Utility Vehicle Research Articles

Regression algorithm based residual range prediction and validation on EV travel data

ABSTRACT Range anxiety is one of the daunting facts that holds back customers from purchasing electric vehicles (EVs). The range of an EV depends on many internal and external parameters that cause large deviations in the energy left in the battery. taxi and bus fleets also decide on a fixed distance of travel after which they recharge the battery so as to avoid unwanted last-minute surprises. In a country like India, range prediction methods have to be extensively worked out due to inadequate charging infrastructure and vivid range of climatic and terrain conditions. This paper presents residual range prediction methods implemented in two different models of EVs based on real travel data on Indian roads. The data collected are from two compact Sports Utility Vehicles (SUV) in the Indian automobile sector, namely MGZSEV and TATA Nexon EV. The travel data of MGZSEV was collected from the mobile application whereas the data collected from Tata Nexon EV was from the dashboard display of the vehicle. Two different approaches were implemented, first being the conventional vehicle dynamics based mathematical method and second using Machine Learning (ML) based algorithms. The analysis and plots are discussed in detail and interpreted.

The Role of Marketing Campaigns Through Social Media and Perceived Usefulness on Purchase Intention of Electric Vehicle

This study investigates consumers' perceptions of the utility of electric vehicles and the effectiveness of social media marketing efforts on EV purchase intentions. Marketers and lawmakers must understand the drivers of electric vehicle adoption in light of increasing concerns about environmental sustainability and technological development. The research strategy adopted for the study is a quantitative approach based on a survey. A cross-section of social media users exposed to advertisements regarding electric vehicles were surveyed. The perceived utility of EVs includes environmental advantages, cost savings, and performance measured by the questionnaire, as well as the exposure to social media marketing activities and intention to purchase. Regression analysis is used as the analytical approach to finding how the variables relate. Therefore, a positive relationship exists between social media marketing efforts and perceived usefulness intending to purchase. In instances where consumers are subjected to persuasive social media advertisements describing the benefits of EVs, and when they view an EV as practical, they show a greater tendency to express an intention to buy. The practical implications of this study will help marketers devise social media ads that successfully promote electric vehicle adoption; it also adds to the literature on sustainable consumerism. This study's results will benefit politicians who want to encourage the switch toward electric mobility.

Anatomy of a Crash: Analysis of 102 Pedestrian and Bicyclist Fatalities.

Pedestrian and bicyclist fatalities have increased over the past decade in the United States. Factors proposed to explain this increase include the increased popularity of larger passenger vehicles, road design to accommodate faster-moving traffic, and poor road infrastructure. We analyzed a series of 102 pedestrian and bicyclist fatalities to determine which factors were involved. Results demonstrated substance abuse as the most common pertinent decedent medical history, a disproportionate number of crashes occurred during evening/nighttime hours, and most crashes involved larger passenger vehicles. The percentage of cases involving sport utility vehicles (SUVs) has increased over time. Injury pattern analysis demonstrated that smaller passenger vehicles at lower speeds were more likely to cause lower extremity fractures compared to SUVs. Alcohol was the most common decedent substance detected on toxicology, and decedents with a previous mental health history were more likely to have positive toxicology for illicit substances than those without. Sixty-three percent of cases lacked sidewalks, and 85% of cases lacked bike lanes. We compared the trends that we saw on a small scale to those seen nationally and uncovered certain novel associations from the perspective of medical examination.

Lipid extraction from Azolla filiculoides and its applications for catalyzed biodiesel production

The growing recognition that first-generation biofuels from food crops and oil seeds are inadequate has spurred global discussions on sustainable renewable energy production. This concern has increased interest in second-generation biofuels from non-food feedstocks, such as algae. Azolla is identified as a highly promising macroalgae for the production of biodiesel. This study investigates the efficiency of lipid extraction and biodiesel quality from Azolla, a promising macroalgae. Characterization techniques including GC-MS (Gas Chromatography-Mass Spectrometry), FT-IR (Fourier Transform Infrared Spectroscopy), and NMR 1H and 13C (Nuclear Magnetic Resonance) spectroscopy were employed. The findings show that the kinematic viscosity and flash point of the biodiesel are 4.32 mm2/s at 40 °C and 165 °C, respectively. Trace element analysis revealed no major environmental concerns. Overall, the biodiesel produced from Azolla demonstrates potential as a sustainable and locally supplied substitute for diesel fuel in utility vehicles.

