Search Results (191)

Expanding university campuses face a dual challenge: meeting higher internal travel demand while reducing congestion and emissions. Using stated-preference data (412 respondents; 9 choice tasks per person), this study quantifies the expected adoption of two low-emission micromobility options—bicycle and electric scooter—relative to walking and car for intra-campus trips at an Ecuadorian university. Under Random Utility Theory, we estimate a multinomial logit (MNL) and a panel mixed logit (MIXL) model, treating MIXL as the preferred specification. Simulated maximum likelihood with 12,000 draws shows MIXL substantially improves fit and reveals marked heterogeneity in time sensitivity. In out-of-sample prediction (TEST), the two prospective modes achieve comparable average choice probabilities (bicycle = 0.289; electric scooter = 0.286), with a joint acceptance of 0.575, supporting the feasibility of a micromobility program under the evaluated scenarios. Environmental impact (gCO₂/km) exhibits limited aggregate influence compared with operational factors (time and cost). A complementary WTP-space MIXL provides VOT estimates and confirms that 10–20% time reductions increase expected acceptance. Overall, results indicate that adoption is most likely when sustainability objectives are translated into tangible service improvements in effective speed, reliability, and affordability. Full article

Background/Objectives: The aims of this study were to investigate maxillofacial trauma resulting from electric scooter accidents and to identify risk factors associated with the location of injuries. Methods: An 8-year retrospective cohort study was conducted involving all patients presenting with electric scooter-related maxillofacial fractures at a tertiary care center from 2017 to 2024. Data recorded for each patient included gender, age, date and cause of injury, contributing factors, type of facial fractures, other injuries, helmet use, and length of hospital stay. Results: Maxillofacial fractures were diagnosed in 138 patients (18.5% of e-scooter accident presentations). The study included 93 male and 45 female patients (ratio 2:1), with a mean age of 25.8 ± 7.75 years (range 14–45 years). Patients aged 20–29 years formed the largest group (51%). Most patients (89%) sustained a single facial fracture, and the most affected facial area was the lower third, with 80 cases (58%), followed by the middle third (36%). The remaining patients were represented by a combination of the various facial thirds, with thirds I-II being the most representative (12%). The most recurrent patterns were multifocal mandibular fractures (55%), followed by fractures of the orbito-malar-zygomatic complex (33%). Dental injuries were also frequent and were recorded in 40 patients (29% of all cases). Concomitant injuries outside the facial region were documented in 32 patients (23%), among which orthopedic limb injuries were most common (44% of patients with concomitant injuries). Contributing factors were identifiable in 102 patients (74%). Self-reported helmet use was low, with 63% of patients reporting never wearing a helmet, and 27% reporting inconsistent or occasional use. Conclusions: Accidents involving personal mobility vehicles have become a primary cause of emergency room admissions in recent years. Although electric-scooter-related maxillofacial fractures are a new phenomenon, an awareness of their frequency, contributing factors, and anatomical distribution is important for emergency and trauma teams who assess these patients first. Early recognition and timely management are crucial because missed diagnoses or delayed treatment can lead to permanent facial deformities and functional disability. These findings can inform targeted public health strategies and injury-prevention programs. In the future, helmet designs should be modified to improve maxillofacial protection in scooter-related injuries. Full article

