Browse Topic: Data exchange

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A Cooperative AFS/DYC Control for FWDIEV Based on Dissipative Energy Method2026-01-0619To be published on 04/07/2026
To enhance the lateral stability of four-wheel-drive intelligent electric vehicles (FWDIEV) under extreme operating conditions, this paper proposes a cooperative control strategy integrating active front steering (AFS) and direct yaw moment control (DYC) based on dissipative energy method. A nonlinear three-degree-of-freedom vehicle model is established to analyze the evolution of the vehicle state phase trajectory. A quantitative lateral stability index is constructed using dissipative energy to accurately evaluate the vehicle's lateral dynamics. Utilizing dissipative energy and its gradient information, a time-varying stability boundary is defined under dynamic constraints, and adaptive weighting coordination between the AFS and DYC systems is designed to achieve coordinated control of front steering angle and additional yaw moment. A feedforward–model predictive control (FF-MPC) framework is developed, in which a feedforward module generates compensation based on driver intent to
Zhao, Kun, Zhao, Zhiguo, Wang, Yutao, Xia, Xue, Chen, Xi, Hu, Yingjia
Curvature-Based End-to-End Autonomous Vehicle Path Planning at Intersections2026-01-0045To be published on 04/07/2026
Autonomous vehicle navigation requires accurate prediction of driving path curvature to ensure smooth and safe trajectory planning. This paper presents an end-to-end approach to curvature prediction using deep neural networks trained on real-world driving data. We develop a comprehensive neural network architecture that directly maps high-dimensional sensor inputs to curvature predictions, eliminating the need for intermediate feature engineering steps. The model processes multi-modal inputs including vision features, vehicle state parameters, and environmental context through a deep learning pipeline. Our end-to-end approach demonstrates the feasibility of learning complex driving behaviors directly from raw sensor data, providing a more robust and generalization solution compared to traditional rule-based methods. The neural network architecture incorporates dropout regularization and adaptive learning rate scheduling to ensure stable training and optimal performance. Results show
Hajnorouzali, Yasaman, Wang, Hanchen, Li, Taozhe, Burch, Collin, Lee, Victoria, Tan, Lin, Arjmandzadeh, Ziba, Xu, Bin
Oscillatory Behavior of Understeering Vehicles2026-01-0623To be published on 04/07/2026
Oscillations in understeering vehicles are occasionally described in the literature, primarily in terms of the poles of the yaw rate response, but perhaps not completely appreciated in their complexity. This work shows that as speeds of the understeering vehicle increase, the increasingly underdamped poles of the yaw rate transfer function combine with the effects of a low frequency zero and a reduced steady-state response to result in oscillations greater than would be expected from eigenvalues alone. A speed range for acceptable yaw rate response is suggested, and it is shown that a typical understeering passenger car operates within this range. As the understeering vehicle’s speed increases beyond this range, the high speed limit of the oscillation frequency is found.
Williams, Daniel
Impact of C-rates on Electrical Behavior of Li-ion Batteries under Coupled Temperature-load Conditions2026-01-0383To be published on 04/07/2026
The utilization of lithium-ion batteries in electric vehicles becomes increasingly common. Battery performance degradation is influenced by both temperature and boundary constraints. Monitoring the usable cell capacity (UCC) under real-world operating conditions is essential for ensuring accurate state-of-health estimation. Capacity tests in laboratory settings are typically conducted at low C-rates to approximate equilibrium conditions, whereas in real vehicle applications, charging currents are often much higher. This discrepancy in charge/discharge rates frequently results in deviations between laboratory characterization and on-board BMS capacity estimation. To investigate the impact of C-rates under coupled temperature-load conditions, we conducted long-term cycling tests on LFP/graphite pouch cells at 25 °C and 45 °C under different constrained conditions. The UCC was evaluated at different test rates (1/20C, 1/3C, and 1C) as an indicator of aging. The results show that
ZHANG, Shan, Niu, Zhice, Xia, Yong
High Strain-Rate Behaviors of Fiber Reinforced Composites in Principal and Off-Axis Directions2026-01-0175To be published on 04/07/2026
Materials can exhibit significantly different mechanical behaviors compared to quasi-static conditions at high strain rates (> 100 s-1). High strain rate tests using setups such as SHPB (Split-Hopkinson Pressure Bar) can provide, in a practicable manner, the stress-strain relations for a material at high strain rates. Such properties are vitally needed for activities such as simulation-driven impact safety design of composite structures deployed in the form of automotive body parts and assembly, and other sub-systems. Although the behaviors of isotropic and ductile materials such as various metallic alloys appear to have been extensively studied and reported in literature, dependence of mechanical properties of fiber-reinforced composites especially in different off-axis directions are extremely difficult to come across. To fill up this void, a detailed experimental study has been carried out on high strain rate mechanical characterization of orthotropic glass, carbon and a natural
Bawa, Prashant, Deb, Anindya, Zhu, Feng
Research on the control of magnetic weakening scheme for the voltage utilization rate of hybrid transmission2026-01-0447To be published on 04/07/2026
This paper proposes a weak magnetic control method for PMSM current regulators based on the ratio of pressure to frequency and voltage utilization rate when the motor speed exceeds the weak magnetic speed. That is, the direct-axis offset current id is generated through the action of weak magnetic feedforward and weak magnetic I regulator, and the control of weak magnetic speed can directly adjust the demagnetization effect of id to achieve weak magnetic control of PMSM. The weak magnetic control method of PMSM current regulators with the outer loop of voltage utilization rate is adopted. It is proposed to use the phase-locked loop control method to decode the motor position signal in a closed loop and calculate the motor speed. The fluctuation of the position signal is reduced and the signal is more stable. This paper realizes constant power speed regulation based on high voltage utilization rate and weak magnetic control method at high speed operation above the base speed, which
Jing, Junchao, Yan, Xiaoqian, Liu, Yiqiang, Sun, Fengjiao, Dai, Zhengxing
Optimization Strategies of Gliding Arc Plasma-Based Ammonia Cracker towards On-Board Applications2026-01-0292To be published on 04/07/2026
