Browse Topic: Tires

Items (3,245)
This study addresses the insufficient tractive trafficability of four-track unmanned amphibious tracked vehicles (UATV) in beach terrain by proposing an optimization strategy based on coordinated suspension height and hitch point adjustment. A mathematical model of vehicle drawbar pull was established to systematically analyze the influence mechanisms of vertical load distribution, suspension adjustment, and hitch point elevation on tractive trafficability. DEM-MBD coupling simulations revealed differentiated traction laws under sandy loam and clay conditions, particularly regarding track overlap effects. Results demonstrate that in sandy loam, rear-axle traversal over front-axle tracks reduces drawbar pull due to soil loosening, whereas track overlap enhances drawbar pull in clay through soil compaction. Nine suspension-hitch configurations were tested, validating optimization strategies: increased front-axle loading (Configuration a) in sandy loam and reduced front-axle loading
Chen, YaoyaoGao, XueWang, WenhaoXu, Xiaojun
According to the working characteristics of the tire changer, the movement characteristics of its rim clamping mechanism are analyzed, and the complex movement structure is abstracted and simplified into four identical six-bar mechanism subunits. One of the subunits is taken as the research object, and the mathematical model of kinematic analysis is established. Using MATLAB software to simulate and analyze the motion law of each component, the mechanical characteristics of the component are analyzed. The optimization of the design parameters of the “six-bar mechanism subunit” is realized, the rim clamping mechanism becomes more stable, and the clamping force follows the diameter of the rim more closely.
Zhao, FengqinZhou, LiyaoWang, MantongHuo, Fengwei
Accurate tire models are a key enabler for vehicle dynamics simulation, control design, and lap time optimization, particularly in the context of Formula Student race cars, where vehicle setups and tire characteristics differ significantly from production vehicles. State-of-the-art tire models, such as Pacejka’s Magic Formula, generally provide high prediction accuracy. However, their predefined functional structure and large number of coupled parameters are designed for broad applicability across many tire types rather than for specific racing tires. This often results in limited interpretability, nontrivial parameter identification, and unnecessary model complexity for specialized applications such as Formula Student. This paper presents a data-driven approach for deriving compact and physically interpretable tire force models using symbolic regression. The proposed method employs an intelligent tree search to systematically explore the space of mathematical expressions and identify
Anselment, MarcelBorowski, JulianRudolph, Stephan
Vehicle manufacturers use Hardware-in-the-Loop (HiL) approaches to validate overall vehicle characteristics, including those dependent on the powertrain, at an early stage of vehicle development. A powertrain test rig is a typical example. In the specific setup, the vehicle engine and side shafts are mechanically coupled to the load machines of the test rig, eliminating the physical influence of the rims, tires and vehicle body. Adapting a specimen to the test rig changes some characteristics. This affects the specimen's vibration behaviour, making it more challenging to validate comfort-related characteristics. A particular example is longitudinal vehicle shuffle; the powertrain's first torsional natural frequency causes it. The natural frequencies of the real vehicle and device under test differ significantly, so a road-matching approach is not directly feasible. To account not only for tire-road contact but also for the missing vehicle mass, some scientific studies propose a purely
Hübner, CarlProkop, Günther
Battery electric vehicles (BEVs) place high demands on electric drives across a wide operating range: high efficiency in customer-related driving scenarios and maximum performance in dynamic driving modes. A promising solution to this challenge is the dynamic reconfiguration of the electric machine winding configuration between series and parallel mode, enabling optimal electromagnetic properties of the drive for different operating points. This paper presents the design and prototyping of an electronic winding reconfiguration system for high-performance traction applications. The hardware prototype has been designed and built, but has not yet been tested, which is why the results are based on simulations. Unlike mechanical winding reconfiguration concepts, which have long transition times and cannot switch under load, the proposed system enables fast and safe load transitions between the winding configurations. The study describes the topology and hardware of the switching unit
Oestreicher, RaphaelSchneider, Jörgvon Ohlen, DavidFuchs, PatrickKulzer, André Casal
Gyroscopic effects split circumferential traveling-wave resonances of rotating structures into forward and backward branches. This work first analyzes the splitting in the co-rotating (Lagrangian) frame to provide physical intuition for the evolution of the two branches with spin speed. A transformation to the inertial (Eulerian) frame is then derived, showing that the observed frequencies are shifted by a kinematic Doppler-like term that acts with opposite sign on the forward and backward waves, leading to different Campbell-diagram slopes depending on the observation frame. The resulting framework is validated experimentally on a freely rotating, unloaded tire using two complementary sensing modalities: wireless on-tire accelerometers (co-rotating view) and a scanning laser Doppler vibrometer (inertial view). A frequency-domain SVD-based identification (FDD/ODS-SVD) is used to extract poles and deformation patterns over a range of spin speeds, enabling Campbell diagrams in both
del Fresno Zarza, JavierNaets, Frank
Part- or component-level tests are commonly performed by Tiers and OEMs to investigate the NVH behavior and loading mechanisms. However, because test bench dynamics differ from those of the actual vehicle environment, correlating measured sound, acceleration and forces between bench and vehicle often proves challenging. Blocked forces offer a way to address this issue, as they provide test bench and vehicle independent load representations. This effectively enables different Tiers to deliver consistent load data, which OEMs can then use to better tune excitation and noise transmission on their vehicles. This paper focuses on 2 test bench compensation techniques, involving pure test and a simulation models of the tire to obtain accurate blocked-forces. The compensation techniques are validated on four testbenches of different companies.