This article presents an experimental–computational methodology for evaluating the state of charge (SoC), energy consumption, terminal-voltage behavior, and driving range of a 350 W electric scooter powered by a 36 V, 7.8 Ah lithium-ion battery. The test was carried out using a 117 s elementary urban driving cycle derived from the low-speed section of the New European Driving Cycle (NEDC) and limited to the 32 km/h operating speed of the scooter. Laboratory measurements were performed on rollers under controlled conditions. Battery current and terminal voltage were recorded during the discharge test. The experimental SoC was reconstructed from the measured current by trapezoidal Coulomb counting. The voltage-derived SoC values included in the original laboratory file were kept only for traceability, since they did not correspond to current integration. A MATLAB/Simulink model was developed to reproduce the driving cycle, longitudinal vehicle dynamics, DC motor demand, battery current, and SoC evolution. The valid experimental endpoint occurred at 5233 s, when the terminal voltage reached 31.50 V. At this point, the tested distance was 16.49 km, the discharged capacity was 5.817 Ah, and the final experimental SoC was 25.42%. The simulation produced a discharged capacity of 5.147 Ah and a final SoC of 34.01%, with a charge deviation of 11.51%. Energy consumption was also evaluated from the measured and simulated electrical power. The experimentally integrated discharged energy was 208.10 Wh, equivalent to 12.62 Wh/km. The simulated electrical demand was 184.41 Wh, equivalent to 11.18 Wh/km. A semiempirical terminal-voltage reconstruction, based on the simulated SoC, current demand, an open-circuit-voltage curve, and a fixed internal resistance, reproduced the global voltage-decay trend observed in the experiment. The simplified model captured the general discharge behavior, although it underestimated the measured charge and energy demand. The proposed workflow provides a reproducible basis for comparing manufacturer-declared range, laboratory measurements, current-based SoC reconstruction, energy consumption, and simplified simulation results in light electric vehicles. Full article

This study presents a topology optimization-based design methodology for a fail-safe stub axle of a lightweight 4 × 4 electric scooter with independent suspension, with the objective of developing a structural design roadmap. Topology optimization was performed under five critical load conditions: vertical, longitudinal, and lateral impacts, as well as braking and cornering under braking, representing standard driving scenarios defined in the literature. The final geometry was built by combining the topology optimization results from each load case, and it was evaluated using finite-element analysis, showing that it is safe under all critical loading conditions with respect to yield strength. The fatigue life assessment was performed using the Goodman–Haigh approach, based on load-condition pairs recommended in the literature, and it was found that the stresses in critical regions remain within the infinite fatigue life region. In addition, based on literature data, the proposed lightweight design approach indicates potential benefits in terms of both energy consumption and manufacturing cost. Overall, the findings suggest that the presented methodology can serve as a fail-safe design roadmap for the development of electric vehicle components. Full article

The market for electric single-person vehicles in Sweden has undergone significant changes, shifting from a rental-dominated model to increasing private ownership. This transformation has resulted in both benefits and challenges, including improved accessibility, evolving consumer behaviour, and increased accident rates, particularly among young users. This study, commissioned by the Swedish government, presents a comprehensive mapping of the availability, usage, and consequences of private electric scooters. Through market surveys, user studies, and accident data analysis, we provide insights into regulatory gaps, consumer awareness, and safety concerns. Our findings highlight the need for clearer communication of existing regulations and improved consumer education to ensure the safe and responsible use of electric single-person vehicles. Full article

Electric scooters (e-scooters) have rapidly integrated into university transportation networks; however, there is limited empirical understanding of users’ and non-users’ perceptions, which is essential for developing effective and inclusive policies. This study addresses this gap by analyzing the differential perceptions of e-scooter adoption, safety, and policy preferences at Louisiana State University (LSU). A quantitative, cross-sectional survey was administered to 1036 respondents (592 users and 444 non-users). Statistical analyses, including Chi-square tests and Binary Logistic Regression, were used to identify key perceptual differences and behavioral predictors of e-scooter usage. Results show that users were predominantly male undergraduates, with speed (90%) and convenience (61%) as the primary motivators. Users were over 12 times more likely to perceive e-scooters as safer than walking. In contrast, non-users cited frequent scooter misplacement (84%) as their top barrier to adoption. Logistic regression confirmed that concern about misplacement (Odds Ratio = 0.076) and support for restrictive policies were strong negative predictors of use, while belief in safety and low cost were positive predictors. These findings may help inform campus micromobility policy discussions. The strong negative perceptions associated with scooter misplacement suggest that designated parking hubs and geofencing strategies could help improve campus operations and pedestrian accessibility. In addition, because safety perception was identified as an important predictor of e-scooter use, targeted safety awareness and educational initiatives may help improve rider behavior and address perceived operational safety concerns. This strategy ensures a balance between user adoption incentives and the safety/accessibility needs of the entire university community. Full article