Ammonia has emerged as a viable hydrogen energy carrier owing to its superior hydrogen density, mature industrial utilization. However, ammonia faces critical challenges including inadequate ignition characteristics and sluggish combustion kinetics, necessitating supplementary high-reactivity fuels for optimizing combustion. Onboard ammonia cracking technology resolves this problem through on-demand hydrogen in-time production. Among existing decomposition methods, gliding arc plasma (GAP) demonstrates exceptional promise for on-board crackers given its decent hydrogen conversion rate and transient response capability. Prevailing research predominantly employs experimental methodologies wherein macroscopic parameters inadequately proxy microscopic electric field characteristics, thereby impeding mechanistic insight. This study establishes a quasi-1D numerical model to interrogate how electric field parameters modulate ammonia-to-hydrogen conversion yield and system energy efficiency in
Dong, Guangyu, LI, Xian, ZHOU, Yanxiong, XU, Jie, Li, Liguang
Attention and Intrinsic Curiosity-Enhanced Deep Reinforcement Learning for Path Planning in Dynamic Environments2026-01-0044To be published on 04/07/2026
Efficient and reliable path planning remains a core challenge for autonomous vehicles operating in dynamic and crowded environments. Although Deep Reinforcement Learning (DRL) has shown considerable potential in autonomous decision-making, it still faces challenges such as insufficient feature extraction, sparse rewards, and low obstacle avoidance efficiency in complex scenarios. To address these issues, this paper proposes an end-to-end path planning framework, PPO-ICM-Attn. Built upon the Proximal Policy Optimization (PPO) algorithm, the framework incorporates a dual-channel attention convolutional neural network module (Attention-CNN) to enhance spatial and semantic understanding of dynamic obstacles, and introduces an Intrinsic Curiosity Module (ICM) to promote active exploration in sparse reward settings. Furthermore, a reactive avoidance reward function based on velocity obstacle theory is designed and embedded to achieve real-time proactive collision avoidance in highly dynamic
Shen, Shiquan, Liu, Jiahao, Chen, Zheng, Li, Zongdian, Zhao, Yuting, Wu, Minggong, Zhao, Jie, Qin, Zongquan, Wang, Yanfeng
Autonomous Racing Control Using Reinforcement Learning with Racing Line Guidance2026-01-0031To be published on 04/07/2026
In recent years, with the emergence of autonomous racing competitions such as Roborace, autonomous racing cars have become a prominent research focus and have undergone rapid development. This paper establishes a reinforcement learning-based decision-making and control framework for autonomous racing cars, achieving cooperative optimization between high-speed racing and safety control under extreme operating conditions. By integrating a Control Barrier Function constrained reward function for dynamic stability and a racing line-guided path optimization, the proposed framework achieves a synergistic balance between minimum lap time and operational safety. Dynamic stability domain constraints based on a two-degree-of-freedom single-mass rigid-body model and racing line optimization based on track geometric modeling are established. The phase plane stability boundary is constructed using the yaw rate method and double-line method, upon which Control Barrier Function constraints are
peng, tao, Zhang, Weiqi, Li, Zengwen, sudong, jiang
RRT*_Heuristic_Adaptiv_maxR: A practical path planning method based on novel adaptive framework for autonomous mobile agent2026-01-0038To be published on 04/07/2026
Aim at addressing the problem of random sampling and low efficiency of rapidly-exploring random tree (RRT) path planning algorithm, a practical path planning method is proposed for autonomous mobile agents, named RRT*_Heuristic_Adaptiv_maxR. This method is based on a new adaptive framework, balancing the search efficiency and convergence accuracy of path planning by dynamically adjusting the maximum radius parameters in the search process. Combining the heuristic search strategy, guiding the sampling direction, accelerating convergence to the target area, the obstacle detection mechanism is used to optimize the path in real time to avoid collisions. Experimental results show that the proposed method, RRT*_Heuristic_Adaptiv_maxR, has higher planning success rate and path quality in complex environments compared with various RRT algorithms, and it is verified the effectiveness of the adaptive framework and the maximum radius dynamic adjustment strategy in mobile agent path planning.
Dong, Xiaomei, Zeng, Dequan, Petitti, Antonio, You, Jingyi, xiong, min, GAO, Letian, Jiang, Xiaomeng, Yu, Yinquan, CARBONE, GIUSEPPE, Hu, Yiming, Nawaz, Aamir, Linh, Nguyen Vu
Roundabout Dilemma Zone Data Mining and Forecasting with Trajectory Prediction and Graph Neural Networks2026-01-0029To be published on 04/07/2026
Traffic roundabouts, as complex and safety-critical road scenarios, present significant challenges for autonomous vehicles. In particular, predicting and managing dilemma zone (DZ) encounters at roundabout intersections remains a pivotal concern. This paper introduces an AI-driven system that leverages advanced trajectory forecasting to anticipate DZ events, specifically within traffic roundabouts. At the core of our framework is a modular, graph-structured recurrent architecture powered by graph neural networks (GNNs). By modeling agent interactions as a dynamic graph, our approach integrates heterogeneous data sources, including semantic maps, while capturing agent dynamics with high fidelity. This GNN-based forecasting model enables accurate prediction of DZ events and supports safer, data-driven traffic management decisions for both autonomous and human-driven vehicles. We validate our system on a real-world dataset of roundabout intersections, where it achieves high precision with
Lu, Duo, Farhadi, Mohammad, Satish, Manthan, Yang, Yezhou, Chakravarthi, Bharatesh
Bias and uncertainty in the time, position, and speed data of consumer-grade GPS devices2026-01-0544To be published on 04/07/2026
The goal of this study is to quantify the accuracy and uncertainty of position and speed measurements acquired by a wide range of consumer-grade GPS-enabled devices while road cycling. We acquired position and speed data simultaneously from 13 consumer devices (e.g., phones, watches, bicycle computers) at their maximum sampling rate (typically 1 Hz) during 10 hours (thirty 20 minute sessions) and 150 km of road cycling in a suburban environment. The position data from these devices were compared to real-time kinematic (RTK) data acquired using a differential GPS system and the speed data from these devices were compared to speed data acquired with high-resolution wheel rotation sensors (23,040 pulses per revolution) synchronized with the RTK data. Based on these comparisons, we generated probability distributions for the errors in the position and speed measured by each of the consumer devices. This study provides foundational data needed to quantify the accuracy and uncertainty across
Booth, Gabrielle R., Mitchell, Alan L., Siegmund, Gunter P.