IMPROVED TECHNIQUES FOR ASSESSING RIDE QUALITY ON CONCRETE PAVEMENTS

Under current procedures used in Australia for testing and interpretation of road profiles it is difficult to identify and isolate pavement sections responsible for unpleasant ride vibration. For the construction of new concrete pavements, in particular, where subsequent correction of profiles is very expensive, there is a need for improved procedures to give early feedback of the ultimate ride quality. To help identify and treat pavement problem areas, numerical models were developed to simulate ride vibration and pavement grinding. The ride and grind simulation models cover four generic vehicle classes – passenger cars, heavy commercial vehicles, offroad recreational and sports utility vehicles and motorcycles – and conventional pavement grinding equipment. A number of vibration response presentation formats were developed to help quantify ride vibration severity, intrinsic unevenness and grind treatment effectiveness. The models and key findings of the study are presented in this paper through contrasting examples of responses from the models to a selection of road profiles before and after virtual (theoretical) remedial grind treatment.

RIDE QUALITY MEASUREMENT AND USER RATINGS: INITIAL ASSESSMENT OF IMPROVED TECHNIQUES

Improved techniques for assessing ride quality have been developed by the authors that closely simulate actual vehicle ride dynamics and the responses of humans to whole-body vibration. Using numerical models to simulate four generic road-user vehicle classes – passenger cars, heavy commercial vehicles (trucks), off-road recreational and sports utility vehicles (SUVs) and motorcycles – fundamental issues associated with current ride quality measurements are addressed leading to more robust and accurate estimates of pavement rideability. Initial field trials and tests of the proposed ride quality model for a passenger car were conducted. To assess the effectiveness of the model as a ride quality predictor, the overall modelled ride responses were compared with actual measured ride vibrations (objective measures) and road-user ride ratings (subjective measures), all taken on the same sections of pavements. For the objective measures of ride quality portable vibration measuring equipment, comprising accelerometers, event markers and a data logger were assembled, customised and tested. In later versions of the equipment, also described in this paper, GPS tracking was incorporated to provide precise time-based recordings of location and speed. Developed specifically for this project, the equipment is small in size, completely self-contained, and is readily adapted for use in both small and large vehicles (motorcycles, cars, SUVs and trucks). The initial study found there was good agreement between the modelled responses, vibration measurements and subjective ratings. A further larger study is planned, which is discussed in this paper.

Underwater DVL Optimization Network (UDON): A Learning-Based DVL Velocity Optimizing Method for Underwater Navigation

As the exploration of marine resources continues to deepen, the utilization of Autonomous Underwater Vehicles (AUVs) for conducting marine resource surveys and underwater environmental mapping has become a common practice. In order to successfully accomplish exploration missions, AUVs require high-precision underwater navigation information as support. A Strapdown Inertial Navigation System (SINS) can provide AUVs with accurate attitude and heading information, while a Doppler Velocity Log (DVL) is capable of measuring the velocity vector of the AUVs. Therefore, the integrated SINS/DVL navigation system can furnish the necessary navigational information required by an AUV. In response to the issue of DVL being susceptible to external environmental interference, leading to reduced measurement accuracy, this paper proposes an end-to-end deep-learning approach to enhance the accuracy of DVL velocity vector measurements. The utilization of the raw measurement data from an Inertial Measurement Unit (IMU), which includes gyroscopes and accelerometers, to assist the DVL in velocity vector estimation and to refine it towards the Global Positioning System (GPS) velocity vector, compensates for the external environmental interference affecting the DVL, therefore enhancing the navigation accuracy. To evaluate the proposed method, we conducted lake experiments using SINS and DVL equipment, from which the collected data were organized into a dataset for training and assessing the model. The research results show that the DVL vector predicted by our model can achieve a maximum improvement of 69.26% in terms of root mean square error and a maximum improvement of 78.62% in terms of relative trajectory error.