Background/Objectives: Distal femoral physeal fractures are rare and particularly uncommon in very young patients, as they typically require a significant amount of kinetic energy. They carry a high risk of premature physeal closure and later growth disturbance. We aimed to describe the management and long-term outcome of an open distal femoral physeal fracture in a 6-year-old child. Methods: We report a previously healthy 6-year-old child sustained an open distal femoral physeal fracture in an electric scooter–motor vehicle collision. Emergency treatment included trauma assessment, resuscitation, intravenous cefazolin, urgent irrigation and debridement, open reduction, crossed smooth Kirschner-wire fixation, and immobilization. Long-term follow-up included growth prediction using the multiplier method. Results: The injury was classified intraoperatively as a Salter–Harris type I distal femoral physeal fracture. Despite timely surgical treatment, progressive limb-length discrepancy developed, increasing from 1.3 cm at 10 months to 6.5 cm over 5 years. Growth prediction estimated a final discrepancy of 7.32 cm at skeletal maturity, and contralateral distal femoral epiphysiodesis was performed. The literature confirms that displaced high-energy distal femoral physeal injuries in younger children carry a substantial risk of premature physeal closure and later corrective surgery. Conclusions: Open high-energy distal femoral physeal fractures in young children are limb-growth-threatening injuries. This case demonstrates that satisfactory initial fracture management does not eliminate the risk of later premature physeal closure, and that clinically important discrepancy evolves gradually over several years. Long-term follow-up and growth prediction are essential to guide timely corrective treatment to minimize the leg-length discrepancy in bone maturity. Full article

This study aimed to investigate how human, vehicle, and environment (HVE)-related factors and their interactions contribute to fall accidents related to electric scooters (e-scooters). Falls are the most common type of e-scooter accidents, and developing a thorough understanding of the factors that contribute to these accidents is critical for effective accident prevention. Unlike collisions, falls frequently result from the complex interaction among the rider, the vehicle, and the environment. To this end, this study conducted a systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines and uses the Haddon Matrix framework to identify and classify factors related to e-scooter fall accidents from HVE perspectives, spanning the pre-fall and fall phases. The findings suggest that e-scooter fall accidents are multifactorial, resulting from the interaction of HVE-related factors across accident phases rather than from a single cause. Human-related factors, vehicle attributes, and environmental conditions were all found to contribute to fall risk, with notable interactions identified across all three dimensions. This study contributes to a better understanding of the mechanisms underlying e-scooter fall accidents by systematically identifying these factors and examining their interactions, highlighting the need for further investigation into HVE interactions across diverse accident contexts. Full article

This paper conducts an experimental study to develop a response strategy for lithium-ion battery fires. Guided by the principle of “first control, then extinguish”, the strategy integrates a lithium-ion battery-specific fire-controlling blanket with castable fire-extinguishing agents. Both fire tests of e-bikes and lithium-ion batteries are conducted. From e-bike fire tests, the feasibility of rescuers conducting close-range disposal of LIB (lithium-ion battery) fires is analyzed from three perspectives, i.e., fire evolution stage, battery splashing and high temperature. The results indicate a high risk of fire spread, as well as a strong likelihood of human injury caused by flying LIB debris and extremely hot gases. Subsequently, the fire-controlling capability of the fire blanket is validated. It not only blocks splashing batteries and jet flames, reducing combustion intensity, but also offers a safe way for personnel to operate the portable fire extinguishers. Through two castable extinguishing agents tested, the perfluorohexanone-based agent outperforms the water-based alternative. The reasons are as follows. First, perfluorohexanone evaporates easily in the low-temperature, confined environment created by the fire blanket. Second, it possesses both physical and chemical fire-extinguishing capabilities, ultimately delivering a more potent combustion suppression effect. Full article