Determining Video Frame Capture Rate through Reverse Engineering2026-01-0543To be published on 04/07/2026
The timing of video recordings, along with the spatial positioning of objects, is a fundamental parameter for calculating the speed time history. If the task involves determining an object’s average speed over several to a dozen frames, the average inter-frame interval can be used as the basic time unit. However, if the objective is to compute speed from individual frames, the reliability of the timing becomes crucial. Without access to DVR hardware documentation, proprietary algorithms, or software – and considering the frequent hardware modifications and software updates - the most effective way to solve the problem is through a reverse-engineering approach. This study discusses several aspects of timing analysis, including: (1) making a test recording of a calibrated LED lightboard; (2) analyzing the relationship between the lightboard time and the presentation time stamp (pts) extracted from the file metadata; (3) investigating frequency interference occurring when recordings are
Wach, Wojciech
Machine Learning Modeling for Compressive Property Prediction of Foams2026-01-0512To be published on 04/07/2026
Foam material models for automotive structural analysis typically require tensile and compressive data at multiple strain rates. The testing is costly and may require a long time to complete. For many applications, foams of similar chemistry are used and the foam structural responses, such as stiffness and compression force deflection, are controlled by the foam density. In such cases, Machine Learning (ML) lends itself as an ideal tool to detect the trends in material response based on density and strain rate. In this paper, five microcellular polyurethane (PU) foams of different densities were tested at four strain rates ranging from 0.01/s to 100/s. A ML model capable of predicting compressive stress-strain response for a range of densities was developed. The model demonstrated good prediction capability for intermediate strain rates at all foam densities and in extrapolating stress-strain curves at higher densities at all strain rates. The strain rate trends for a density outside
M, Gokula Krishnan, Kavimani, Harish, Muppana, Sai Siddhartha, Savic, Vesna, Chavare, Sudeep, V S, Rajamanickam
Ambient and Initial Temperature Effects on Battery Electric Vehicle (BEV) Range and Energy Consumption Rate Modeled in FASTSim2026-01-0277To be published on 04/07/2026
Ambient and initial temperatures have a significant impact on the energy consumption rate of battery electric vehicles (BEVs) due to auxiliary loads and the dependence of battery efficiency on temperature. Quantifying these impacts can help BEV owners, communities, and researchers understand and prepare for the impact of temperature on BEV vehicles, especially as adoption increases. We used NREL's FASTSim 3 to investigate the impacts of a two-dimensional design-of-experiment that swept ambient and initial temperature in simulating a compact BEV hatchback over UDDS (city) and HWFET (highway) US EPA drive cycles. Compared to a 22 ° C ("cozy") initial / ambient temperature baseline in UDDS, a cold initial / cold ambient temperature (-7 ° C) resulted in a 221% increase in the energy consumption rate, a cozy initial / cold ambient temperature resulted in a 94% increase, a hot initial (45 ° C) / hot ambient (40 ° C) temperature resulted in a 40% increase, and a cozy initial / hot ambient
Baker, Chad, Steuteville, Robin, Holden, Jake, Gonder, Jeffrey, Carow, Kyle
Techno-Economic Evaluation of Electified Vehicle Options in Drayage Fleets2026-01-0454To be published on 04/07/2026
The transition of drayage fleets from diesel to battery electric vehicles (BEVs) poses both opportunities and uncertainties, especially regarding long-term economic viability. While total cost of ownership (TCO) is a useful benchmark, fleet operators and investors are equally concerned with investment performance metrics such as payback period and Internal Rate of Return (IRR), which better reflect financial risks and investment return timelines. This study proposes a comprehensive framework to evaluate the economic feasibility of transitioning from diesel to BEVs, jointly analyzing TCO parity conditions, payback periods, and IRRs under different technology, cost, and operational scenarios. Building on a previously developed cost modeling tool, the analysis incorporates evolving battery prices, energy costs, vehicle performance characteristics and other assumptions from 2025 to 2050. Real-world duty cycle data from a Class 8 drayage fleet at the Port of Savannah is used to capture
Sun, Ruixiao, Sujan, Vivek, Goulet, Nathan, Wang, Qixing
Numerical Analysis of Operating Parameters Coupled Effects on Flow Instability Mechanisms at Supercritical Pressure2026-01-0134To be published on 04/07/2026
Supercritical fluids (SCFs) are widely utilized in advanced energy systems due to their exceptional heat transfer characteristics. However, flow instability, particularly near pseudo-critical conditions, poses a significant challenge to their effective applications. Despite extensive research, the coupled effects of thermal and fluid dynamic mechanisms on flow instability remain insufficiently understood, particularly in supercritical water (SCW) systems. This study identifies the onset of flow instability (OFI) in the negative slope region of pressure drop curve during steady-state conditions, analyzing the relationship between pressure drop and mass flow rate. Transient analyses were then conducted to investigate the influence of operating parameters on oscillatory phenomena such as pressure drop oscillations (PDO), density wave oscillations (DWO), and thermal oscillations (ThO). The results show that higher mass flow rates and heat fluxes, reduce pressure oscillations by up to 20
Rehman, Attiq, Ahmad, Hassaan, Du, Xiaocheng, kanwal, Lubna
Thermal Management Simulation of Liquid-Cooled Energy Storage Batteries Using a Reduced-Order Model2026-01-0122To be published on 04/07/2026
A linear time-invariant (LTI) reduced-order model (ROM) based on 3D CFD offers high accuracy for simulating energy storage battery thermal behavior under variations in ambient temperature, initial temperature, coolant inlet temperature, cell heat generation, and Joule heating. However, it cannot capture coolant flow rate fluctuations, which are essential for liquid cooling start–stop conditions in energy storage containers. To address this, we use an enhanced LTI+HTC ROM, which incorporates flow-rate-dependent heat flux at the fluid–solid interface into the LTI ROM. This is achieved by establishing a correlation between the coolant flow rate and the interface heat transfer coefficient (HTC). We further improve model fidelity by applying interface heat flux distribution features extracted from CFD. Comparisons with 3D CFD results demonstrate that the LTI+HTC ROM is highly accurate and significantly reduces computational cost, making it a practical tool for thermal management studies
