Browse Topic: Mathematical models

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Accurate simulation of Sealing process using a GPU-accelerated Lagrangian differencing dynamics method2026-01-0492To be published on 04/07/2026
A vehicle body consists of many parts, between which there are seams and gaps that water, dust, and noise can enter. To prevent corrosion and reduce noise, these gaps are sealed with a paste featuring complex non-Newtonian properties. Sealing also serves a cosmetic function for visible areas, which demands high quality for better customer satisfaction. Usually, seam length can reach several meters with a height of 0.5-5 mm and a width of 5-40 mm. In this situation, optimizing the robotic paths and sealant flow can speed up production and reduce costs. Accurate and fast CFD modeling helps with planning the sealing process, shortening vehicle development cycles and minimizing costs. Due to the complexity of vehicle body geometry, arbitrary robotic movements, sealing seam length, free surface, and the complex rheological material properties, traditional CFD simulations have difficulties in modelling this process. This paper presents a new framework for modelling the sealing processes
Panov, Dmitrii Olegovich, Zhu, Huaxiang, Basic, Josip, Zhang, Lingran, Kotian, Akhilesh, Menon, Muraleekrishnan, Borra, Ravi Kanth, Ando, Yuya
Research on Fault-Tolerant Control Strategy for Drive System Failure of Corner Module-by-Wire Chassis Vehicles2026-01-0620To be published on 04/07/2026
As an emerging research focus, corner module-by-wire chassis vehicles address the pain points of traditional chassis in flexibility, cost, and development efficiency, and have become one of the key infrastructures in the autonomous driving era. However, their large number of actuators significantly increases the risk of failures. This paper analyzes the characteristics of such vehicles and studies the fault-tolerant control for their drive system failures. Firstly, a full-vehicle dynamic model was established, with mathematical modeling conducted for the vehicle body, motor, tire, and corner module system models. Secondly, a hierarchical yaw stability control strategy was designed for the non-faulty actuator scenario: the decision-making and control layer adopted both Sliding Mode Control (SMC) and fuzzy PID control, selecting the method with better performance to output the additional yaw moment; the control allocation layer used a quadratic programming algorithm based on tire load
Zheng, Hongyu, Zhang, Tianhao, Zhang, Yuzhou
Digital Twin Aerodynamics Model Validation for HALO Wind Tunnel2026-01-0610To be published on 04/07/2026
A simulation-based aerodynamics model of the Honda Automotive Laboratories of Ohio (HALO) Wind Tunnel, a three-quarter open-jet (ground plane) configuration opened in 2022 for full-scale automotive testing, is under development to support data fusion for more accurate surrogate models in vehicle engineering programs. The objective is to demonstrate that a matched set of boundary values between the physical wind tunnel and the three-dimensional numerical model yield correct responses for several key flow field quantities, starting with the baseline empty tunnel case: (1) streamwise static pressure distribution, (2) evolution of the free shear layers downstream of the nozzle exit plane, and (3) ground-plane boundary layer development. Pressure-based measurement probes were deployed in these regions using a four-axis overhead traverse to acquire validation data in the large facility, including instrument verification between a 14-hole probe and Pitot-static rake. Detached eddy simulation
Patel, Sajan, Disotell, Kevin, Eagles, Naethan
A Latent Space Framework for Modeling Transient Engine Emissions Using Joint Embedding Predictive Architectures2026-01-0423To be published on 04/07/2026
Accurately modeling exhaust emissions during transient events, such as rapid acceleration and deceleration, remains a long-standing challenge in the automotive field and is a prerequisite for real-time control and optimization in modern powertrain systems. The nonlinear emission behavior is difficult to capture, and early mathematical models frequently relied on approximations that limited their accuracy. With the rise of data-driven methods, especially deep neural networks, including multilayer perceptrons and long short-term memory (LSTM) networks, modeling capabilities have improved significantly. However, to achieve meaningful accuracy, these models often require deep architectures, which increase computational load and inference time. This makes their application in real-time control systems challenging, as controllers must run at high sampling rates while maintaining accuracy, which is often a contradictory requirement. This paper addresses the trade-off with a new framework
Sundaram, Ganesh, Gehra, Tobias, Ulmen, Jonas, Heubaum, Mirjan, Görges, Daniel, Günthner, Michael
From Static Ground to Moving Ground Wind Tunnels: Feature Selection for Reliable Estimation of Drag Coefficient Discrepancies2026-01-0203To be published on 04/07/2026
Moving ground wind tunnels offer a more accurate test environment for ground vehicle drag coefficient measurement due to their highly realistic representation of the boundary layer phenomenon. However, historically most vehicles have been tested on static ground wind tunnels. As a result, the measured drag coefficient of these vehicles may not be sufficiently realistic for certification purposes. Therefore, it is valuable to build statistical models to estimate moving-ground wind tunnel drag coefficient by using information from a static-ground wind tunnel and other relevant vehicle characteristics such as presence of aerodynamic devices (spoilers, air dams, etc.). However, to build accurate statistical models, appropriate predictive features must be identified as a first step. In this paper, an aerodynamic feature selection study has been conducted to identify vehicle characteristics that contribute to drag coefficient estimation discrepancies between a static- and a moving-ground
Singh, Yuvraj, Jayakumar, Adithya, Rizzoni, Giorgio
The Characterization of Lumbar Acceleration in Rear-End Impacts Across Different Surrogate Occupant Types2026-01-0552To be published on 04/07/2026
Longitudinal lumbar acceleration is often overlooked as a key variable when biomechanically assessing lumbar response in rear-end collisions. Previous studies have assessed lumbar accelerations for occupant types individually, but comparative analyses between surrogate occupant types have been limited. Human volunteers best reflect kinematics in real crash scenarios but are limited to low-severity impacts due to ethical limitations. Post-mortem human subjects (PMHS) can be employed in higher speed impacts, however their lack of muscular input may not extensively capture occupant kinematics. Anthropomorphic test devices (ATDs) offer trial consistency and repeatability, however the widely used Hybrid III ATD's relatively simple lumbar spine may not fully emulate the human lumbar vertebrae. Based on these physiological differences between occupant types, there may be corresponding differences in lumbar spine acceleration that have not been objectively quantified. The aim of this study was