This study presents a hybrid Non-Uniform Rational B-Spline (NURBS) methodology for the geometric reconstruction of topology-optimized structural components. NURBS are employed exclusively as a post-processing tool; all structural analyses are performed using standard finite elements (SOLID187 elements, ANSYS Mechanical R19.2), and isogeometric analysis (IGA) is not used. The methodology is validated on an Al 6061-T6 electric scooter neck under a 600 N static load. Two SIMP optimization iterations followed by a hybrid NURBS reconstruction reduce the component mass from 1.247 kg to 0.531 kg, achieving a 57.4% mass reduction. Finite element re-validation of the reconstructed geometry yields a maximum von Mises stress of 126.45 MPa (safety factor, SF = 2.18, exceeding the 2.0 requirement), a maximum deflection of 2.31 mm, and a first natural frequency of 127 Hz. Mesh convergence between the 2.5 mm and 1.25 mm refinements is Δ = 0.90%. Relative to the direct SIMP output (201 MPa), NURBS reconstruction reduces the peak stress by 37%, demonstrating that geometric post-processing is not a neutral step but a critical determinant of structural performance. Both fully automated STL reconstruction and edge-based NURBS reconstruction failed for this geometry class due to non-manifold topology and patch discontinuities, respectively. The proposed hybrid region-decomposition approach is the only method that has produced a watertight, FEA-compatible CAD model. Full article

Urban roundabouts present significant design challenges for the integration of micro-mobility, yet comparative evidence regarding user behavior remains limited. As cities transition toward sustainable transport networks, understanding the operational needs of different micromobility modes is essential for urban planning. This study investigates the dynamic strategies of micromobility users through a controlled field experiment at a mini-roundabout in Gravina di Catania, Italy. Twenty experienced riders executed crossings using conventional bicycles and electric scooters. Utilizing drone recordings and open-source tracking, the analysis extracted speed, longitudinal acceleration, and path radius across 80 maneuvers. The findings reveal that behavior is highly dependent on vehicle type and geometric deflection. On highly deflected trajectories, e-scooters selected wider radii and achieved up to 15% higher speeds and accelerations than bicycles, whereas on gentler trajectories, they adopted more conservative, tighter lines with intense braking. Bicycles exhibited smaller, less systematic adjustments. These significant kinematic differences indicate that bicycles and e-scooters possess distinct performance envelopes. Treating them as a single legal or design class obscures stability disparities influencing conflict risk. Ultimately, this research provides empirical insights to guide urban planners in redesigning intersections, emphasizing that tailored infrastructure and targeted speed management are critical steps toward safer, truly sustainable urban mobility. Full article

This study presents a stator-focused electromagnetic optimization of a 350 W, 27-slot, 30-pole outer-rotor brushless direct current (BLDC) motor developed for electric scooter applications. Unlike conventional redesign approaches that modify rotor topology or overall motor dimensions, the proposed methodology preserves the rotor structure and external geometry of a commercially validated reference motor and improves performance primarily through targeted stator geometric refinement, with minor adjustments in the winding configuration. A two-stage optimization strategy combining parametric analysis and genetic algorithm (GA)-based multi-objective optimization is implemented to minimize cogging torque and torque ripple while maximizing efficiency. Finite element analyses (FEA) were conducted to evaluate back electromotive force (back-EMF) characteristics, magnetic flux density distribution, torque behavior, and current density. Experimental validation confirms a 54.86% reduction in cogging torque (from 257 mNm to 116 mNm), a 19.6% decrease in torque ripple, a 6.17% reduction in maximum current density, and a 2–3% improvement in efficiency within the nominal load range (5.2–6.45 Nm), reaching 85.69% efficiency at 350 W output power. The results demonstrate that systematic stator geometry optimization, supported by minor winding modifications, can significantly enhance efficiency, torque smoothness, and thermal margin without increasing motor size, rated power, or manufacturing complexity. This work provides a practical and manufacturable design pathway for high-performance outer rotor BLDC motors in light electric vehicle (LEV) propulsion systems. Full article