Reichart, Ronde Klerk, Dennis
Alloy wheels are essential safety components in two-wheeled vehicles. This study details the finite element analysis (FEA) used to simulate and evaluate the wheel and tire performance under the double mass impact load specified by the AIS-073 (Part-1) standard. The impact is carried out by dropping a striking mass along with a main mass onto the alloy wheel–tire assembly, as per the standard. The alloy wheel is modeled using a three-dimensional finite element model with elastic-plastic material behavior, and the tire is modeled with its internal elements (e.g., carcass, belt, etc.). The prediction of wheel impact failure is based on the total plastic work of the ductile fracture mechanism. The validity of results is confirmed by comparing the predicted permanent lateral rim deformation against the measured lateral deformation from a corresponding physical test.
Minz, Jai ShankarSingh, Sanjay KumarNirala, Deepak Kumar
Corner module vehicles (CMVs) achieve the decoupling of driving, braking, steering, and suspension, significantly enhancing vehicle handling potential, but under extreme operating conditions, the interactions between actuators severely constrain the improvement of vehicle handling performance. In order to mitigate conflicts between subsystems and enhance vehicle handling stability, a hierarchical hybrid game–based limit stability control method for CMVs is proposed in this article. Taking into account the handling potential of subsystems under limit conditions, a Stackelberg leader–follower game is designed by first designating Direct Yaw moment Control (DYC) as the leader and Active Rear Steering (ARS) as the follower. Subsequently, the DYC–ARS and Active Suspension System (ASS) were constructed into a non-cooperative game system, and the Nash equilibrium solution was solved through iteration. The lower-level controllers, respectively, established a tire force distribution model that
Peng, JinxinXiao, FengKe, YuanJin, Liqiang
Meta-wheels—non-pneumatic wheels whose performance is governed by structural geometry rather than internal pressure—offer new opportunities for directional stiffness control. Yet achieving independent tuning of longitudinal, lateral, and vertical stiffness within a single wheel architecture has remained challenging due to the inherent coupling in conventional radial and planar curved spokes. In this study, we introduce a three-dimensional (3D) discrete curved-spoke design that provides explicit geometric control through two independent parameters: the in-plane curvature angle (α) and the out-of-plane inclination angle (β). Using spoke-level and full-wheel finite-element (FE) simulations, supported by a simplified cantilever-beam analytical model, we show that these two geometric parameters govern stiffness in fundamentally different ways. The curvature angle α serves primarily as a geometric softener, reducing stiffness in all directions while maintaining a high top-loading ratio (TLR
Han, HeeseungLiu, ZhipengJu, Jaehyung
Wind-tunnel tests were conducted using a 30%-scale DrivAer model, in estateback and notchback rear-geometry configurations, to investigate aerodynamic performance changes associated with snow and ice buildup on passenger vehicles. Around 20 snow/ice accumulation patterns were tested, at a Reynolds number of 2.8 × 106 based on model wheelbase, for each of the notchback and estateback variants. 5 additional patterns were tested on the estateback with roof-rack support bars. Snow accumulation was modelled with foam, while ice accumulation was simulated with aluminum tape hand-formed to the desired shape. A simulated full-scale snow thickness of 58 mm on the hood, roof and trunk increased the wind-averaged drag coefficient by 16% for both model variants. With 90 mm of snow, the drag of the estateback variant increased by 19%. Drag changes increased with, but were not proportional to, snow thickness. Chamfered front and rear edges, representing windblown shapes, reduced the drag penalty
de Souza, FenellaMcAuliffe, Brian
The tire model is a crucial component in the design of the K-characteristic of FSAE racing car suspensions, and directly influences the achievement of maximum cornering lateral force. Not only do the slip angle, vertical load, tire pressure, and camber angle affect the mechanical characteristics of the tire, but temperature is also an important influencing factor when FSAE vehicle tires operate at high speeds. However, the modeling process of traditional tire models based on temperature characteristics is often very complex. The FSAE tire test code (FSAE TTC) already has a large amount of official sample data, which provides a basis for data-driven neural network models. This study implemented a hybrid modeling methodology, constructing two cascaded feedforward neural networks that combine the physical interpretability of the Magic Formula tire model with the nonlinear approximation capabilities of neural networks. The first network model uses slip angle, vertical load, tire pressure
