Development Of Vehicles Research Articles

Theoretical evaluation of C24 nanocage functionalization with protons for enhanced sulfacetamide drug delivery: A DFT study with non-covalent interaction analyses

In the realm of drug design, achieving precise and effective drug delivery poses a significant challenge. In this computational study, we explore the capacity of pristine C24 nanocages and those modified with 1H+ and 2H+ ions to serve as carriers for the sulfacetamide (SA) drug, employing density functional theory (DFT) calculations. Geometry optimizations of the SA&C24, SA&H+C24, and SA&2H+C24 complexes were conducted at the cam-B3LYP/6–31+G (d, p) level of theory. The optimized structures of all complexes exhibit local minima on the potential energy surface, indicated by the absence of imaginary frequencies, which confirms their thermodynamic stability. The negative values of adsorption energy (Eads) denote an exothermic and favorable adsorption process, with H+ ion functionalization enhancing the drug's binding affinity to the nanocages. Further analysis of the structural properties of the complexes was conducted through natural bond orbital (NBO) charge distribution, dipole moment calculations, and frontier molecular orbital analysis. Additionally, Atoms in Molecules (AIM), reduced density gradient (RDG), and electron localization function (ELF) analyses were employed to elucidate the nature of intermolecular interactions governing the drug-nanocage binding. UV-visible and nonlinear optical (NLO) response calculations reveal the potential of both pristine and functionalized C24 nanocages as optical sensors for SA drug detection. Our findings suggest that these nanocages hold promise for the development of sensitive drug delivery vehicles and targeted therapeutic agents.

On the Influencing Factors of the Development of New Energy Vehicles in China from the Perspective of Low-carbon Economy

On the Influencing Factors of the Development of New Energy Vehicles in China from the Perspective of Low-carbon Economy

When electric vehicles bump into sharing economy: Consumer's variety seeking in the sustainable transportation

The development of electric vehicles incurs the consumer's variety seeking in the sharing economy. In addition to being passengers on the sharing platform, customers can rent electric vehicles from the rental company as ride-hailing drivers, rather than purchasing from the manufacturing firm. In this article, we set up a game-theoretic model to study the customer's variety-seeking behavior in the new frenemy partnership and solve the equilibrium pricing strategy and quality decision for the rental company and the sharing platform. The numerical experiments show that the rental company's price is less influenced by the valuation heterogeneity, but the sharing platform's price is the opposite. Given some real-world examples of product ownership and product usage in sustainable transportation, we discuss the consumer's variety seeking and the company/platform's pricing strategy from both the passenger and driver sides.

Integrated Waverider Forebody/Inlet Fusion Method Based on Discrete Point Cloud Reconstruction

The integrated design of waverider forebodies and inlets is considered a critical challenge in high Mach number vehicle development. To facilitate the rapid construction of integrated geometrical models for waverider forebodies and inlets during the conceptual design phase, a method based on discrete point cloud reconstruction has been proposed. In this method, the geometries of the waverider body and inlet are used as inputs and decomposed into the point cloud under discrete rules. This point cloud is refitted to generate new section lines, which are then lofted into an integrated shape under the constraints of guide curves. By modifying the coordinates of the point cloud positions, the geometric configuration of the integrated shape can be rapidly adjusted, providing initial support for subsequent aerodynamic optimization and thermal protection. Using this method, an integrated approach was applied to a waverider forebody and inward-turning inlet in a tandem configuration. This achieved body-inlet matching and integration, resulting in a 15.6% improvement in the inlet’s total pressure recovery coefficient. The integration time was reduced to just 3.18% of the time required for traditional manual adjustments. Additionally, optimization based on the discrete point cloud enhanced the lift-to-drag ratio by 7.83%, demonstrating the feasibility of the proposed method.