Shared e-scooter systems are frequently characterized as zero-emission mobility solutions; however, lifecycle greenhouse gas (GHG) emissions depend on manufacturing, electricity generation, and operational logistics. While conventional life cycle assessment (LCA) studies quantify environmental impacts using static average parameters, they rarely integrate lifecycle emissions into real-time fleet decision-making. This study proposes a formally defined carbon-aware operational framework that integrates ride-level telemetry, time-varying electricity grid carbon intensity, amortized production emissions, and dynamically allocated logistics impacts into a unified optimization architecture. Lifecycle emissions are computed at ride-level granularity and incorporated into charging and rebalancing decisions through a constrained optimization framework. A multi-objective extension is introduced to account for environmental–economic trade-offs. An illustrative simulation of 1000 rides was conducted to evaluate the operational performance of the framework. Under the assumed baseline scenario, the illustrative carbon-aware simulation indicated a potential reduction of up to 24.5% relative to conventional scheduling. Sensitivity analysis across variations in grid carbon intensity, scooter lifetime, energy consumption, and logistics emissions demonstrated reduction outcomes ranging between 18% and 29%, indicating robustness to parameter uncertainty. The study does not present large-scale empirical validation but provides a mathematically formalized decision-support architecture that operationalizes lifecycle assessment within shared micro-mobility fleet management. The results suggest that integrating carbon metrics into operational control may substantially enhance the environmental performance of shared e-scooter systems. Future research should validate the framework using real-world fleet data and incorporate a comprehensive economic assessment. The proposed framework provides a scalable methodological basis for integrating environmental metrics into real-time micro-mobility management and urban sustainability planning. Full article

Background: In the past ten years, the number of publications on injuries associated with electric scooters (e-scooters) has been increasing continuously. The aim of this systematic review and meta-analysis was to synthesize the original study results on injury types, injury severity, clinical care, accident mechanisms, risk factors, and patient characteristics associated with e-scooter accidents. Methods: The literature search was conducted in PubMed, EMBASE and Medline. We included quantitative clinical studies published between 07/2019 and 07/2024 that report e-scooter-associated injuries in patients who presented to an emergency department. Variables that were reported as proportions (e.g., frequency of extremity fractures) were summarized using a proportional meta-analysis. Parameters on a continuous scale were combined using a meta-analysis of the arithmetic means. Results: Among 524 unique records, 149 articles met the inclusion criteria, and 68 were eligible for quantitative analyses. Most e-scooter patients sustained injuries to the head and face with a pooled frequency of 42.1% (95% CI 38.7–45.4). Injuries of the upper extremities were estimated at 40.1% of patients (95% CI 35.8–44.4). Fractures of the extremities occurred with a pooled frequency of 25.7% (95% CI 22.5–28.9). An estimated proportion of 2.3% (95% CI 1.6–3.0) sustained severe traumatic brain injuries. Determined by the Injury Severity Score (ISS), 2.8% (95% CI 1.5–4.1) of the e-scooter patients were severely injured (ISS ≥ 16). Conclusions: Injuries to the head and face as well as the upper extremities are the most common causes for emergency department visits following e-scooter accidents. One in four patients presented with extremity fractures. Severe injuries, however, affect less than three percent of e-scooter patients. Full article

We investigated stator–rotor structure optimization for a commercial electric scooter motor through geometric modeling and comparative analysis of various magnet configurations and arrangements. We improved magnetic circuit distribution to enhance output performance, efficiency, and overall motor characteristics. Sensitivity analysis was conducted to identify the dominant design parameters. Magnetic bridges were then incorporated on both outer sides of the rotor magnets to increase magnetic flux density and reduce leakage flux. The Taguchi method was applied to determine the optimal parameter set. Comparative simulations between the optimized and baseline commercial motor revealed that, at a rated current of 87 A and rated voltage of 96 V, the optimized design achieved an efficiency improvement from 89.14 to 90.28% (+1.28%), a torque increase from 22.84 to 23.29 N·m (+0.45 N·m), and a power output enhancement from 7104.78 to 8053.44 W (+948.65 W). The results confirm that the proposed rotor design yields superior performance across efficiency, torque, and power output compared with the commercial reference motor. Full article