Liu, XiyuanWang, ShenyaoLi, MingyuanHuang, Jiayu
Flat tires represent a common yet serious issue in vehicle safety, leading to compromised control, increased braking distance, and potential rim or structural damage when undetected. Conventional tire pressure monitoring systems (TPMS) rely on embedded sensors that can fail, incur high replacement costs, and are not always equipped in older or low-cost vehicles. To address these limitations, this study presents a comprehensive visual dataset for flat-tire classification using computer vision and machine learning techniques. The dataset comprises 600 labeled images—300 flat-tire and 300 non-flat-tire samples—collected from diverse vehicle types, lighting conditions, and viewpoints. This dataset is designed to support the training and benchmarking of lightweight edge-AI models suitable for real-time deployment on embedded platforms. A set of supervised learning models were evaluated. Results demonstrate that visual-based classification provides a cost-effective and scalable pathway
Gunasekaran, AswinGovilesh, VidarshanaChalla, KarthikeyaMaxim, BruceShen, Jie
This study focused on investigating how tire grip performance on dry, wet, and snowy road surfaces varied with the different level of tire wear. New, 50% worn, and end-of-life tires were prepared following worn tire preparation standards. Additionally, worn tires obtained under real driving conditions in the market were used. Tire grip performances on dry, wet and snowy roads were characterized respectively by using an indoor flat belt machine, an outdoor trailer, and a specially designed snow truck. The results demonstrated an evolution of grip performance as a function of tire wear. The study identified differences in impact between worn tire preparation methods —real driving versus artificial—particularly on snowy road surfaces. Furthermore, the effects of tire stiffness, reduced tread depth, and tread surface roughness of worn tires were investigated for each type of road surface. The objective of this study is to enhance the understanding of tire behavior throughout its lifecycle
Kim, ChangsuSaito, Yoshinori
Off-road autonomous vehicle systems must be able to operate across unstructured and variable terrain while avoiding obstacles. This presents significant challenges in vehicle and control system design, especially for less conventional platforms such as 6×4 vehicles. While forward driving autonomy has developed and matured in recent years, effective reverse navigation remains an under-explored area of vehicle co-design. Reversing 6×4 vehicles have limited rear steering authority, an extended wheelbase, and asymmetric traction, which introduce complex dynamics into any control system that is used. To address this need, a robust and experimentally validated fuzzy logic control architecture for 6×4 reverse navigation was developed during the course of this project. This architecture incorporates both near-field and long-range path data with adaptive outputs controlling steering and velocity based on a rule base that covers the whole vehicle state space. This method has low computational
Dekhterman, Samuel R.Sreenivas, Ramavarapu S.Norris, William R.Patterson, Albert E.Soylemezoglu, AhmetNottage, Dustin
This paper presents a novel approach to modelling and analyzing a 315/80R22.5 sized truck tire running over dry and snow-covered surfaces. The tire is modelled using Finite Element Method (FEM) in ESI Virtual Performance Solutions (VPS) software. The tire model consists of various parts representing the tread, under tread, carcass, sidewalls and beads in addition to the rim. The tire model is then verified in both static and dynamic domains against experimental data. The experimental results were conducted over a dry surface at a high-speed test track in Hällered, Sweden, at a constant travelling speed of 80 km/h, and a constant vertical load of 26 kN with sensors depicting both temperature and inflation pressure changes throughout a 40-minute run. A tire temperature model is developed, and the simulation results are correlated with the measured temperature of the tested tires. In addition, the rolling resistance variation with speed, temperature and inflation pressure is predicted and
Opatha, DillonOijer, FredrikEl-Sayegh, ZeinabEl-Gindy, Moustafa
Vehicle pull under acceleration is a phenomenon commonly observed in high-performance vehicles and electric vehicles (EVs), primarily arising asymmetric driveshaft angles, drivetrain architecture, and suspension geometry. In addition to these mechanical factors, tire characteristics, particularly the tire lateral force generated at the contact patch, significantly influence this effect. The lateral force is intricately tied to the dynamics of the contact patch and the geometric design of the tire tread pattern. This study investigates the relationship between tread pattern geometry and vehicle pull under acceleration, emphasizing the role of tire lateral force variations. By employing finite element (FE) simulation, lateral force response variations (dfy/dfx) resulting from tread block deformation were analyzed. Based on these simulation, a robust analytical methodology for tread pattern evaluation and optimization was established. The developed tread pattern characteristic parameter