Shifting towards Electric Vehicles: A Case Study of Mercedes-Benz from the Perspective of Cross-Functional Teams and Workforce Transformation

The automotive industry’s shift towards electric vehicles (EVs) is driven by technological advancements and environmental concerns. This paper examines Mercedes-Benz’s strategy in this transition, highlighting the challenges and opportunities involved. Using thematic analysis of semi-structured interviews with key professionals at Mercedes-Benz, the study reveals a dual strategy: integrating new talents with specific EV competencies and upskilling the existing workforce. This approach reflects the company’s recognition of evolving vehicle development requirements and commitment to maintaining a skilled workforce. Emphasis on data-driven functions highlights the industry’s shift towards technological advancements. The transition significantly impacts workforce roles, necessitating role reassignment and collaborative planning, indicating a culture of inclusivity and proactive change management. Challenges include the importance of mindset change and adaptability among employees, as well as managing overlapping traditional and EV projects, leading to increased workloads and compressed timelines. Tailored training and development strategies are essential for a comprehensive transition. Mercedes-Benz’s commitment to an electric-only strategy signals a clear future direction. However, this raises questions about workforce preparedness and ongoing skill development. The study offers insights into managing workforce transformation in the EV transition, contributing to academic discussions and providing practical guidance for industry professionals.

Unveiling gap acceptance behaviour during lane change with EDIV data: A deep dive into driving behaviour on expressway using a three level mixed effect linear regression approach

Lane change has a potential significance in road safety. Gap acceptance phenomena serves as a primary and critical phase in lane change maneuver. This study aims to investigate the gap acceptance behaviour of drivers during lane changes on expressways, with a focus on understanding how various factors influence drivers' decisions to change lanes. An extensive dataset collected through various sensors tailored for expressway driving, known as the ‘Expressway Drive: Instrumented Vehicle (EDIV) Dataset’ is utilized. Driving data from 59 drivers covering a distance of around 4000 km was used in the current study. Total 2578 lane changing events are identified through computing lateral deviations measured through 3D LiDAR sensor. Substantial differences are observed within the groups in primary analysis which suggest that lane-change direction significantly affect gap acceptance. To effectively manage both intra- and inter-cluster variances, this study employs two separate three levels mixed-effects linear models. These models account for the interdependence of gap acceptance characteristics within individual drivers and for different directions of lane changes by incorporating random effects. Furthermore, these models examine relationships between lead/ lag gap acceptance and the various influencing factors as fixed effects. It was found that factors such as speed of the subject vehicle, gap position, relative speeds, and surrounding vehicle types had influence on gap acceptance during lane changes on expressways. The insights gained from this study could inform the development of advanced driver assistance systems (ADAS) as well as development of autonomous vehicles, contributing to improved road safety and traffic flow management in high-speed environments.

Study on the role of d electronic donor in Ni-rich layered oxide cathode materials for Li-ion battery

The further development of electrochemical devices and electric vehicles requires advanced Li-ion battery with higher energy density and longer lifetimes. Ni-rich LiNi0.8Co0.1Mn0.1O2 layered oxide cathodes are receiving increased attention due to its high specific capacity. Nevertheless, the role of d electrons in Ni-rich cathodes has not been uniformly reported, which hinders the design of high-performance Ni-rich cathodes. To address this issue, the role of d electronic donor in Ni-rich layered oxide cathode materials was investigated by first principles calculations and explored the mechanism for enhancing the electrochemical performance in this work. The results show that the d electronic donor V and Mo can elevate the intercalation potential, improve the stability, and enhance the diffusion rate of Li-ions in Ni-rich cathode. This theoretical study complements the mechanism for improving the electrochemical performance of Ni-rich cathode, and provides a theoretical basis for the design of high-performance Li-ion battery.

From properties of zirconium carbide to the reverse design of ultra‐high temperature CMCs

AbstractThe development and commercialization of aerospace vehicles have posed significant challenges to the performance requirements for the corresponding materials. To meet these challenges, ceramic matrix composites (CMCs) have been developed and are widely used in the aerospace industry. However, their stability under extreme environmental conditions still needs to be improved. In this review, some properties of zirconium carbide (ZrC), which are related to extreme environmental applications of CMC are discussed first. Then, the effect of ZrC on the properties of CMC is comprehensively reviewed. ZrC can be introduced into the matrix and coated on the surface to increase the ablation resistance. The protection mechanisms of ZrC addition to CMCs, and the improvement in ZrC ablation resistance are explained. In addition, some perspectives on future developments are given.

Methods Review for Mitigating Motion Sickness of Electric Vehicle Passengers

Under the background of the continuous development of electric vehicles and intelligent cockpit technology, the problem of motion sickness is becoming more and more prominent, which has become an important factor affecting the riding experience. Therefore, this study centers on the problem of motion sickness, discusses its mechanism, influencing factors and mitigation methods, and aims to provide theoretical and practical support for improving the comfort and safety of passengers, which is of great significance for improving the riding environment and enhancing the quality of passenger travel.