Zambare, Keya, Ogbu Felix, Jordan, Arana Barcala, Emily, Westrom, Clyde, Caraan, John, Adanty, Kevin, Shimada, Sean
Mathematical Modeling of Trust Calibration for Human–Automation Safety2026-01-0530To be published on 04/07/2026
Trust between humans and automated vehicles is increasingly recognized as a pivotal factor in achieving safety in advanced vehicles and mobility environments. Poorly calibrated trust—either over-trust leading to complacency or under-trust leading to disengagement—has been identified in numerous incidents involving advanced driver assistance systems and autonomous functions. Yet, most current approaches to managing trust rely on surveys, heuristics, or qualitative assessments, providing little predictive capability for safety engineers and system designers. This paper presents a formal mathematical framework for trust calibration, modeling trust as a dynamic, evolving construct grounded in probabilistic reasoning. We represent trust as a Beta-distributed belief that updates over time through Bayesian inference, with parameters adjusted by observed successes and failures, contextual cues, and system feedback signals. The model also incorporates forgetting and drift functions, allowing
Wen, He, Mounir, Adil
Application of DFSS for Optimizing Thermal Protection in Electric Vehicles During Battery Thermal Runaway Events2026-01-0142To be published on 04/07/2026
Battery thermal runaway is a major safety concern in electric vehicles because of the extreme heat and hazardous gases released during cell failure. These venting events can quickly raise the temperature of the battery enclosure and cabin floor, threatening occupant safety. To address this challenge, this study employs the Design for Six Sigma (DFSS) methodology to design and optimize a thermal protection system that delays and limits heat transfer to the cabin. A physics based transient heat transfer model was combined with DFSS principles to systematically evaluate insulation materials, shield layouts, surface emissivity, and layer geometry. An L 18 orthogonal array was used to identify key parameters and quantify their influence on thermal robustness. The optimized architecture reduced cabin floor temperature rise under severe runaway conditions (600–900 °C vent gas), meeting occupant egress safety requirements. Findings confirm DFSS as an effective framework for developing high
El-Sharkawy, Alaa, Asar, Mona, Taha, Nahla, Sheta, Mai
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
Research on electro-hydraulic compound braking coordinated control strategy based on sliding mode control2026-01-0631To be published on 04/07/2026
Hydraulic braking torque and motor braking torque are the main sources of braking torque of new energy vehicles. Hydraulic braking converts vehicle kinetic energy into heat dissipation, and motor braking converts vehicle kinetic energy into electric energy to achieve energy recovery. In the process of vehicle braking, when the wheels tend to lock, it is easy to cause vehicle instability, which seriously threatens the safety of driving.Therefore, how to coordinated the braking torque of the two braking systems to ensure the vehicle braking safety and energy recovery efficiency is still an urgent problem to be solved. In this paper, the electric vehicle equipped with electro-hydraulic compound braking system is taken as the research object, and the electro-hydraulic compound braking coordinated control strategy considering the general braking state and emergency braking state is proposed. Firstly, a 3-DOF vehicle longitudinal dynamic model is established according to the vehicle dynamic
Zhao, Gaoming, Zhao, Bingquan, Zhao, Binggen, He, Chengkun, Zhang, Xiaoyang
Dynamic Characterization and Viscoelastic Modeling of Polymer Foams for Automotive Applications2026-01-0236To be published on 04/07/2026
Viscoelastic behavior of polymeric materials serves as a critical indicator of their internal structure and chemical composition, offering valuable insights into energy absorption and dissipation mechanisms. This study focuses on the dynamic characterization of polymer foams through both experimental and numerical approaches, aiming to accurately capture their time and frequency dependent mechanical response. Experimental investigations include uniaxial tension and uniaxial compression, which characterize hyperelastic or instantaneous behavior of the material. Stress relaxation tests and Dynamic Mechanical Analysis (DMA) characterize the dependence on time, frequency and temperature. A combination of these tests is effectively utilized to create viscoelastic material models that can describe the material response as a function of time, frequency and temperature containing a viscous and an elastic part. This paper presents dynamic characterization of polymer foams in finite element
M, Gokula Krishnan, Lin, Chunfu, Savic, Vesna
Development of Door Impact Loads Using Pedal Force Sensor and First Principles2026-26-05381/16/2026
The first step in designing or analyzing any structure is to understand “right” set of loads. Typically, off-road vehicles have many access doors for service or getting into cab etc. Design of these doors and their latches involve a knowledge of the loads arising when the door is shut which usually involves an impact of varying magnitudes. In scenarios of these impact events, where there is sudden change of velocity within few milliseconds, produces high magnitude of loads on structures. One common way of estimating these loads using hand calculations involves evaluating the rate-of-change-of-momentum. However, this calculation needs “duration of impact”, and it is seldom known/difficult to estimate. Failing to capture duration of impact event will change load magnitudes drastically, e.g. load gets doubled if time-of-impact gets reduced from 0.2 to 0.1 seconds and subsequently fatigue life of the components in “Door-closing-event” gets reduce by ~8 times. For these problems, structures
Valkunde, Sangram, Ghate, Amit, Gagare, Kiran
Early Prediction of CNG Filling Time Using Artificial Intelligence for Design Optimization2026-26-06621/16/2026
Over the past few decades, Compressed Natural Gas (CNG) has gained popularity as an alternative fuel due to its lower operating cost compared to gasoline and diesel, for both passenger and commercial vehicles. In addition, it is considered more environmentally friendly and safer than traditional fossil fuels. Natural gas's density (0.7–0.9 kg/m3) is substantially less than that of gasoline (715–780 kg/m3) and diesel (849–959 kg/m3) at standard temperature and pressure. Consequently, CNG needs more storage space. To compensate for its low natural density, CNG is compressed and stored at high pressures (usually 200-250 bar) in on-board cylinders. This results in an effective fuel density of 180 kg/m3 at 200 bar and 215 kg/m3 at 250 bar. This compression allows more fuel to be stored, extending the vehicle's operating range per fill and minimising the need for refuelling. Natural Gas Vehicles (NGVs), particularly those in the commercial sector like buses and lorries, need numerous CNG