Yoon, YoungsamJang, DongjinKim, HyungjooLee, Jaekil
Roller bearings are used in many rotating power transmission systems in the automotive industry. During the assembly process of the power transmission system, some types of roller bearings (e.g., tapered roller bearings) require a compressive preload force. Those bearings' rolling resistance and lifespan strongly depend on the preload set during the installation process. Therefore, accurate setting of the preload can improve bearing efficiency, increase bearing lifespan and reduce maintenance costs over the life of the vehicle. A new method for bearing preload measurement has shown potential for both high accuracy and fast cycle time using the frequency response characteristics of the power transmission system. An open problem is experimental validation of the multi-row tapered roller bearing analytical model. After validation, the analytical model can be used to predict the assembled system damped natural frequency for a desired bearing preload. This work presents the experimental
Gruzwalski, DavidMynderse, James
This paper investigates the performance of a computational radial passenger car tire over winter road sand at different operating conditions. This study seeks to address gaps in literature by using both an experimental direct shear-strength test and then validating the same test in a Finite Element Analysis (FEA) software called Virtual Performance Solution (VPS) using a Smoothed-Particle Hydrodynamic (SPH) technique to model a winter road sand. The simulated sand was measured against physical sand data ensuring validation of the density, internal friction angle and cohesion. Once the sand was validated against physical testing data the sand was layered atop an icy road surface to understand the influence sand has on tractive effort and rolling resistance performance. With modelled and validated winter road sand and a Continental CrossContact LX Sport tire size 235/55R19 testing conditions were set up. The tire-sand interaction was simulated using a node-to-segment contact algorithm
Fenton, ErinEl-Sayegh, Zeinab
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, KunZhao, ZhiguoWang, YutaoXia, XueChen, XiHu, Yingjia
The Electro-Mechanical Brake (EMB) system is a novel type of brake by wire systems with independently controllable characteristics. This system aids in the decoupling analysis of the vehicle and actuator dynamics, thereby improving the accuracy of parameter identification. Therefore, this paper proposes an innovative parameter identification method for vehicle parameters and longitudinal tire model parameters, based on the characteristics of the EMB system and onboard sensors. First, based on the wind resistance and rolling resistance coefficients obtained from the vehicle coasting conditions, a decoupled constant clamping force sequence braking condition for the front and rear axles is designed by integrating the characteristics of the EMB actuator and vehicle dynamics. This approach enables the identification of vehicle and nonlinear longitudinal tire model parameters, significantly improving the accuracy of parameter identification. Next, considering the nonlinear characteristics of
Huang, JiayiCheng, YulinZhuo, GuirongLe, QiaoWei, WeiShu, Qiang
Tires are critical to vehicle dynamics, transmitting traction, braking, and cornering forces to the road. A tire blowout, the sudden and rapid loss of inflation pressure due to puncture or structural failure, can cause severe instability, rollover, or collisions. Understanding vehicle response during blowout events is essential for developing robust safety systems and control strategies. Earlier developed simulation models are used to study and understand vehicle behavior during blowouts, but there is a lack of on-road testing platforms to validate these models experimentally. In this paper, an experimental platform integrating a tire blowout device and an instrumentation system has been developed to address this gap. The blowout device consists of multiple solenoid valves mounted on the wheel surface and powered by a 12V power supply. All valves can be triggered at the same time using an RF remote, producing rapid and synchronized deflation. As an extension of this implementation, an
Kanthala, Maha Vishnu Vardhan ReddyKrishnakumar, AshwinLin, Wen-ChiaoChen, Yan