guo, Jia, CHEN, Guijie, ma, Shihu, Hu, Xiao, Jing, Li, SONG, Shujun, Huang, Long
Physical Adversarial Infrastructure Attacks on Vision-Language Models for Autonomous Driving2026-01-0170To be published on 04/07/2026
Vision-language models (VLMs) offer a promising end-to-end approach for autonomous driving, but their robustness to physical adversarial attacks remains an unaddressed gap for safety-critical deployment. This paper introduces a systematic framework for evaluating these attacks using the Dolphins VLM and CARLA simulator. We employ Natural Evolution Strategies (NES), a black-box optimization method, to generate adversarial patches without internal model access. Our approach uses semantic similarity loss and Expectation over Transformation (EoT) to ensure physical realizability under varying viewing conditions. Patches are strategically placed on realistic advertising infrastructure (bus shelter panels and highway billboards), reflecting a plausible threat model. We establish two complementary scenarios: crosswalk pedestrian detection suppression and highway steering manipulation. Our evaluation reveals critical vulnerabilities. Adversarial patches achieved a 76.0% overall attack success
Fernandez, David, MohajerAnsari, Pedram, Salarpour, Amir, Pese, Mert D.
Automotive Ethernet Proxy-Based Security Architecture In Vehicle Computers2026-28-0121To be published on 02/12/2026
Modern vehicles require sophisticated, secure communication systems to handle the growing complexity of automotive technology. As in-vehicle networks become more integrated with external wireless services, they face increasing cybersecurity vulnerabilities. This paper introduces a specialized Proxy based security architecture designed specifically for IP-based communication within vehicles. The framework utilizes proxy servers as security gatekeepers that mediate data exchanges between Electronic Control Units (ECUs) and outside networks. At its foundation, this architecture implements comprehensive traffic management capabilities including filtering, validation, and encryption to ensure only legitimate data traverses the vehicle's internal systems. By embedding proxies within the automotive middleware layer, the framework enables advanced protective measures such as intrusion detection systems, granular access controls, and protected over-the-air (OTA) update channels. This strategy
M, Arvind, Praneetha, Appana Durga, Remalli, Ravi Teja
Effect of Sebastiana rostrata Fiber Loading on the Tribological Behaviour of Polycaprolactone Biocomposite.2026-28-0021To be published on 02/12/2026
This study investigates the tribological performance of Sesbania rostrata fibers (SRFs) reinforced polycaprolactone (PCL) composites, focusing on the effects of fiber loading under varying normal loads. Composite samples with fiber contents of 10%, 20%, and 30% were tested at sliding velocities of 0.5 m/s and a fixed sliding distance of 500 m. Results show that the inclusion of SRFs significantly reduces the coefficient of friction (COF) and specific wear rate (SWR) compared to neat PCL, particularly at fiber loadings up to 20%. Beyond this threshold, fiber agglomeration leads to increased wear. The results highlight the potential of SRF/PCL composites for use in wear-critical automotive and orthopedic applications due to improved load-bearing capability and surface resistance.
Raja, K., Senthil Kumar, M.S.
Implementation of Automotive Cybersecurity Assurance Level2026-26-06241/16/2026
This paper explores the implementation of ISO 21434 Automotive Cybersecurity Assurance Levels (CAL), focusing on enhancing component level cybersecurity for a vehicle. CAL values, which range from 1 to 4, provide a metric for ensuring that assets are protected against relevant threats at various phases of the product life cycle. By identifying parameters in the attack feasibility rating and their severity early in the product life cycle, specifically during the concept phase of ISO 21434, organizations can determine the CAL values. The CAL value serves as a benchmark to determine the level of severity required during the design, development and verification phases of the product life cycle. This paper outlines a method to establish CAL values as per ISO 21434 guidelines. The proposed methodology includes a detailed analysis of threat modeling, which is crucial for identifying and mitigating potential cybersecurity risks. By conducting threat modeling, organizations can systematically
Ghosh, Subham, Khader Batcha, Jashic
Johnson-Cook Model Calibration for Brittle Materials under Impact Loads2026-26-03671/16/2026
In the assessment of parts subjected to impact loading, the current process relies on static analysis, which overlooks the significant influence of high strain rate on material hardening and damage. The omission of these effects hinders accurate impact simulations, limiting the analysis to comparative studies of two components and potentially misidentifying critical hot spot locations. To address these limitations, this study emphasizes the importance of incorporating the effects of high strain rate in impact simulations. By utilizing the Johnson-Cook material calibration model, which includes both material hardening and damage models, a more comprehensive understanding of material behavior under dynamic loading conditions can be achieved. The Johnson-Cook material hardening model accounts for the strain rate sensitivity of the material, providing an accurate representation of its behavior under high strain rate conditions. This allows for improved prediction of material response
Pratap, Rajat, Apte, Sr., Amol, Babar, Ranjit, Dudhane, Karan, Poosarla, Shirdi Partha Sai, Tikhe, Omkar
High-Performance Computing for Software-Defined EV Powertrains: Design and Real-Time Validation with NXP S32G3 Domain Controller2026-26-06841/16/2026
Software-Defined Vehicles (SDVs) are changing the automotive landscape by separating hardware from software and enabling features like over-the-air updates, advanced control strategies, and real-time decision-making. To support this transformation, EV powertrain systems require high-performance computing (HPC) platforms capable of real-time control, data processing, and cross-domain communication. This paper introduces a fully SDV-compatible EV powertrain architecture designed with NXP S32G3 domain controller. This processor supports multiple core having lockstep. It is designed for zonal control and automotive functional safety. The proposed designed uses the automotive Ethernet as an alternate option for CAN based communication to fulfill the bandwidth and timing requirement of today’s SDV applications. Hence it allows gigabit data transfer, Time Sensitive Networking (TSN) and also provides low latency across SDV control domain. Through secure real time interface with the vehicle’s