Choudhary, Aditya Kant, Petale, Mahendra, Dutta, Surabhi, Bagul, Mithilesh
Mathematical Modeling and Genetic Algorithm-Based Energy Management in Hydrogen PEM Fuel Cell Electric Vehicles2026-26-02571/16/2026
Hydrogen Fuel Cell Electric Vehicles (FCEVs) represent a significant trajectory in vehicular decarbonization, harnessing the inherently high energy density of diatomic hydrogen within electrochemical conversion systems. When sourced via renewable pathways, such hydrogen facilitates propulsion architectures characterized by zero tailpipe emissions, enhanced energy efficiency, and extended operational range profiles. Realizing peak systemic efficacy necessitates the synergistic orchestration of high-fidelity fuel cell stack design, resilient compressed gas storage modalities, and nuanced energy governance protocols. To reduce transient stressors and guarantee long-term electrochemical stability, employing multi-scale modeling and predictive simulation, combined with constraint-aware architectural synthesis, is crucial in handling stochastic driving conditions spectra. This study develops a high-fidelity mathematical plant model of a hydrogen Proton Exchange Membrane (PEM) fuel cell
Mulik, Rakesh Vilasrao, E, Porpatham, Senthilkumar, Arumugam
Systemic Modelling and Simulation Approach to Estimate Brake Response Time in a Pneumatic Brake Systems2026-26-04691/16/2026
Brake response time in truck air brake systems is crucial for ensuring safety and operational efficiency. This paper details the development of a simulation model aimed at fulfilling all regulatory requirements for brake response time, as well as serving as a tool for stopping distance calculations. The actual pneumatic circuit, including brake valves, relay valves, brake chambers, and plumbing have been replicated. The aim is to use 1D simulations to predict the response time compliance during the pressurizing phase (when brakes are applied) of the brake system. A mathematical model is developed using a commercially available 1D simulation tool. This model employs a lumped parameter approach for the pneumatic components, with governing equations derived from compressible flow theory and empirical valve flow characteristics. The simulation outcomes provide detailed response time and pressure build-up profiles. Validation against 201 vehicle test cases showed 96% of simulations within
Kumbar, Praful, Murugesan, Karthik, Shannon, Rick
A Mathematical Modelling Approach Based on Artificial Neural Network for Estimation of Key Parameters in Internal Combustion Engine2026-26-06591/16/2026
In a conventional powertrain driven by Internal combustion (IC) engines, various sensors are used to monitor engine performance and emissions. Along with physical sensors, virtual sensors or modelled values of key parameters play an important role for enabling various diagnostics strategies and engine monitoring. Conventional strategies for modelling incorporate the use of regression models, map-based models and physics-based models which have few drawbacks in terms of accuracy and model calibrations efforts. Data driven models or neural networks have fairly better accuracy and reliability for estimating complex parameters. Representing the neural network with a mathematics-based model would help to eliminate drawbacks associated with conventional modelling approach. The proposed methodology uses artificial intelligence technique called artificial neural network (ANN) for estimation of temperature at turbine inlet (TTI) in typical diesel engine. The data driven model is built in Python
Jagtap, Virendra Shashikant, Shejwal, Sanket, Mitra, Partha
Novel Approach for Predicting Steering Rack Load Using Multi-Body Simulation2026-26-03781/16/2026
In the initial stages of a vehicle development program, the sizing of various components is a critical deliverable. The steering system, in particular, requires a precise estimation of the rack load for the appropriate sizing of the rack and assists units. Accurately predicting the load on the system during the early stages of development is challenging, especially in the absence of benchmark or legacy data. Commonly used processes for estimating parking steering effort often employ simplistic approaches that may fail to account for parameters such as tire size, vertical stiffness, and steering geometry, leading to reduced accuracy. This paper introduces an advanced methodology for predicting steering rack loads, which incorporates considerations such as contact patch size and pressure variation, as well as the tire jacking effect. The methodology involves mathematical modeling of the contact patch using mesh-grids, utilizing common inputs available in the early stages of vehicle
Shirke, Umesh, Dabholkar, Aniruddh, Bardia, Vivek, Srivastava, Harshit, Prasad, Tej Pratap
Analysis of Energy Consumption for Heating City Electric Buses and Ways to Reduce It2026-26-01561/16/2026
For regions with cold climate, the range of an electric bus becomes a serious restriction to expanding the use of this type of transport. Increased energy consumption affects not only the autonomous driving range, but also the service life of the batteries, the schedule delays and the load on the charging infrastructure. The aim of the presented research is to experimentally and computationally determine the energy consumption for heating the driver's cabin and passenger compartment of an electric bus during the autumn-winter operation period, as well as to identify and analyze ways to reduce this energy consumption. To determine the air temperature in the passenger compartment, a mathematical model based on heat balance equations was used. This model was validated using data from real-world tests. The research was conducted at a proving ground under two conditions: driving at a constant speed and simulating urban bus operation with stops and door openings. The causes of heat loss in
Kozlov, Andrey, Terenchenko, Alexey, Stryapunin, Alexander
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
Effects of Battery Integration in Modal Behaviour of Electric Two Wheeler Frame2026-26-03101/16/2026