For off-road driving, particularly on steep grades and over barriers, the engine torque is a key design criterion of off-road vehicles. In conventional powertrains with combustion engines, mechanical all-wheel-drive systems combined with differential locks are used to distribute the torque demand between the front and the rear axle based on wheel-specific traction. With the growing market share of electric powertrains, off-road applications are becoming increasingly relevant for electric passenger cars. In comparison to conventional powertrains, electric all-wheel-drive configurations do not have a mechanical torque transfer between the two axles. If one axle experiences low traction, the second axle can rely on its own torque capability only. Transfer of unused torque of the slipping axle to the other one is not possible. The challenge, therefore, is to specify the right torque requirements for each axle for off-road driving while avoiding over-dimensioning and high powertrain costs
Martin, MichaelWinkelheide, JonasHartmann, LukasSturm, AxelHenze, Roman
At present, tire failures directly affect road safety, and the number of incidents caused by them is gradually increasing. Examining wheel attachment loosening on time is vital for vehicle safety. Tire-related incidents not only put people in peril but also have a detrimental effect on the economy. Therefore, the goal of this research is to develop a new and effective method for identifying wheel attachment loosening. A novel gear error reduction approach, distinct from traditional methods, combines advanced computing and probabilistic analysis. This paper involves three key components: extracting looseness eigenvalues, calculating ring gear errors, and computing the tire loosen probabilities. Gear errors derived from the Kalman filter and adjusted for speed, eigenvalues were calculated, and a tire loosening probability analysis was performed. Real-car trials across speeds and roads confirm its accuracy and reliability. This technology can improve automotive safety and maintenance
Liu, JianjianZhang, ZhijieWang, ZhenfengMa, GuangtaoShi, MeijuanLiu, JingZhao, BinggenLu, Yukun
High-precision estimation of key vehicle–road state parameters is crucial for ensuring the accurate and safe control of mining trucks (MT), as well as for reliable trajectory tracking. Among these parameters, the vehicle sideslip angle is particularly critical for assessing and predicting lateral stability. However, its direct measurement is challenging, and its estimation typically depends on an accurate characterization of tire cornering stiffness. For MT, large variations in loading conditions (from empty to fully loaded) pose significant challenges to sideslip angle estimation due to the resulting nonlinearity and variability of tire cornering stiffness. To address this issue, a novel joint estimation framework integrating the Moving Horizon Estimation (MHE) and Square-Root Cubature Kalman Filter (SCKF) is proposed to simultaneously achieve high-precision estimation of both tire cornering stiffness for each tire and vehicle sideslip angle. In this framework, the cornering stiffness
Xia, XueShen, PeihongJiao, LeqiLi, TaoChen, HuiyongZhao, KunJiao, LeqiZhao, Zhiguo
Parking assist systems are among the most widely adopted driver-assistance features in modern vehicles. A key component of these systems is the path planning module, which ensures accurate vehicle alignment within a parking slot while satisfying various constraints such as maintaining slot centering, avoiding collisions in confined spaces, minimizing maneuver count, and achieving the shortest feasible path. Multiple path generation techniques—such as geometric, polynomial-based, and search-based methods—have been developed to enable safe and efficient parking maneuvers. However, most of these approaches rely on the simplifying assumption that the vehicle’s instantaneous center of rotation (ICR) is fixed, typically located on the non-steering axle. In practice, the ICR is not constant and can vary significantly across vehicles due to several physical and kinematic factors, including steering geometry, tire slip characteristics, suspension configuration, and weight distribution
Awathe, ArpitPatanwala, AbizerJain, ArihantVarunjikar, Tejas
As internal combustion engines are replaced by quieter electric motors in ground vehicles, noise and vibration sources aside from the powertrain have become relatively more important. This is especially true of tires. Measurement of the dynamic vibratory characteristics of tires is critical to understanding their influence on the noise and vibration performance of vehicles, both outside the vehicle body and inside of it. In this work, the normal modes and operating deflection shapes of a Yokohama Geolander A/T light truck tire are measured using traditional modal analysis techniques as well as a non-contact Scanning Laser Doppler Vibrometry (SLDV) approach. Boundary conditions including free, fixed, loaded, and rotating are implemented to the tire and investigated. Rotating conditions are accomplished in a physical chassis dynamometer environment, with the measured tire mounted on the front axle of a Chevrolet Silverado 1500 pickup truck. Modes of vibration and associated natural