Real-Time UAV Recognition Through Advanced Machine Learning for Enhanced Military Surveillance

In an era where the military utilization of Unmanned Aerial Vehicles (UAVs) has become essential for surveillance and operational operations, our study tackles the growing demand for real-time, accurate UAV recognition. The rise of UAVs presents numerous safety hazards, requiring systems that distinguish UAVs from non-threatening phenomena, such as birds. This research study conducts a comparative examination of advanced machine learning models, aiming to address the challenge of real-time aerial classification in diverse environmental conditions without model retraining. This research employs extensive datasets to train and validate models such as Neural Networks, Support Vector Machines, ensemble methods, and Gradient Boosting Machines. The fashions are evaluated based on accuracy, forgetfulness, and processing efficiency—criteria determining the viability of real-time operational scenarios. The findings indicate that Neural Networks exhibit enhanced performance, demonstrating exceptional accuracy in distinguishing UAVs from birds. This culminates in our primary assertion: Neural Networks possess vital operational security ramifications and can markedly enhance the allocation of defense resources. The findings significantly improve surveillance systems, highlighting the effectiveness of machine-learning methods in real-time UAV identification. Moreover, incorporating Neural Network systems into military defenses is recommended to enhance decision-making capabilities and security operations. Foresee forthcoming UAV developments and advocate for regular model updates to keep up with increasingly nimble and perhaps stealthier drone designs.

Development of wireless vehicle-to-grid (V2G) for flexible resource utilization of autonomous vehicles

Development of wireless vehicle-to-grid (V2G) for flexible resource utilization of autonomous vehicles

Utilization of Unmanned Aerial Vehicle (UAV) Technology for The Development of Tourism at Larangan Indah Beach Tegal Regency Indonesia

Abstract Larangan Indah Beach is one of the tourist attractions on the north coast of Tegal Regency, Central Java Province. Based on the 2012-2032 Tegal Regency RTRW regional regulations, the northern coastal area in Tegal Regency is included in the district’s strategic area and has great potential for development, including Larangan Indah Beach. The current condition has not been developed optimally. This research aims to 1) mapping Larangan Indah Beach, 2) determine the internal and external potential found in the coastal area of Larangan Indah Beach and 3) carry out a development plan for Larangan Indah Beach. The research method used in this research is a survey research method by processing aerial photo data, then interpreting aerial photos using field observations and analyzing spatial data for coastal mapping and planning tourism development based on existing potential using internal and external potential scoring. The results of scoring Larangan Indah Beach get a score of 39 which is included in the medium category, showing a good balance between attractions and tourists by making the basis for developing beach tourism areas. Development is carried out by adding attractions such as windmills and ATV rides, as well as improving amenities such as homestays, information centers, parking lots, souvenir stallss and adding road signs.

Multi-physics simulation modeling and energy flow characterization of thermal management system for a sport utility vehicle under high-temperature conditions

Multi-physics simulation modeling and energy flow characterization of thermal management system for a sport utility vehicle under high-temperature conditions

A novel real-time structural acceleration-based methodology for detecting support loss under PCC pavement subjected to vehicle loading

ABSTRACT Support loss is a concealed distress in Portland cement concrete (PCC) pavements. This study proposes a real-time methodology to detect support loss under PCC pavements using structural acceleration responses. Full-scale tests were conducted under different support loss conditions. The sports utility vehicle (SUV), truck, and FWD were used. The results revealed that the main frequency of acceleration signals of PCC slabs under FWD and vehicle loads varied between 20~25 Hz and 10~15 Hz, respectively. When support loss occurs, both the acceleration amplitude and the signal energy within high-frequency range increase. By calculating the signal energy of acceleration response at slab corner (Scor) or longitudinal edge midpoint (Smid), support loss is indicated at slab corner when signal energy at Scor increases by about 90 times or signal energy at Smid increases by about 10 times. Additionally, by calculating the ratio of signal energy within high-frequency range to that within low-frequency range (ER) of acceleration signals at Smid, support loss at slab center is considered to have occurred when ER exceeds 3. To reduce costs, only one sensor can be placed at Smid. The proposed method has advantages of not requiring traffic closure, realizing real-time monitoring, and facilitating intelligent maintenance.