This research investigates the dynamic characteristics of an electric two-wheeler chassis through a combined experimental and numerical approach, and understands the contribution of battery towards overall behaviour of the frame in a structural manner. The study commences with the development of a detailed CAD model, which serves as the basis for Finite Element Analysis (FEA) to predict the chassis's natural frequencies and mode shapes. These numerical simulations offer initial insights into the structural vibration behavior crucial for ensuring vehicle stability and rider comfort. To validate the FEA predictions, experimental modal analysis is performed on a physical prototype of the electric two-wheeler chassis using impact hammer excitation. Multiple response measurements are acquired via accelerometers, and the resulting data is processed to extract experimental modal parameters. The correlation between the simulated and experimental mode shapes is quantitatively assessed using the
Das Sharma, Aritrya, Iyer, Siddharth, Prasad, Sathish, Anandh, Sudheep
A Novel Approach to Optimal Strain Gauge Placement for Structural Assessment: Integrating Looping Configurations with Calibration Techniques2026-26-05511/16/2026
Addressing the challenge of optimal strain gauge placement on complex structural joints and pipes, this research introduces a novel methodology combining strategic gauge configurations with numerical optimization techniques. Traditional methods often struggle to accurately capture combined loading states and real-world complexities, leading to measurement errors and flawed structural assessments [9]. For intricate joints, a looping strain gauge configuration is proposed to comprehensively capture both bending and torsional effects, preventing the bypassing of applied loads. A calibration technique is used to create strain distribution matrices and access structural behavior under different loading conditions. Optimization algorithms are then applied to identify gauge placements that yield well-conditioned matrices, minimizing measurement errors and enhancing data reliability. This approach offers a cost-effective solution by reducing the number of gauges required for accurate stress
Shingate, Uttam, Yadav, Dnyaneshwar, Deshpande, Onkar
Low-Speed Steering Returnability Analysis and Improvements through Mathematical Modeling and CAE Simulation for SUV2026-26-05731/16/2026
In driving, steering serves as the input mechanism to control the vehicle's direction. The driver adjusts the steering input to guide the vehicle along the desired path. During manoeuvres such as parking or U-turns, the steering wheel is often turned fully from lock to lock and then released. It is expected that the steering wheel quickly returns to its original position. Steering returnability is defined as the ratio of the difference between the steering wheel position at lock to lock and the steering wheel angle after 3 seconds of release, to the steering wheel angle at the lock position, under steady-state cornering conditions at 10 km/h. Industry standards dictate that the steering system should achieve 75% returnability under these conditions within 3 seconds. Achieving proper steering returnability characteristics is a critical aspect of vehicle design. Vehicles equipped with Electric Power-Assisted Steering (EPS) systems can more easily meet returnability targets since the
Singh, Ram Krishnan, ahire, Manoj, JAIN, PRIYA, Vellandi, Vikraman, SUNDARAM, RAGHUPATHI, Paua, Ketan
Analysis of Design Parameters of Fuel Cell Stack Design for Vehicle Level Performance Enhancement2026-26-02641/16/2026
The design of the fuel cell stack for enhanced power and voltage characteristics is essential as it impacts the drivability of the vehicles. While many experimental approaches have been explored to improve the performance of the fuel cell stack by refining its design, they are largely limited to trial-and-error based approaches. Hence, the task of identifying the critical parameters affecting the performance of the fuel cell stack becomes tedious. The process is further complicated when many parameters have a counterbalancing impact on the stack performance. To help refine the design process of the fuel cell stack for enhancing the performance, a sensitivity analysis-based approach is proposed in this paper in which a mathematical model of the fuel cell stack relating the parameters and stack power, and voltage is used. The parameters used include membrane thickness, gas diffusion layer thickness, limiting current density, anode current density, transfer coefficient of the anode, and
Inapakurthi, Ravi Kiran, Kumar, Bharat
Model Based Design of Gear Shift Control for Twin Clutch AMT2026-26-00541/16/2026
Model Based Design (MBD) uses mathematical modelling to create, test and refine systems in simulated environment, primarily applied in control system development. This paper discusses an approach to control gear shifting using shift logic on vehicle level for twin clutch transmission using prototype controller. Twin clutch transmission is a concept with two clutches, one at input end of the transmission called primary clutch and the other at output end of the transmission called secondary clutch. This concept is proposed to counter the challenges with conventional transmission which include increased gear shift time and effort in lower gears, potential rollback of vehicle in uphill condition and chance of missed shifts. The advantages of this concept include reduced gear shift effort and improved synchronizer life with potential for reducing the size of the synchro pack. This paper proposes a methodology to develop shift logic, integrate hardware with software, flashing and calibration
Patel, Hiral, Thambala, Prashanth, Tongaonkar, Yogesh, Mosthaf, Joerg, Malpure, Khushal
Material-Optimization in Rib-Stiffened Polymer Structures: A Computational & Analytical Study2026-26-04981/16/2026
The demand for lightweight yet rigid polymer components continue to drive innovation in structural design, particularly for applications requiring optimal stiffness-to-weight ratios. The current literature focuses on single ribbed or homogeneous plate behavior. Understanding the behavior in parallel rib arrangement with inter connections – especially when the ribs are spaced close together is yet to be done. This study examines an alternative rib-stiffening approach for polypropylene plates, where conventional single-rib geometries are reconsidered in favor of parallel dual-rib configurations. While single ribs have been extensively studied, the potential benefits of distributed rib architecture remain less explored, particularly regarding their combined bending performance. The study attempts to understand the behavior of Polypropylene plates specifically, their bending stiffness, load transfer enhancement of the cross-rib structure through mathematical and computational methods. The
Sreejith, M P, Jain, Deepak, Ravi, Abhikrishna, Maheshwari, Pankaj, Kumar, Mandeep
Propeller Shaft Yoke Phase and Inclination Angle Optimization in Passenger Vehicles through Analytical Method2026-26-03481/16/2026