Collaborative planning and control of heterogeneous multi-ground unmanned platforms

With the rapid development of intelligent vehicles, mobile robots, warehousing and logistics, exploration and testing and other industries, multi-platform collaborative work research has become the future research focus of ground platforms. This paper mainly studies the multi-ground platform collaborative system as follows: Combined with the multi-vehicle collaborative scenario, a three-layer system Artificial Intelligence control framework is proposed, which is composed of a task assignment layer, trajectory planning layer and multi-vehicle control layer. Firstly, the multi-car task assignment algorithm based on the Dubins curve is studied. Secondly, the vehicle motion planning algorithm based on the D*Lite algorithm is designed, and the driving direction and the optional grid range are improved. Then, the obstacle scene of multi-vehicle formation is analyzed, two obstacle avoidance schemes of formation are proposed and the process analysis is carried out. Finally, the application in engineering is conducted to verify the effectiveness of obstacle avoidance strategy, trajectory planning strategy and the overall system framework.

Living Greener Using EV/EM: A Review Study in Indonesia

The adoption of electric vehicles (EVs) in Indonesia is a pivotal step toward achieving environmental sustainability and fostering a green economy. This paper provides a comprehensive review of the development of electric vehicles in Indonesia, focusing on their role in promoting environmental sustainability. Through bibliometric analysis, this study examines key themes in the literature, identifies research trends, and explores factors influencing consumer purchase intentions. Our findings highlight the progress and challenges in the Indonesian EV sector and provide insights for policy-making and future research.

Design of bionic active folding flapping wing vehicle

Flapping wing vehicles mimic the wing flapping of flying creatures such as birds, bats and insects, and are characterized by simplicity, lightness, good concealment, high maneuverability and diversified flight attitudes. Currently, the development of wing-fluttering vehicles mainly focuses on wing-fluttering configurations, while there is little research on mimicking the large-scale active folding of wings of birds and bats. Here, we developed two types of large-scale folding wing vehicles with light mass and actively folded wings respectively, based on the property that the wings of flying organisms can be actively folded and contracted in a large scale, and tested their flight capabilities. The test results show that the latter vehicle, which combines the flapping wing mechanism and the active folding mechanism, has good flight performance and is able to accomplish the airborne folding of the wings on the basis of the flapping wing flight.

Improved ablation resistance of silicone/phenolic hybrid resin coatings with Zr-Si-O glass as anti-ablation layer

With the development of the new generation space vehicles, traditional phenolic resin (PR)-based coatings are no longer able to meet the increasingly harsh thermal environment. There is an urgent need to develop higher performance PR to ensure the flight safety of aircraft. Therefore, in this work, a novel hyperbranched polysiloxane containing Si-O-Zr bond was synthesized and then introduced into PR to develop homogeneous silicone/phenolic hybrid resin coatings. The TG results indicate that the introduction of Si-O-Zr bonds significantly improves the heat resistance of silicone. During ablation, the hyperbranched polysiloxane will undergo a ceramization to produce SiO2 and ZrO2 particles, both of which will subsequently generate a highly viscous Zr-Si-O glassy phase as anti-ablation layer. With the fluidity and self-healing properties, it can fill the gaps of the carbon layer and cover the surface of the carbon layer, giving the hybrid resin excellent ablative resistance. The linear ablation rate of the hybrid resin can be as low as 0.003 mm/s, which is an 80 % decrease compared to pure PR. The synthesized hybrid resin is expected to act as superior thermal protection coatings for the next generation of spaceflight.

Application Of Onboard PIV To Front Wheelhouse Wake Behavior Under Stationary Crosswind Conditions