Design of a three-speed automatic transmission system with reverse for all-terrain vehicles (ATV)

This work proposes the design and simulation of a conventional three-speed automatic transmission, including reverse gear, for an all-terrain utility vehicle (ATV). The proposed design was generated considering the power requirements needed for the selected vehicle to operate on a specific driving cycle over uneven terrain with variable slopes ranging from -0.5° to 2.5°. A vehicle with well-defined mass, dimensions, and engine displacement was selected as the design criteria. Using the numerical software MATLAB, the power requirements were calculated, establishing that the transmission ratios range from 0.18 to 1. Using commercial Multibody Dynamics (MBD) software, ADAMS, the reliability of the proper functioning of the gear trains was determined based on boundary conditions. Similarly, to verify that the selected materials and components can withstand critical loads, structural static simulations were carried out using the finite element method with the commercial software ANSYS.

Carbon Footprint of a Windshield Reinforcement Component for a Sport Utility Vehicle

In this study, the carbon footprint of a steel-based windshield reinforcement component assembled in a sport utility vehicle was calculated in three different stages: steelmaking, stamping, and middle-of-use. Possible solutions to decrease carbon emissions were evidenced, such as the purchasing of steel made through low-impact technologies and the exploitation of the green energy grid to power up stamping machines. The life cycle assessment methodology was used to calculate the carbon footprint. Four different steels provided by different suppliers were compared in order to highlight the greenest material for both the steelmaking and stamping processes and the best supplier from an environmental point of view. In addition, the carbon footprint related to the component weight in vehicles with different traction set-ups, i.e., internal combustion engine, mild hybrid electric, and battery electric, was reported. To reduce the carbon footprint, electric arc furnace-based steelmaking and cold stamping were the best options. In addition, component weight reduction (for instance, changing materials) allowed a decrease in fuel and/or energy consumption, with carbon footprint benefits.

Assessment of Stratified Speed Characteristics and Compliance with Posted Speed Limit in an Urban Area: A Case Study of Section of Karnali Highway, Nepal

Speed is the fundamental element of traffic engineering which is related to safety, time, comfort, convenience, and economics of the transportation system. Speed tends to reduce while the vehicles enter the urban areas even within the highway. Urban areas even have posted speed limits to control the speed characteristics, but the obeyance of the posted limit is still questionable. This research examines the speed characteristics of various means of transportation within urban areas. Section of roads within urban areas of Surkhet district along Karnali Highway (NH58) is considered as a study area and a manual method of data collection was adopted. The stratified samples of speed covering all means of transportation were collected during off-peak hours. Even a small section of roads has varying speed limits ranging from 20 to 40kmph. The collected data were used to calculate different kinds of speeds for each category of vehicles and further combined based on volume proportion to come up with average speed. The road is divided into four lanes, which motivates speeding, and it was observed the average speed of 2-wheelers, cars, and utility vehicles was between 30-40kmph. Data assessment shows the average speed limit was within 40kmph, which is legally mandated by the Motor Vehicle and Transport Management Act 2049, which is even taught during the process of licensing to drivers. Hence, the installation of other speed limit signs needs proper education and awareness followed by proper enforcement techniques for effective implementation of the posted speed limit.

Analysis of desert traffic accidents: A retrospective study

Introduction: Motor vehicle accidents (MVAs) are a leading cause of mortality and morbidity worldwide. There is limited literature on the injuries resulting from desert off-road driving accidents. This study aims to delineate the attributes of desert MVA and associated injuries as observed in Qatar. Methods: This is a Qatar-based retrospective descriptive multicenter study from electronic medical records (EMRs) between 2016 and 2022. Patients were evaluated based on demographic characteristics, type of injury and vehicle involved, injury locations, injury severity, treatments applied, length of hospital stay, number and outcome of surgeries, disability on discharge, and mortality. Results: Findings reveal a rising trend in accidents from October to March, peaking between 4:00 p.m. and 8:00 p.m. The patients were predominantly male under 40 years of age, not adhering to personal protective measures, and accidents often involved all-terrain vehicles (ATVs) and sport utility vehicles (SUVs). Blunt trauma emerged as the primary injury type, with orthopedic injuries being the most frequent. Most patients did not undergo surgery and had an average hospital stay of 2.9 days. A 1.5% mortality rate and 6.7% disability rate were observed. Conclusion: This study fills a critical gap in understanding desert traffic accidents in a Gulf Cooperation Council country. This study underscores the need for targeted interventions and public awareness campaigns tailored to the unique challenges of desert driving.