Pawar, Ganesh, Inamdar, Sumer Deepak, Kumar, Mayank, Deosarkar, Pankaj, Tayade, Nikhil, Kanse, Dattatray, Chopade, Vipul
A Performance-Driven Numerical Approach for Optimizing the Plenum Opening Area of Cowl Box2026-26-04611/16/2026
There is a scarcity of research in literature regarding the determination of Plenum Opening Area of cowl box. The area of the plenum opening in the cowl box significantly affects the airflow rate in fresh airflow modes, such as face and defrost modes, as well as issues related to water ingress. Primarily, the size of the plenum opening is determined by the necessary HVAC airflow rate. This study aims to investigate how the plenum opening area impacts both airflow discharge and the water ingress issue in the HVAC module. A novel approach is introduced in this research to determine the optimal plenum opening area of the cowl box, taking into account both airflow rate and water ingress concerns. The ANSYS FLUENT software is utilized to analyze airflow discharge in both face and defrost modes, while the SPH (Smooth Particle Hydrodynamics) based Preonlab tool is employed for water ingress analysis. Airflow discharge is evaluated for various plenum opening sizes in both modes, and the area
Baskar, Subramaniyan, Mahesh, A, Gopinathan, Nagarajan
Influence of Tipping Angles and Body Shapes on Payload Discharge Efficiency in Dump Trucks2026-26-04931/16/2026
The payload retention and material outflow pattern during the unloading process of dump trucks are critical factors influencing the efficiency and effectiveness of operations in construction and mining industries. This paper investigates the impact of tipping angles and the shape of the dump truck body on payload retention and outflow characteristics. Using FEA methodology, we explore the material outflow pattern for different body geometries such as box body, scoop body etc. for comparative analysis in order to optimize the shape for better & effective unloading. The results demonstrate a comparative estimation for an optimal body shape configuration to effectively unload payload and correlation of payload retention at various tipping angles. The current study also describes the effect of high cohesive forces between the payload particles on the discharge efficiency, and the pattern of mass flow rate is mapped against the tipping angle for various types of material properties for
Phukan, Prerna, Sahu, Hemant, Dave, Rajeev
Study of Drive Trace Indices and Their Correlation with CO 2 in Chassis Dynamometer2026-26-05171/16/2026
With introduction of Corporate Average Fuel Efficiency norms (hereafter referred as CAFÉ norms) in India, the manufacturers of all M1 Category vehicles (not exceeding 3,500kg GVW) must ensure that they comply with Annual Corporate average CO2 target as defined in regulation. Moreover, this target will become stricter at various stages in the coming years. Hence CO2 emissions are becoming one of the major focus parameters during vehicle development. There are several factors that can impact CO2 emissions during measurement in laboratory-based test cycles such as MIDC or WLTC. One such major factor is driving variations. Although speed and time tolerances are provided during the test (as part of AIS 137/AIS 175) to limit the variation, even within these tolerances, drive-related effects make significant contribution to test results variability. Monitoring and control of such variations is important to understand the true fuel economy potential of the vehicle. Drive Trace indices are
ER, Shivram, Rawat, Vijaypal, Khandelwal, Vineet, Kumar, Arun, Malhotra, Jitendra
Leveraging Telematics Big Data Analytics for Real-Time Monitoring of Catalytic Converter Failures and Root Cause Identification for Emission Compliance2026-26-05911/16/2026
The automotive industry is continuously evolving at high pace to meet rising customer expectations, reliability, reduced maintenance, and most relevant, compliance with stringent emission norms. Traditionally, the analysis of vehicle emissions relies heavily on periodic inspections and manual checks. These conventional methods are often time-consuming, prone to human error, and lack the ability to provide real-time insights. Also, identifying failures due to non-manufacturing issues require meticulous physical inspections and historical data reviews, which are not always accurate or timely. Telematics or Connected cars technology being one of the major technological innovations in recent times revolutionizes these processes by enabling real-time data exchange between vehicles and external systems. The current study presents an innovative approach to utilizing telematics data for real-time monitoring of vehicle emissions and pinpointing Catalytic converter failures by analyzing vehicle
Dev, Triyambak, Prasad, Kakaraparti Agam, Kalkur, Varun, Modak, Saikat, AGARWAL, Shashank, Chandra, Animesh, Paul, Varsha, Garg, Amit, Sundararaman, Venkataraman, Bose, Sushant
A Unified Concept Model for Advancing Multilingual Summarization and Semantic Reasoning in the Automotive Space2026-26-06761/16/2026
The automotive industry produces a vast amount of multilingual textual data ranging from technical manuals to diagnostic reports that demand efficient summarization and reliable semantic reasoning. At present, the traditional large language models (LLMs) operating at the token level struggle not only with cross-lingual understanding and domain-specific reasoning but also are prone to hallucinations, leading to inaccurate insights and responses [2, 5]. This paper introduces a Unified Concept Model (UCM) architecture for the automotive domain that processes language at the concept level using multilingual, modality-agnostic embeddings, enabling coherent cross-lingual summarization and reasoning. The UCM encodes entire sentences as semantic vectors by leveraging the SONAR embedding space, a multilingual, modality-agnostic sentence representation that supports over 200 languages. This approach to encoding facilitates a deeper understanding across language boundaries and complex technical
Singh, Samagra, Ravi, Utkarsh, Vikram, Prateek, Shenoy, Lakshmi, Awasthi PhD, Anshuman
High-Fidelity Modeling of Vehicle Dynamics for Control-Oriented Stability Enhancement2026-26-00931/16/2026