When driving a car, the driver and passengers may feel larger drag from a headwind, the steering wheel would be taken away by a crosswind or pushed by a tailwind. Anytime, anywhere, we will encounter various scenes with natural wind under real world conditions such as urban, suburb and highway. We will develop the appropriate vehicle by simulating these conditions to satisfy with various customer requirements. For vehicle aerodynamic research and development, we are simply running simulations in physical- and cyber-space, that is, wind tunnel facility and computational fluid dynamics to reproduce these real worlds. However, it is not easy to simulate these wind inlet conditions, such as the temporal change in crosswind, especially, in wind tunnel facility. The stationary yaw angle by rotating turntable would reproduce a crosswind, if there is no turbulent generator system like in Pininfarina and Swing in FKFS. Therefore, we focus on the unsteady and asymmetrical flow from the front wheelhouse of the vehicle with tire rotation. There is three-dimensional complicated flow that are interacted by the flow from various directions, such as the flow along the front bumper, the flow along the rotating tire and wheel, the blowing flow from the rotating wheel opening area and the flow from the tire house. These complicated flow produces the front wheelhouse wake along the body side that affects the vehicle aerodynamic performance. Furthermore, there are asymmetrical flows around the vehicle by different front wheelhouse wake in windward and leeward sides. The larger side wake increases the aerodynamic drag, and the fluctuating side wake may induce the instability of the vehicle handling stability. Here, the proposed onboard 2D-3C PIV measurement system in the previous study enables us to measure same measurement area along the vehicle body side without change in optical configuration effectively, that indicates to reduce the time by resetting the optical configuration. We will investigate what kind of flow field should be focused on and controlled to prevent the vehicle instability by investigating these asymmetrical flow field around the vehicle under crosswinds.

Cybersecurity in Autonomous Vehicles—Are We Ready for the Challenge?

The rapid development and deployment of autonomous vehicles (AVs) present unprecedented opportunities and challenges in the transportation sector. While AVs promise enhanced safety, efficiency, and convenience, they also introduce significant cybersecurity vulnerabilities due to their reliance on advanced electronics, connectivity, and artificial intelligence (AI). This review examines the current state of cybersecurity in autonomous vehicles, identifying major threats such as remote hacking, sensor manipulation, data breaches, and denial of service (DoS) attacks. It also explores existing countermeasures including intrusion detection systems (IDSs), encryption, over-the-air (OTA) updates, and authentication protocols. Despite these efforts, numerous challenges remain, including the complexity of AV systems, lack of standardization, latency issues, and resource constraints. This review concludes by highlighting future directions in cybersecurity research and development, emphasizing the potential of AI and machine learning, blockchain technology, industry collaboration, and legislative measures to enhance the security of autonomous vehicles.

Advanced Systems for Detecting and Recognizing Traffic Objects

Traffic object detection and recognition systems have become critical components in the advancement of intelligent transportation systems (ITS). These systems leverage various technologies such as computer vision, machine learning, and sensor fusion to accurately identify and classify objects on the road, including vehicles, pedestrians, traffic signs, and obstacles. The integration of these technologies enhances traffic management, improves road safety, and facilitates the development of autonomous vehicles. This paper provides an overview of the state-of-the-art methods and technologies used in traffic object detection and recognition. It also discusses the challenges faced in real-world implementations, such as varying weather conditions, lighting changes, and occlusions, and explores potential solutions and future research directions to address these issues.

Improvement of Dynamic Characteristics of Purpose-Built Vehicles Using Semi-Active Suspension System.

The diversification of mobility into services such as smart stores and conference rooms has accelerated the development of purpose-built vehicles (PBVs)-vehicles designed for specific purposes that utilize an extended electric vehicle chassis and autonomous driving technology. Despite the standards on speed bump dimensions stipulated by the National Land Transportation Act of the Republic of Korea, real-world speed bumps feature varying widths and heights that deviate from these standards. In this study, a velocity equation was derived via regression analysis to achieve the desired dynamic characteristics for a PBV passing over speed bumps with varying shapes through two types of semi-active suspension control: proportional-integral-differential (PID) and linear-quadratic-regulator (LQR). For a cargo-transport PBV, the PID and LQR controllers increased the velocity by 23.74% and 50.74%, respectively, under different speed bump widths and by 19.44% and 38.31%, respectively, under different speed bump heights. Moreover, an analysis of the vibration dose value (VDV), an indicator of ride comfort, revealed that the VDVs calculated using the velocity equation were within an acceptable error range of 10% above the target VDV. These findings provide insights into the speed control required for different types of autonomous PBVs to ensure ride comfort, as well as minimize the driving duration, depending on the specific purpose of the vehicle.