The customer perception of ride comfort with vehicle performance is the most important aspect in a vehicle design. The ride comfort and vehicle performance are influenced by driveline components i.e. propeller shaft phase angle, inclination angle and critical frequency of the driveline system. The optimization of the driveline system is essential to ensure the efficient and smooth power transfer. Propeller shaft is one of the critical components in the driveline to influence the vehicle performance. Propeller shaft characteristics influenced by several factors like vehicle max torque, propeller shaft joint type, materials properties, UJ phase and inclination angle and shaft unbalance value. The optimization of the above parameter within the tolerance limit enables to meet the required performance standard. Various methodologies are available to optimize these parameters to enhance the vehicle performance and comfort leads to customer satisfactions. This study focuses on the analytical
Kumar, Sarvesh, Sanjay, L, S, Manickaraja, Kanagaraj, Pothiraj
Game Theory-Based Coordinated Control Strategy for Multiple Types of Vehicles in Ramp Concourse Area2025-01-734812/31/2025
Decision modeling based on game theory provides an effective means to achieve safe and efficient ramp merging. However, there are some limitations in the current research, such as previous ramp merge control only studied the interaction problem of networked autonomous vehicles, ignoring the diversity of vehicle types, which is a non-negligible problem in real life. To solve this problem, this study proposes to use different game approaches to address the merging challenge. First, a static game is used to deal with the merging problem of networked self-driving vehicles, and then a belief pool with non-cooperative game approach is used to deal with the problem of human driver’s driving style with the merging problem of self-driving vehicles with human-driven vehicles with unknown information. The simulation results show that the efficiency of on-ramp merging can be significantly improved when networked self-driving cars interact with each other; in the case of merging self-driving cars
Gao, Zhenyu, Dong, Jiuyun, Zhang, Lu, Guo, Ge
Predictive Analysis of Slip Distance of Highway Loess Slopes Based on Intense Rainfall Infiltration2025-99-024112/23/2025
Based on field investigations of loess slopes along highways in the Lüliang region, a numerical infiltration model of highway loess slopes was established using the ABAQUS finite element software. The study examined the time to plastic zone coalescence and variations in infiltration range under two intense rainfall scenarios for slopes of different heights. Furthermore, a landslide numerical model of the loess slope was constructed using the FEM-SPH method, and a predictive formula for landslide runout distance of highway loess slopes was derived through data fitting.The results indicate that under the same slope height, increased rainfall intensity leads to a certain degree of reduction in landslide runout distance. Conversely, under the same rainfall condition, greater slope height significantly increases the runout distance. This study provides a theoretical foundation and methodological support for stability evaluation and runout distance prediction of loess slopes under intense
Liu, Manfeng, Li, Hong
The Forecasting and Analysis of Container Throughput at Tianjin Port Based on Combination Forecasting Model2025-99-021612/23/2025
Accurate forecasting of port container throughput is essential for strategic port planning and infrastructure development. This paper systematically employed the GM (1,1) grey prediction model, quadratic exponential smoothing model and ARIMA model to forecast container throughput at Tianjin Port. Subsequently, a combined model was established through weighted integration of these individual predictors. The results demonstrated that the combined model achieved higher predictive accuracy and lower mean error compared to individual model, thereby providing valuable insights for Tianjin Port’s strategic development planning.
Shi, Yujie, Zhou, Xin
Multi-Contact-Point Tire Model Applied to the Study of the Longitudinal and Vertical Dynamics of a 6x6 Military Vehicle2025-36-011212/18/2025
The present study aims to utilize a tire mathematical model that incorporates multiple contact points between the tire and the ground to provide a more accurate and realistic representation of the vertical and longitudinal dynamics of the Guarani 6x6 Armored Personnel Carrier (APC), a medium-wheeled vehicle used by the Brazilian Army. First, the subsystems involved in the longitudinal dynamics of the Guarani APC are introduced and modeled using TMeasy, a physical-mathematical model for tire slip behavior. Subsequently, the subsystems associated with the vehicle’s vertical dynamics are presented and modeled based on Ageikin’s concepts of obstacle negotiation. Finally, the longitudinal and vertical models are integrated to develop a multi-contact-point model with enhanced completeness, considering their mutual influence on each other. The modeling process is conducted within the Simulink® environment of MATLAB®. In each stage, simulations validate the proposed model’s suitability in
Godinho, Gabriel Asvolinsque, Costa Neto, Ricardo Teixeira
Parameter Estimation and Analysis of the Vertical Dynamics of an 8WD Military Vehicle2025-36-002812/18/2025
Vehicle dynamics encompasses a vehicle’s motion along three principal axes: longitudinal, lateral, and vertical. The vertical component is particularly susceptible to vibrational forces that can impair passenger comfort and overall performance, and the suspension system filters these vibrations. Engineers and designers conduct various studies to enhance quality and develop innovative designs in this context. However, when it comes to military vehicles, this system is often treated as classified. Consequently, the proposed work aims to determine the parameters of this system for a wheeled military vehicle with four axles. To achieve this, a mathematical model is proposed utilizing the concepts of power flow and kinematic transformers through a modular system, intended to serve as the foundation for solving an inverse problem to identify these parameters. This approach employs two stochastic methods, particle swarm optimization (PSO) and differential evolution (DE), and field tests to
de Oliveira, André Noronha, Bueno Caldeira, Aldélio, da Costa Neto, Ricardo Teixeira
Fuzzy Logic-Based Traction Control for a 4WD In-Wheel Electric Formula Vehicle2025-36-011412/18/2025
Vehicle dynamic control is crucial for ensuring safety, efficiency and high performance. In formula-type electric vehicles equipped with in-wheel motors (4WD), traction control combined with torque vectoring enhances stability and optimizes overall performance. Precise regulation of the torque applied to each wheel minimizes energy losses caused by excessive slipping or grip loss, improving both energy efficiency and component durability. Effective traction control is particularly essential in high-performance applications, where maintaining optimal tire grip is critical for achieving maximum acceleration, braking, and cornering capabilities. This study evaluates the benefits of Fuzzy Logic-based traction control and torque distribution for each motor. The traction control system continuously monitors wheel slip, ensuring they operate within the optimal slip range. Then, torque is distributed to each motor according to its angular speed, maximizing vehicle efficiency and performance