Numerical Analysis on the Aerodynamic Characteristics of SUV Car Model Install with Vortex Generator

The investigation of automotive aerodynamics involves analysing several forces operating on a car while driving on the road, such as drag and lift forces. The flow separation at the vehicle's rear end is one of the primary causes of aerodynamic drag for automobile vehicles. It is feasible to improve fuel efficiency by lowering the drag force. The study focuses on the influence of a vortex generator (VG) on the aerodynamics of a sport utility vehicle (SUV) car. The study aims to simulate fluid flow analysis for an SUV car that uses VG and without VG, as well as to assess the impact of a different configuration of VG and a varying number and fillet radius of VG. The number of VG are 3, 5, and 9. The different fillet radius of VG are 5, 10, and 15 mm. Using the Reynold-Averaged Navier Stokes Equation (RANS) in the numerical simulation, the Reynolds number at the computational domain is 1.1391 × 107 and 1.4808 × 107, which is determined by the height of the model and the freestream velocity. The results show that aerodynamic characteristics are significantly influenced by the number of VG and various size radius fillets of VG. From the result, 9 number of VG and 5 mm fillet radius obtained the lowest value of coefficient of drag, Cd compared with the others which is Cd = 0.3747 for 27.78 m/s and Cd = 0.5031 for 33.33 m/s, respectively. Furthermore, the analysis of flow structures suggested the locations of vortex formation and wake turbulence at the rear of the vehicle. In contrast, the 9 number of VG with a 5 mm radius fillet of VG emerged as the most suitable VG for this scenario, exhibiting a Cd value closest to the base model and the lowest Cd value.

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Design of Microstrip Antenna Array for Autonomous Vehicles

The utilization of Autonomous vehicles has been rapidly increasing in both civilian and military applications. This is primarily due to their exceptional communication capabilities with ground clients, as well as their inherent properties such as adaptability, mobility, and flexibility. To effectively monitor and control the deployment of Autonomous vehicles, a 5G wireless network can be utilized alongside other devices as user equipment (UE). Through the utilization of a highly directive microstrip patch antenna (MPA) functioning within a dedicated frequency band, the Autonomous vehicle is able to establish effective long-range communication, overcoming signal degradation and minimizing interference from other channels within a confined area. The adoption of MPA is especially advised for Unmanned Aerial Vehicles (UAVs) due to its characteristics such as being lightweight, cost-efficient, small in size, and having a flat structure. This study details the development and simulation of a highly directive single-band 1x2 and 1x4 antenna array designed to operate at a 5.8 GHz frequency specifically tailored for Autonomous vehicle use. To enhance directivity and ensure structural robustness, the Roger RT5880 material has been utilized as a substrate, known for its lower dielectric constant.. The results demonstrate a high gain of 9.16 dBi and 11.4 dBi for the 1x2 and 1x4 antenna arrays respectively, while maintaining a compact size. The simulated 1x4 antenna array was fabricated using the Roger RT5880 material, and this array was tested in the microwave communication's laboratory at College of Engineering, Al-Nahrain University. The antenna presents good results by means of return losses (-26.672 dB) which equivalent to VSWR of 1.098.

Analysis of the Impact of the Comfort Systems in Sport Utility Vehicles on the Exhaust Emissions Measured under Worldwide Harmonized Light Vehicles Test Cycles Conditions

Analysis of the Impact of the Comfort Systems in Sport Utility Vehicles on the Exhaust Emissions Measured under Worldwide Harmonized Light Vehicles Test Cycles Conditions