Investigation on situation awareness model of unmanned aerial vehicle groups communication network based on adversarial network

With the widespread application and development of unmanned aerial vehicle (UAV) technology, ensuring the security and stability of UAV swarm communication networks has become crucial. Given the diverse forms of interference and attacks in current networks, this poses a serious threat to the normal operation of UAV swarm communication. Therefore, how to accurately identify and effectively counter these network threats has become the focus of research. This study comprehensively evaluates the core technology of UAV swarm communication network situational awareness and constructs a situational awareness model based on adversarial networks. The model utilizes adversarial network technology and combines data collection and processing to design four experiments to comprehensively evaluate the performance of the model in different scenarios. The experimental results show that as the amount of data gradually increases, the performance of the model also improves. When processing 100, 1000, and 10,000 data points, the model achieved accuracies of 0.955, 0.962, and 0.982, respectively. Furthermore, the experimental results also indicate that effective noise suppression measures can significantly improve the accuracy and stability of the situational awareness model. Additionally, it is noted that different model structures will affect training duration, accuracy, and stability. Although increasing network scale may lead to increased computational complexity and latency, its accuracy is correspondingly improved. The adversarial network-based situational awareness model proposed in this study can accurately identify and effectively counter interference and attacks in UAV swarm communication networks, thereby providing solid protection for the collaborative combat and information sharing of UAV swarms.

Analysis of the integrated pattern of hoverable flapping wing micro-air vehicle

Flying creatures, such as insects and hummingbirds, display superior flight capabilities that have inspired the development of Flapping-Wing Micro Air Vehicles (FWMAVs). Although these vehicles have achieved certain milestones, integrating subsystems under stringent size, weight, and power (SWaP) constraints poses significant energy and weight management challenges. These vehicles' common patterns and critical differences still need to be clearly understood, indicating that their integrated patterns still need to be defined.To determine the integrated pattern of these aircraft, this study began with analyzing existing data on hover-capable bionic aircrafts. It then formulated a set of indices through the permutation and combination of subsystem parameters. Key indices were identified by examining the universality and specificity of system indices through case studies of aircraft, which helped establish the integrated pattern of FWMAVs.The study revealed certain commonalities in these aircraft; for example, the actuation system, comprising the drive, transmission, and manipulation systems, accounts for 51.72 % of the take-off weight. Combining the transmission system and structure, the airframe system represents 27.62 % of the take-off weight. The battery system accounts for about 20.18 %, while the electronic system usually constitutes 12.78 % of the aircraft's take-off weight. Additionally, significant variability was observed among aircrafts in parameters such as CD_5 and CD_7, which represent the distribution of control functions, and CS_4, which tests the integration of the structure with the transmission system. This paper constructs an integrated pattern for such aircraft based on these findings.The integrated pattern derived from this work provides a practical range of parameter values for subsystems during the initial design phase of these aircraft. This is crucial for enhancing the iterative convergence speed in engineering, facilitating the parallel development and design of subsystems, and validating the practicality of numerical optimization results from optimization algorithms. Ultimately, this contributes to advancing future designs and developments of hover-capable bio-inspired flying aircraft.

Continuous mapping of deformation over a ship structure model based on pointwise measurements

The development of structural monitoring systems on-board vehicles aims to achieve a full-picture of the vehicle response under operating conditions. The use of different data sources is a key point for many SHM approaches which demand for extensive information and data fusion techniques to address the specific inverse problem in a robust way. Therefore, a procedure to transform pointwise measurements into a continuous representation of the monitored structure is presented in this paper. To achieve the desired monitoring goals, a numerical approach which combines experimental recorded data and modelled responses from a ship structural model is developed. Craig-Bampton truncation technique is applied on the FE vehicle model to reduce elastic dofs and obtain a computationally cost-effective model. The main advantage of Craig-Bampton modes is the capability to keep unchanged the information at the sensor nodes. A state observer is then built to evaluate the elastic deflection field and the loads over the structure in the points where no measurement is available. A natural second-order observer is exploited as it is more suited for the present application than the Kalman filter. To enhance the observer performances, an optimization process is carried out based on a learning phase. Following a previous paper about theoretical aspects of the virtual sensing approach on 1D structures. the developed techniques are here applied to the monitoring of the structural deflections and the ambient excitation relative to an elastically scaled model of a fast catamaran, tested in the towing-tank. Accelerations and strain-gage data are used to reconstruct the elastic deformations of the physical model metallic backbone scaling the reference ship behavior. Hydrodynamic load data relative to the demihull portions and the wetdeck are obtained as well.