Bastiaan, Jennifer M.Chauda, GauravBaqersad, JavadGupta, ArjunDhami, Kevalya
The vibrating half-car model is used to represent the dynamic behavior of a truck’s dependent suspension system, capturing four degrees of freedom. This research investigates time and frequency responses of vibration behavior of half-car model with possible tire–road separation. This investigation is significant because all previously reported analyses based on the tire-road attachment were incorrect, particularly regarding the tire-road separation phenomenon. The differential equations are extended to enhance the accuracy of the model, incorporating tire–road separation conditions for both wheels. A numerical approach is applied to simulate the vertical and roll dynamics of the system under the separation assumption. The simulation results are validated through experiments conducted using ADAMS View software. Integrating the tire–road separation into the model results in dynamic responses that closely reflect real-world behavior. These findings provide valuable guidance for designing
Nguyen, Quy DangJazar, Reza
In response to the decline in vehicle stability and the resulting safety risks caused by inappropriate driver operations during high-speed emergency obstacle avoidance, a human–machine cooperative control strategy based on driver operation recognition is proposed. The strategy establishes a vehicle controllability boundary by integrating real-time driver inputs with tire adhesion limits, enabling dynamic evaluation of the influence of operations on system controllability and identification of potential inappropriate operations. On this basis, a control authority allocation mechanism is developed, capable of adaptively adjusting to vehicle states and driver operations. By combining road boundary constraints with vehicle stability envelope constraints, the strategy dynamically regulates the steering angle, ensuring vehicle stability while retaining the driver’s effective intentions as much as possible. Unlike conventional path-tracking or single-envelope control approaches, the proposed
Liu, YangyiZhou, BingWu, XiaojianJiang, XiaokunCui, Qingjia
Aluminum foils have gained traction with EV battery manufacturers for their pouch cell format. Over the years, it has evolved as a material of choice, but it is still plagued by the issues of stress concentration and swelling due to lower strength and lower stiffness of base aluminum layer. Preliminary investigation revealed that laminates using steel foil material (thickness < 0.1mm) could be a potential candidate for EV pouch cell casing. Thus, steel-based laminate was developed meeting key functional requirements (e.g., barrier performance, insulation resistance, peel strength, electrolyte resistance, formable without cracking at edges, and heat sealing compliant). This innovative patented steel-based laminate [1] was further used to manufacture pouch cell prototypes (up to a maximum capacity of 2.8Ah) for key performance evaluation (e.g., cell cycling and nail penetration). The study paves the way for a low cost, sustainable and flexible yet strong steel-based laminate packaging
Singh, Pundan KumarRaj, AbhishekKumar, AnkitChatterjee, SourabhVerma, Rahul KumarSamantaray, BikashGautam, VikasPandey, Ashwani
Tire noise reduction is important for improving ride comfort, especially in electric vehicle due to lack of engine noise and majority of the noise generated in-cabin is from tire-road interaction. Therefore, the tire tread pattern contribution is one of the important criteria for NVH performance apart from other structurally generated noise and vibration. In this work a GUI-based pitch sequence optimization tool is developed to support tire design engineers in generating acoustically optimized tread sequences. The tool operates in two modes: without constraints, where the pitch sequence is optimized freely to reduce tonal noise levels; and with constraints, where specific design rules are applied to preserve pattern consistency and manufacturability. The key point to be considered in this pitch sequence is that it should be reducing the tonal sound and equally spread i.e., the same pitch cannot be concentrated on one side which may lead to non-uniformity. So, the restriction is that
Sampathraghavan, LakshmiRamarathnam, Krishna KumarMantripragada PhD, Krishna TejaRamachandran, Neeraj
Tire wear progression is a nonlinear and multi-factor degradation phenomenon that directly influences vehicle safety, handling stability, braking performance, rolling resistance, and fleet operational cost. Global accident investigations indicate that accelerated or undetected tread depletion contributes to nearly 30% of highway tire blowouts, highlighting the limitations of conventional wear indicators such as physical tread wear bars, mileage-based service intervals, and periodic manual inspections. These manual and threshold-based approaches fail to capture dynamic driving loads, compound ageing, pressure imbalance effects, or platform-specific wear behaviours, thereby preventing timely intervention in real-world conditions. This work presents an Indirect Tire Wear Health Monitoring System that employs an advanced Machine Learning + Transfer learning architecture to infer tread wear level and Remaining Useful Life (RUL) without relying on any tire-mounted sensors. The system ingests
