADAS features were less likely to be involved in fatal and severe crashes than vehicles of a similar age and body style. Additionally, vehicles with ADAS features had a lower rate of change in velocity pre- and postcrash, a key proxy for injury severity. Vehicles with ADAS were also less likely to be involved in head-on and rear-end crashes than similar vehicles without ADAS and were less likely to experience a severe outcome than vehicles without ADAS when involved in sideswipe collisions. Despite these promising findings, however, small sample sizes precluded robust within-category and multivariate analysis. More robust data are urgently needed to disentangle the safety effects of ADAS features from those related to confounding variables such as vehicle age and body type for vehicle occupants, pedestrians, and bicyclists. We conclude the paper with recommendations for improvements to the CISS database that could support future investigations. We hope this work provides a baseline for scholars and practitioners to deepen our understanding of the effects of ADAS features on transportation safety.

Techno-economic feasibility analysis of an electric vehicle charging station for an International Airport in Chattogram, Bangladesh

The transportation system is one of the crucial requirements of day-to-day human life. The car is one of the most attractive modes of transportation system for human beings. The demand for electric vehicles (EVs) has been growing dramatically in the last few years to reduce environmental impacts. This article provides a proposed electric vehicle charging station (EVCS) development with detailed planning and comprehensive analysis for Shah Amanat (CGP) International Airport, Chattogram, Bangladesh. A load profile prediction method is developed by utilizing Fuzzy logic and RNN-LSTM, taking account of climate data, battery state of charge (SOC), vehicle occupancy, and flight schedules. After predicting the load profile, an average load of 10.54 MWh/day is generated as output. This load profile is used in optimization software to optimize the operational and economic performance of the components and determine the most cost-effective design of the EVCS. Four scenarios with different resource combinations were explored, and Scenario-3 (S3): grid-tied Photovoltaic (PV) and wind turbine (WT) configuration was found to be the optimal scenario, with a cost of energy (COE) of $0.041/kWh based on the renewable fraction (84.3 %) and profitability index (5.55). Given these results and a suitable charging tariff ($0.140/kWh), the estimated profit was calculated to be $0.22 M/year. In comparison to the grid-only scenario (Base Scenario), Net present cost (NPC), COE, and emission can be lowered by 84 %, 63 %, and 75 %, respectively. As EVs have yet to enter the country's market, the feasibility research will assist decision-makers in determining the best adoption of integrating EVCS using renewable energy.

Numerical Analysis of Crashworthiness on Electric Vehicle’s Battery Case with Auxetic Structure

Due to the reduction in pollutant emissions, the number of electric vehicles has experienced rapid growth in worldwide traffic. Vehicles equipped with batteries represent a greater danger of explosion and fire in the case of traffic accidents, which is why new protective systems and devices have been designed to improve impact safety. Through their design and construction, auxetic structures can ensure the efficient dissipation of impact energy, reducing the risk of battery damage and maintaining the safety of vehicle occupants. In this paper, we analyze the crashworthiness performance of a battery case equipped with an energy absorber with a particular shape based on a re-entrant auxetic model. Simulations were performed at a velocity of 10 m/s and applied to the battery case with a rigid impact pole, a configuration justified by most accidents occurring at a low velocity. The results highlight that by using auxetic structures in the construction of the battery case, the impact can be mitigated by the improved energy absorber placed around the battery case, which leads to a decrease in the number of damaged cells by up to 35.2%. In addition, the mass of the improved energy absorbers is lower than that of the base structure.