Oliveira, Vivian Fernandes, Hayashi, Daniela Tiemi, Dias, Gabriel Henrique Rodrigues, Andrade Estevos, Jaqueline, Guerreiro, Joel Filipe, Ribeiro, Rodrigo Eustaquio, Eckert, Jony Javorski
Refrigerants Selection for Automotive Air Conditioning System in Tropical Climates2025-36-014312/18/2025
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Oliveira Dias, Vinícius José de, Barbieri, Paulo Eduardo Lopes, Moreira, Thiago Augusto Araújo, Santos, Alex Henrique, Freitas Paulino, Tiago de
Turbulent Jet Ignition Engine: Calibration of Flame Multipliers for Combustion Model2025-36-023912/18/2025
With the implementation of increasingly stringent regulations for pollutant emissions, such as Proconve L8 [1], which requires a 37% reduction in NOx and non-methane organic gases (NMOG) emissions for light passenger vehicles compared to previous regulations, the automotive engineering community is constantly evolving to develop prediction models that are capable of predicting the performance of Internal Combustion Engines (ICE). With this, the society search solutions to increase fuel conversion efficiency and reduce fuel emissions. In a special case, related to the study of the turbulent jet ignition (TJI) engine, there was a need to develop a refined numerical model that allows for the accurate design of the ignition pre-chamber geometry. In view of this, a one-dimensional modeling was carried out in the GT-SUITE ® software, in its modeling environment for Internal Combustion Engines (ICE), GT-POWER ®, with the objective of determining its ideal volume, parameters such as internal
Silva, Arthur Medeiros, Souza, Ediwaldo Júnio de, Rocha, Hiago Tenório Teixeira Santana, Filho, Fernando Antônio Rodrigues, Guzzo, Márcio Expedito, Oliveira, Wender Pereira de, Baeta, José Guilherme Coelho
Multi-Physics Numerical Modelling of a Magnetorheological Braking System2025-36-005012/18/2025
The global effort to reconsider transport in compliance with ecological challenges leads to a significant increase in the market share of Electric Vehicles (EVs), enlightening secondary sources of pollution. One of the most important is the particles emitted by the abrasion of braking pads. The innovative system addressed in this paper is among the most promising non-polluting solutions to ensure safety and comfort. It uses the capability of the Magneto-Rheological Fluid (MRF) to change its properties when subjected to a magnetic field, generating a braking torque between a stator and a rotor. This study focuses on characterizing the system's performance and endurance during an emergency braking situation by developing a numerical model that involves fluid and structural considerations. This model takes the form of a Finite-Element Model (FEM) that interpolates local forces determined from Computational Fluid Dynamics (CFD) and takes them as input. It enables analysis of the stresses
de Carvalho Pinheiro, Henrique, Billiant, Lucas, Imberti1, Giovanni, Carello, Massimiliana
Gear Ratio Variation Concept Influence on Energy Efficiency Optimization of Light Vehicles2025-36-010412/18/2025
The growing concern regarding global warming pushes the contribution of all emitting sources to mitigate greenhouse gases. The significant light passenger vehicle fleet deserves continued attention, both in the implementation of more efficient new technologies and in the optimization of conventional technologies, which are still widely used. The vehicle’s energy efficiency is directly influenced by the coupling of the internal combustion engine to the transmission system. Engines have a restricted operation region of maximum efficiency that must be adequately explored by the transmission system in the different conditions of vehicle use. Thus, this paper analyzes and quantifies the sensitivity of the vehicle’s energy efficiency of two distinct engine technologies, naturally aspirated and turbocharged, coupled to an automatic transmission system with six discrete or continuously variable gears. Experimental data on the overall efficiency of the engines and the transmission concepts
Rovai, Fernando Fusco, Menezes Lourenço, Maria Augusta de, Rohrig, Marcelo
Methodology for Characterizing the Spray of an Internal Combustion Engine Fuel Injector2025-36-019412/18/2025
This study presents a methodology for characterizing the spray of an internal combustion engine (ICE) fuel injector, focusing on direct injection (DI) systems. It addresses the knowledge gap in academic research regarding injector spray patterns by conducting experimental tests and numerical simulations. Using a Bosch HDEV 1.1 pressure swirl injector and EXXSOL D60 test fluid, spray characteristics were captured with a high-speed camera under varying injection pressures and ambient/counterpressure conditions. These experimental data were used to calibrate a numerical model for simulating spray dynamics within the combustion chamber. The research examines the impact of parameters such as breakup length and breakup size constant on spray behavior, revealing that the breakup size constant significantly affects spray penetration. The study successfully developed and validated a methodology for characterizing and modeling fuel injector sprays, providing a valuable reference for optimizing
Paula Araújo, Gabriel Heleno, Assis, Marcelo Suman Silva, Malaquias, Augusto Cesar Teixeira, Carvalho Torres Filho, Marcos, Baeta, José Guilherme Coelho
Advanced Geological Prediction and Monitoring Measurement for Tunnels in Water-Rich Sections Near Reservoir Areas2025-99-032912/17/2025
In order to ensure the construction safety of tunnels in water-rich sections near reservoir areas, it is very important to adopt comprehensive and reliable advanced geological prediction technology combined with on-site monitoring and measurement. Taking the Chenlingding tunnel as an example, through the comprehensive geological prediction of the broken rock section near the reservoir, the numerical model of the broken rock section was established, and compared with the field measurement data. The results show that the comprehensive advanced geological prediction system combining short, medium and long distances, such as geological radar, seismic wave reflection method and advanced horizontal drilling, has high accuracy in adverse geology, rock fragmentation and water rich conditions in the tunnel; The rich water condition, fault information and rock engineering geology provided by the advanced geological prediction can provide reliable guarantee for the tunnel excavation scheme, the