This study presents an integrated vehicle dynamics framework combining a 12-degree-of-freedom full vehicle model with advanced control strategies to enhance both ride comfort and handling stability. Unlike simplified models, it incorporates linear and nonlinear tire characteristics to simulate real-world dynamic behavior with higher accuracy. An active roll control system using rear suspension actuators is developed to mitigate excessive body roll and yaw instability during cornering and maneuvers. A co-simulation environment is established by coupling MATLAB/Simulink-based control algorithms with high-fidelity multibody dynamics modeled in ADAMS Car, enabling precise, real-time interaction between control logic and vehicle response. The model is calibrated and validated against data from an instrumented test vehicle, ensuring practical relevance. Simulation results show significant reductions in roll angle, yaw rate deviation, and lateral acceleration, highlighting the effectiveness
Duraikannu, Dinesh, Dumpala, Gangi Reddi
Scalable and Modular Data-Driven Hybrid Chassis Dynamometer Framework for EV Powertrain Evaluation2026-26-03631/16/2026
In its conventional form, dynamometers typically provide a fixed architecture for measuring torque, speed, and power, with their scope primarily centered on these parameters and only limited emphasis on capturing aggregated real-time performance factors such as battery load and energy flow across the diverse range of emerging electric vehicle (EV) powertrain architectures. The objective of this work is to develop a valid, appropriate, scalable modular test framework that combines a real-time virtual twin of a compact physical dynamometer with world leading real-time mechanical and energy parameters/attributes useful for its virtual validation, as well as the evaluation of other unknown parameters that respectively span iterations of hybrid and electric vehicle configurations, ultimately allowing the assessment of multiple chassis without having to modify the physical testing facility's test bench. This integration enables a blended approach, using a live data source for now, providing
Kumar, Akhilesh, V, Yashvati
A Large-Scale Characterization of PyCrash Collision Model Behavior Using Real-World Collision Data2026-01-50041/15/2026
PyCrash is an open-source collision simulation software package that includes a formulation of the Carpenter–Welcher collision model. Upon its release, PyCrash was accompanied by a companion paper that described its functions and provided preliminary validation results against staged collisions. However, the collisions investigated in the original report were limited to a single type of alignment. The purpose of this study was to characterize PyCrash collision model behavior against EDR data collected from a heterogeneous cohort of real-world two-vehicle collisions. PyCrash simulations were informed by the published vehicle geometries, crush profiles, and available pre-impact EDR data; simulation outputs were compared to EDR data, which served as the surrogate for “ground truth” with respect to the collision mechanics. Simulation settings were tuned to the specifics of each crash, based on previous published work and engineering judgement. Using optimized inputs for each crash, PyCrash
Fischer, Patrick, Cormier, Joseph, Watson, Richard
Advanced High-Repetition-Rate Lasers Drive Next-Gen ImagingTBMG-544131/1/2026
Since the advent of laser-based imaging techniques in the early 2000s, image acquisition has faced a fundamental challenge: the imaging speed and signal averaging was directly tied to the firing rate of the laser. Because a minimum of one laser pulse generates a single data point, traditional flashlamp-based lasers operating at relatively low repetition rates were constrained in their ability to capture fine spatial or temporal detail quickly. For applications requiring real-time analysis or high-resolution mapping, these limitations often reduced the practicality of otherwise powerful imaging technologies.
STGT-Gen: Spatio-Temporal Graph Transformer for Multi-Vehicle Traffic Scenario Generation2025-01-731612/31/2025
In the testing and validation of autonomous driving systems, scenario-based simulation is crucial to address the high costs and insufficient scene coverage of real-road testing. However, existing simulators rely on handcrafted rules to generate traffic scenarios, failing to capture the complexity of multi-agent interactions and physical rationality in real traffic. This paper proposes STGT-Gen, a data-driven Spatio-Temporal Graph Transformer framework, to generate realistic and diverse multi-vehicle traffic scenarios by integrating spatio-temporal interaction modeling, physical constraints, and high-definition (HD) map information.STGT-Gen adopts an encoder-decoder architecture: The encoder captures temporal dependencies of vehicle trajectories and spatial interactions via a Temporal Transformer and a Spatial Graph Transformer, respectively, while a hierarchical map encoding module fuses lane topologies and traffic rules. The decoder ensures physical feasibility during long-term
Qin, Xupeng, Lu, Chao, Wei, Yangyang, Fan, Sizhe, Song, Ze, Gong, Jianwei
Kinematics-Based Differential In-Situ Steering Control for Distributed-Drive Electric Vehicles2025-01-733312/31/2025
In-situ steering can significantly improve the vehicle's maneuverability in narrow spaces, especially suitable for extreme scenarios such as off-road driving and professional operations. For distributed drive electric vehicles, kinematics-based left and right wheel differential control and dynamics-based vehicle yaw control can achieve in-situ steering, however, the two methods have different effects on in-situ steering performance. This paper proposes a kinematics-based distributed drive electric vehicle differential in-situ steering control method, which first establishes the functional relationship between the drive pedal and the expected yaw rate, so that the driver can adjust the steering speed. The initial reference wheel speed is calculated from the expected yaw rate, and the reference wheel speed is adjusted by feedback from the actual and expected yaw rate errors to improve the tracking accuracy. On this basis, the sliding mode control algorithm is used to calculate the
Chen, Jingxu, Li, Yang, Zhang, Yi, Zhao, Hongwang, Qiao, Miaomiao, Wang, Beibei, Wu, Dongmei
Experimental Investigation of Stress Distribution Characteristics in Surrounding Rock during Unloading in Oblique Upper Crossing Tunnel2025-99-024212/23/2025
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Wu, Hao, Qin, Shuzhen, Li, Guofeng, Dong, Tianwen, Shi, Yongyue
Trajectory Reconstruction at Signalized Intersections in a Vehicle-to-Infrastructure Environment2025-99-021712/23/2025