Dai, Yunfei, Feng, Meijie, Liu, Dacheng, Tang, Xianyuan
Development of an Adaptive Algorithm for the Automatic Emergency Braking System10-10-01-000812/13/2025
Automatic emergency braking (AEB) systems are crucial for road safety but often face performance challenges in complex road and climatic conditions. This study aims to enhance AEB effectiveness by developing a novel adaptive algorithm that dynamically adjusts braking parameters. The core of the contribution is a refined mathematical model that incorporates vehicle-specific correction coefficients and a real-time prediction of the road–tire friction coefficient. Furthermore, the algorithm features a unique driver-style adaptation module to optimize warning times. The developed system was functionally tested on a vehicle prototype in scenarios including dry, wet, and snow-covered surfaces. Results demonstrate that the adaptive algorithm significantly improves collision avoidance performance compared to a non-adaptive baseline, particularly on low-friction surfaces, without introducing excessive false interventions. The study concludes that the proposed adaptive approach is a vital step
Petin, Viktor, Keller, Andrey, Shadrin, Sergey, Makarova, Daria, Antonyan, Akop, Furletov, Yury
Identification of Runway Friction Coefficient Using Extended Kalman Filter09-13-02-001212/11/2025
Aircraft operations during landing or takeoff depend strongly on runway surface conditions. Safe runway operations depend on the tire-to-runway frictional force and the drag offered by the aircraft. In the present research article, a methodology is developed to estimate the braking friction coefficient for varied runway conditions accurately in real-time. To this end, the extended Kalman filtering technique (EKF) is applied to sensor-measured data using the on-ground mathematical model of aircraft and wheel dynamics. The aircraft velocity and wheel angular velocity are formulated as system states, and the friction coefficient is estimated as an augmented state. The relation between the friction coefficient and wheel slip ratio is established using both simulated and actual ground roll data. Also, the technique is evaluated with the simulated data as well as real aircraft taxi data. The accuracy of friction estimation, with and without the measurement of normal reaction force on the
T.K., Khadeeja Nusrath, Singh, Jatinder
Research on Vibration Tension Control of High-Speed Tracked Vehicle Systems2025-99-042412/10/2025
Addressing the vibration issues during the operation of high-speed tracked vehicles, a dynamic tension control method based on an electro-hydraulic servo system is investigated, along with a comparative study of two tension control strategies. Based on the force analysis of the idler wheel and curved arm, a theoretical model for tension near the idler wheel is established. The accuracy of this theoretical numerical model is verified by comparing it with the results of multibody system dynamics simulations conducted in RecurDyn. A co-simulation platform for electro-hydraulic servo control is built using the software interfaces of RecurDyn, Simulink, and AMESim to tune the PID control parameters and achieve dynamic tension control of the track. Simulation results indicate that the root mean square value of the track plate displacement is reduced by 18% when using the PID control strategy, and by 33.3% when employing the fuzzy PID control strategy. Furthermore, the track tension
Huang, Zhangxian, Deng, Jiahui
Investigation of Roll Motion Behavior in a Multi-Functional High-Speed Trimaran Unmanned Vessel2025-99-043912/10/2025
This study focuses on the multifunctional three-body high-speed unmanned boat model, and experimentally measures the roll attenuation characteristics under different draft conditions. It focuses on the influence of the initial roll angle on roll attenuation, and analyzes the change pattern of roll angle over time. Experimental results show that the model shows obvious self-oscillation period and amplitude attenuation. Based on the system identification theory and combined with improved genetic algorithms, a mathematical model used to simulate the roll attenuation motion of the boat model was constructed. The difference between experimental data and fitted values was further evaluated using identification software and verified with data at specific roll angles. In addition, the study also deeply analyzed the change trend of the roll moment coefficient with the initial roll angle. By comparing the experimental results of the three-mall boat and the catamaran, it was found that the three
Zhang, Di, Tong, Wei, Yu, Qingzhu, Liu, Bofei
Aircraft Cross Taxiing Conflict Prediction and Avoidance Methods2025-99-042312/10/2025
With the rapid development of the civil aviation industry, the increasing number of flights has made ensuring the safety and efficiency of airport surface movements a pressing issue. This study establishes a mathematical model to predict the collision risk of aircraft in the intersection area in real time, and proposes appropriate intervention zones for avoidance, implementing a deceleration avoidance strategy. The model is validated using historical operational data from Beijing Capital International Airport, and the results indicate that the proposed model effectively reduces the collision probability to below 0.3. It demonstrates strong performance in predicting cross-path conflicts and reducing conflict risks. Additionally, the deceleration avoidance strategy further lowers the collision probability, improving both the safety and efficiency of airport surface operations. This research offers valuable insights for enhancing the operational efficiency and proactive safety levels of
Zhang, Ting, Lian, Guan, Zhang, Guoxin, Zhao, Yeqi
Lumped Parameter Thermal Network for Automotive Components: Modeling, Simulation, System Identification, and Parameter Estimation2025-01-507811/28/2025
This research paper proposes a framework based on lumped parameter thermal networks (LPTN) to understand the system behavior of thermally stressed component spaces in automotive vehicles. LPTNs offer an energy-based, low-degree-of-freedom model that can represent arbitrary thermal systems inside automotive vehicles. The time response of these low-order models can be calculated using standard ordinary differential equation solvers. The paper showcases the modeling of LPTNs and the calculation of their time response by using an electronic control unit (ECU) of a BMW 7 series. The use of LPTNs instead of exponential functions reduced the MAE in this example by 60.5%. Furthermore, a system identification approach for experimental temperature curves has been developed and implemented. System identification aims to mathematically model system behavior and predict system output. This paper compares least-square estimation (LSE) with constrained minimization (CM), where CM has a higher MAE by
Kehe, Maximilian, Enke, Wolfram, Rottengruber, Hermann
Development of a Comprehensive Predictive QD Knock Simulation Model for Hydrogen, Methanol, and an Ammonia–Hydrogen Blend2025-01-052811/25/2025
To support the transition toward climate-neutral mobility and power generation, internal combustion engines (ICEs) must operate efficiently on renewable, carbon-neutral fuels. Hydrogen, methanol, and ammonia-hydrogen blends are promising candidates due to their favorable production pathways and combustion properties. However, their knock behavior differs significantly from conventional fuels, requiring dedicated simulation tools. This work presents a modeling framework based on quasi-dimensional (QD) engine simulation, including two separate knock prediction models. The first model predicts the knock boundary of a given operating point and combines an auto-ignition model with a knock criterion. The overall methodology was originally developed for gasoline and is here adapted to hydrogen, methanol, and ammonia-hydrogen blends. For this purpose, the relevant fuel properties were incorporated into the auto-ignition model, and a suitable knock criterion was identified that applies to all
Benzinger, Steffen, Yang, Qirui, Grill, Michael, Kulzer, Andre Casal, Plum, Lukas, Hermsen, Philipp, Günther, Marco, Pischinger, Stefan, Hurault, Florian, Foucher, Fabrice, Rousselle, Christine
Data-Based Modeling of Power-Split Hybrids Using Cascaded Neural Networks2025-01-052211/25/2025
Power-split hybrid powertrains represent one of the most advanced and complex types of powertrain systems. The combination of multiple energy sources and power paths offers great potential but results in complex interactions that require improved strategies for optimal efficiency and emission control. The development and optimization of such operating strategies typically involve algorithms that demand fast computational environments. Traditional high-accuracy numerical simulations of such a complex system are computationally expensive, limiting their applicability for extensive iterative optimizations and real-time applications. This paper introduces a data-based approach designed specifically to address this challenge by efficiently modeling the dynamic behavior of power-split hybrid powertrains using cascaded neural networks. Cascaded neural networks consist of interconnected subnetworks, each specifically trained to represent individual drivetrain components or subsystems. This
Frey, Markus, Itzen, Dirk, Yang, Qirui, Grill, Michael, Kulzer, André Casal
Hydro-Pneumatic Suspension Optimization for Mining Explosion-Proof Vehicles in Underground Coal Mines2025-99-010611/11/2025
This study investigates the critical factors influencing the performance of hydro-pneumatic suspension systems (HPSS) in mining explosion-proof engineering vehicles operating in complex underground coal mine environments. To address challenges such as poor ride comfort and insufficient load-bearing capacity under harsh mining conditions, a two-stage pressure HPSS was analyzed through integrated numerical modeling and field validation. A mathematical model was established based on the structural principles of the suspension system, focusing on key parameters including cylinder bore (195–255 mm), piston area (170–210 mm), damping orifice diameter (7–8 mm), check valve flow area, and accumulator configurations (low-pressure: 1.2 MPa, high-pressure: 6 MPa). Experimental trials were conducted in active coal mines, simulating typical mining scenarios such as uneven road surfaces (120 mm obstacles), heavy-load gangue transportation, and confined-space operations in thin coal seams (<1.5 m
Song, Yan, Liang, Yufang
A Theoretical Approach to Secure Protocols for Ultra-Reliable Low-Latency Communication (URLLC) in V2X Systems2025-28-032611/6/2025
Ensuring secure and ultra-reliable low-latency communication (URLLC) is critical for Vehicle-to-Everything (V2X) systems, which form the backbone of autonomous transportation. This paper presents a theoretical framework for designing secure communication protocols tailored for V2X systems with stringent latency and reliability requirements. The proposed framework incorporates dynamic message prioritization, adaptive encryption, and lightweight authentication to address the unique challenges of V2X networks. The study provides mathematical models to predict latency and security performance under varying network conditions, with a focus on scalability and efficiency. This work aims to contribute a foundational approach for future advancements in URLLC protocols in autonomous vehicle ecosystems.
Imran, Shaik Moinuddin
A Load Cell-Free Solution for Weighing2025-28-034611/6/2025
Large farms cultivating forage crops for the dairy and livestock sectors require high-quality, dense bales with substantial nutritional value. The storage of hay becomes essential during the colder winter months when grass growth and field conditions are unsuitable for animal grazing. Bale weight serves as a critical parameter for assessing field yields, managing inventory, and facilitating fair trade within the industry. The agricultural sector increasingly demands innovative solutions to enhance efficiency and productivity while minimizing the overhead costs associated with advanced systems. Recent weighing system solutions rely heavily on load cells mounted inside baling machines, adding extra costs, complexity and weight to the equipment. This paper addresses the need to mitigate these issues by implementing an advanced model-based weighing system that operates without the use of load cells, specifically designed for round baler machines. The weighing solution utilizes mathematical
Kadam, Pankaj
Impact of Enhanced Physics-Based Estimation Modeling for Trapped Air and EGR in Real-Time Control of Hydrogen Injection in a PFI Internal Combustion Engine2025-32-004711/3/2025
Hydrogen PFI engines face abnormal combustion issues, especially during transient operation. The air-to-fuel ratio and trapped exhaust gas significantly affect combustion stability and NOx emissions, requiring continuous monitoring. Real-time estimation of the trapped gas composition and thermodynamic state is therefore crucial but challenging. This work introduces a real-time, physics-based Multi-Input-Multi-Output (MIMO) model for accurately estimating trapped air and exhaust gas mass at the intake valve closing (IVC) event. In detail, the estimation model makes use of dynamic in-cylinder and exhaust pressure measurements to accurately model mass flows and heat exchange equations with 0.5 CAD resolution. This allows extremely high fidelity when modelling the physical properties of the various chemical species along the engine cycle. Moreover, the model calibration appears only in the form of two coefficients implemented on a lookup table for twelve different operating points
Galli, Claudio, Ferrara, Giovanni, Grilli, Niccolò, Balduzzi, Francesco, Romani, Luca, Vichi, Giovanni
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