Vehicle trajectories encapsulate critical spatial-temporal information essential for traffic state estimation, congestion analysis, and operational parameter optimization. In a Vehicle-to-Infrastructure (V2I) environment, connected automated vehicles (CAVs) not only continuously transmit their own real-time trajectory data but also utilize onboard sensors to perceive and estimate the motion states of surrounding regular vehicles (RVs) within a defined communication range. These multi-source data streams, when integrated with fixed infrastructure-based detectors such as speed cameras at intersections, create a robust foundation for reconstructing full-sample vehicle trajectories, thereby addressing data sparsity issues caused by incomplete CAV penetration. Building upon classical car-following (CF) theory, this study introduces a novel trajectory reconstruction framework that fuses CAV-generated trajectories and infrastructure-based speed detection data. The proposed method specifically
Bai, Wei, Fu, Chengxin, Yao, Zhihong
Research on Civil Aviation Transportation Scheduling Optimisation System Based on Artificial Intelligence2025-99-023312/23/2025
The rapid development of civil aviation industry makes it difficult for traditional flight scheduling methods to cope with the increasingly complex air transport demand. In this study, an AI-based civil aviation transportation scheduling optimisation system is designed, integrating a novel deep reinforcement learning framework with a validated multimodal fusion algorithm (MMFA) to address spatiotemporal dependencies in aviation data to construct the core architecture of the system. Measurement results show that the system effectively reduces the average flight delay time by 58.1%, improves the slot utilisation rate by 21.3%, increases the flight punctuality rate to 93.7%, and shortens the response time to emergencies by 62.5%. The high performance and significant economic benefits demonstrated by the system in the real environment provide a feasible solution for the intelligent upgrading of civil aviation transport.
Li, Mohan
Research on Dynamic Adjustment Mechanism of Railway Freight Pricing Based on NSGA-II Algorithm2025-99-024812/23/2025
With the implementation of the "road-shift-to-rail" policy and the intensification of competition in the freight transport market, establishing a scientific and effective dynamic pricing mechanism has become a crucial factor in enhancing the competitiveness of railway freight. To address this, this paper constructs a multi-objective dynamic pricing model that comprehensively considers the interests of railway transport enterprises, shippers, and societal externalities. A new multi-objective genetic algorithm (NSGA-II) is designed to solve the model, and an empirical analysis is conducted based on real-world data from "road-shift-to-rail" projects. The research results indicate that the proposed method aligns closely with the current pricing practices of railway transport enterprises. For goods with low time sensitivity, greater freight rate discounts should be offered to shippers, whereas for high time-sensitive goods, the time gap between rail and road transport should be minimized.
Zhang, Hengyuan, Feng, Zhichao, Wu, Xu
Research on the Visibility Attenuation Model of Pavement Markings for Older Drivers Based on Retroreflective Luminance Coefficient2025-99-022012/23/2025
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Cheng, Lizhi, Guan, Yanyan, Cheng, Xinyu, Hu, Jiangbi, Fu, Youlei, Yang, Biyu, Song, Shousong
Technical management: Focus Matrix Methodology Applied to the 2° GEN of Bosch Flex Fuel Pump2025-36-005212/18/2025
Reliability and performance are critical for product success in engineering. With this aim, the Focus Matrix is a strategic tool designed to enhance the development process by effectively managing technical requirements and prioritizing resources. This paper outlines the application of the Focus Matrix in product development to organize technical packages based on complexity and the technical expertise of the project team. The methodology will be illustrated through a case study on the second-generation Flex Fuel (EVO) fuel pump developed by Bosch. The Fuel pump is responsible for delivering fuel to the engine while maintaining optimal pressure and flow rate. Transitioning to a second generation of a fuel pump focuses on optimizing performance to keep the product relevant in the market, necessitating a thorough analysis of lessons learned and current technological trends. Throughout the development phase, the Focus Matrix provided a structured approach for identifying and mitigating
de Souza, Ana Laura Lima, de Oliveira Melo, Lazaro Benedito, Aguiar, Rayssa Moreno Silva, Azevedo Fernandes, Luiz Eduardo de, Boa, Nathan Barroso Fonte
Development of a Localized Heat Treatment Route for Stamped Automotive Parts2025-36-008912/18/2025
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Santana, Jessica, Curti, Gustavo, Lima, Tiago, Sarmento, Matheus, Callegari, Bruna, Folle, Luis
Design and Construction of a Bench Test System for Elastomers Suspension2025-36-004112/18/2025
This study presents the design, construction, and experimental validation of a test bench for characterizing elastomer-based torsion suspensions in light vehicle applications. The system replaces conventional spring-damper assemblies with viscoelastic elements that simultaneously absorb and dissipate road-induced vibrations. We developed a scaled prototype instrumented with an Arduino-based data acquisition system and analyzed results using Octave®. The experimental protocol comprised: (1) tribological tests to identify optimal friction pairs through coefficient of friction (μ) and wear rate measurements, and (2) dynamometric evaluations of torque transmission capacity, power output, and efficiency across gear ratios (2.03-6.34). Results indicate that a steel-steel friction pair under a normal force of 250-300 N achieves optimal performance, delivering an output power of 1706 W (84.8% efficiency) and a torque of 30.25 Nm. Comparative analysis shows this configuration reduces wear rates
Silva, Diego Bruno, Grandinetti, Francisco José, Castro, Thais Santos, Dias, Érica Ximenes, Souza Soares, de Álvaro Manoel, Martins, Marcelo Sampaio, Reis de Faria Neto, dos Antônio
Research on Floating Pricing Strategy of Railway Coal Transportation Considering the Competition of Road and Railway2025-99-035212/17/2025
The market-oriented reform of railway coal transport price is a key initiative to optimize the transport structure and enhance the railway’s market share in coal transport. Based on the competitive relationship between road and railway, this paper explores the impact of the floating pricing mechanism of railway coal transport on the allocation of capacity and enterprise benefits. Firstly, we construct a model to consider the selection behaviour of highway and railway freight transport modes to reveal shippers’ choice of coal transport modes, and analyse shippers’ preference for highway and railway based on transport cost, timeliness and price elasticity; secondly, we combine railway coal transport clearing rules with market-oriented floating pricing policy, establish a pricing decision model with the goal of optimizing transport volume and carrier revenue, and quantify the full railway tariff, transport time and volume, surplus and so on. Secondly, we establish a pricing decision model
Liu, Li, Yang, Lei, Cai, Zhenghong
Research and Application of Contribution Rate of Acoustic Transfer Function in Vehicles2025-99-034312/17/2025
How to quickly identify weak areas and design redundancies in vehicle acoustic package design is an industry challenge. To address this issue, this paper investigates the relationship between acoustic parts and acoustic transfer function of vehicle. The contribution rates of each acoustic part to acoustic transfer function are calculated, and the area with the highest contribution rate is the weak area of the acoustic package. The area with the lowest contribution rate based on vehicle positioning can be identified as design redundancy. Firstly, establish a three-level architecture of acoustic transfer function - system - acoustic parts, determine the relationship formula between adjacent levels, and then establish the contribution rate relationship formula. Through simulation method, the contribution rate of each acoustic part to acoustic transfer function is obtained. Through test method, the contribution rate of each system to acoustic transfer function is analyzed. And optimize
Liu, Xiaona, Pan, Dianlong, Zhao, Wei, Yang, Xiaotao, Feng, Yihao, Chen, Zuozhong, Zhao, Minghao, Wu, Haichuan
Study on the Performance of High-Pressure Oxygen Cylinder Oxygen Supplemental System in Civil Aircraft Lavatories Based on Airworthiness Oxygen Requirements2025-99-030712/17/2025
This paper focuses on the performance of the high-pressure oxygen cylinder oxygen supplemental system in the lavatory of civil aircraft. Due to the potential safety hazards of chemical oxygen generators in the lavatory, high-pressure gaseous oxygen cylinders are used instead. Through theoretical and study, the influence of the orifice on the oxygen flow rate is thoroughly investigated. Based on relevant principles, the calculation method of the gas flow characteristics in the orifice is determined. Considering the high initial pressure of the oxygen cylinder, the supersonic flow condition within approximately 20 minutes is mainly considered. The Simulink is used to simulate the system flow rate under different temperatures during cabin depressurization. Experimental verification shows that the oxygen flow rate under different temperatures meets the minimum oxygen demand, and the simulation results are highly consistent with the experimental results, indicating that the simulation
Wan, Shuting, Lei, Mingjun, Yu, Xiaoying
Analyzing the Operation of Road Cold Chain Transportation Using Big Data in the Context of Cost Reduction, Quality Improvement, and Efficiency Enhancement2025-99-030312/17/2025
In recent years, the market size of cold chain transportation in China has been expanding, but the industry has problems such as low cold chain circulation rate, low efficiency, high damage rate, and high cost. Under the background of reducing costs and improving quality and efficiency in transportation and logistics, an index set for operational analysis covering average freight rates, daily average number of over-temperature alarm incidents, daily average driving distance, and daily average driving time was established from the perspectives of economic efficiency, quality, and efficiency. Based on data from a third-party platform, including vehicle trajectories, temperatures, speeds, and freight rates, the running situation of road cold chain transportation industry was analyzed. The analysis results show that in 2023, the average freight rate of China’s highway cold chain will rebound, the fluctuation range will significantly narrow, the standardization level of temperature control
Li, Sicong, Ye, Jing, Cao, Mengfei
Study on the Wear Resistance of Aggregates Based on Surface Abrasion Characteristics2025-99-031112/17/2025
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Liu, Yong, Tian, Tao, Hou, Jianwei, Chen, Geng, Wang, Anping
Impact of Maximum Platoon Size of Connected and Automated Vehicles on Safety of On-Ramp Mixed Traffic2025-99-045412/10/2025
This study investigates how the maximum platoon size (MaxPS) of Connected and Automated Vehicles (CAVs) influences traffic safety within mixed traffic environment on freeway on-ramps. Built upon the SUMO simulation framework, a mixed traffic flow model involving CAV platoons is developed for on-ramp scenarios. This paper examines traffic conditions under varying on-ramp inflow volumes and evaluates upstream speed fluctuations in the merging area. Safety indicators such as Time Exposed Time-to-Collision (TET) and Time-Integrated time-to-Collision (TIT) are employed to assess overall traffic safety. Additionally, collision types are analyzed. Results indicate that under low on-ramp inflow conditions, a moderate MaxPS with low CAV penetration rates significantly enhances safety, whereas a larger MaxPS is preferable with high penetration rates. Under moderate on-ramp inflow, limiting the CAV MaxPS to 2 reduces conflicts. As on-ramp inflow increases further, a MaxPS of 1 or 2 leads to a
Pan, Gongyu, Huang, Yujie, Xie, Junping
Research on the Evaluation System for the Digital Transformation Level of Traffic Infrastructure in the National Integrated Multi-Dimensional Transportation Network2025-99-041712/10/2025
The traffic infrastructure of the National Integrated Multidimensional Transportation Network is a crucial foundational support for building a strong transportation country and a key element in the digital transformation strategy of transportation. This paper focuses on the National Integrated Multi-dimensional Transportation Network and, covering the five sectors of railways, highways, waterways, civil aviation, and postal express, proposes a digital evaluation system for transportation infrastructure. By using an indicator system for the digitalization rate, the study constructs a digitalization rate indicator system for transportation infrastructure through methods such as the Analytic Hierarchy Process (AHP) and Principal Component Analysis (PCA). Historical data from 2013 to 2022 are used for analysis and evaluation. Based on the evaluation results, effective measures and recommendations for the digital transformation of transportation infrastructure are proposed.
Wang, Na, Liu, Na
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