Imteyaz, ShahmaIqbal, Shoaib
With increased deterioration of road conditions worldwide, automotive OEMs face significant challenges in ensuring the durability of structural components. The tyre being the primary point of contact with the road is expected to endure harshest of impacts while maintaining the other performance functions such as Ride & Handling, Rolling resistance, Braking. Thus, it is considered as the most challenging component in terms of design optimization for durability. The current development method relies on physical testing of initial samples, followed by iterative construction changes to meet durability requirements, often giving trade-off in Ride & Handling performance. To overcome these challenges, a frugal simulation-based methodology has been developed for predicting tyre curb impact durability before vehicle-level testing so that corrective action can be taken during the design stage.
Sundaramoorthy, RagasruobanLenka, Visweswara
Rack load estimation during the pre-design stages is critical for the calibration of steering systems, particularly in achieving the desired steering feel and optimizing assistance strategies in Electric Power Assisted Steering (EPAS). Conventional approaches often depend on physical vehicle testing or simplified empirical equations, which may be time-consuming or lacks the fidelity required for early-stage analysis. This paper presents a 1D simulation strategy to address limitations from conventional approaches. The proposed rack force estimation model is based on multi-physics analytical equations that calculate tire-road friction forces and the resulting moments about the steering axis, delivering a physics-based yet computationally efficient solution. The rack force estimation model is further extended into EPAS system model by incorporating Direct Current (DC) brushed motor model. The rack force estimation model is validated against physical test data which demonstrates a high
Adsul, SourabhIqbal, Shoaib
The automotive market trend is shifting more and more to SUVs and crossovers. This, therefore, means increasing consumer demand for off-road abilities in passenger vehicles. While dedicated off-road platforms provide a path to performance robustness, getting the same level of functionality out of a passenger vehicle with minimal architectural changes proves to be a great feat for engineers. One highly critical performance determinant in the domain of off-road ability is wheel articulation, it requires independent movement capacity of the wheels to keep contact and stability over uneven terrain. Traditional articulations found in passenger car suspensions—created for comfort, packaging, and on-road dynamics—are limited by suspension geometry, damper alignment as well as compliance setup. Damper side loads- were not considered a significant factor in suspension systems that are operating within their original intended design envelope for on-road use. However, when the vehicle is taken
Siddiqui, ArshadIqbal, ShoaibDwivedi, Sushil
Accurate range estimation in battery electric vehicles (BEVs) is essential for optimizing performance, energy efficiency, and customer expectations. This study investigates the discrepancies between physical test data and simulation predictions for the BEV model. A detailed range delta analysis identifies key contributors to the observed deviations, including regenerative braking inefficiencies, increased propulsion demand, auxiliary loads, and estimated drivetrain losses within the Electric Drive Module (EDM) during traction and regen. Results indicate that the test vehicle exhibits lower regenerative braking efficiency, higher traction forces and lower regen energy than predicted by simulations, primarily due to EDM inefficiencies and friction brake usage during regeneration. The study underscores the importance of refining simulation methodologies by integrating real-world, test based EDM loss maps to improve accuracy and better align predictive models with actual vehicle
Mahajan, PrasadKesarkar, SidheshAli, Shoaib
Unlike internal combustion engine (IC Engine) vehicles, the rapidly growing electric vehicle (EV) market demands tyres with superior yet often conflicting performance characteristics. The increased weight of EVs, due to their heavy batteries, necessitates robust tyres with reinforcement and higher inflation pressure. Conversely, increased wear due to higher initial torque and the need for lower rolling resistance to extend range, combined with the requirement for better grip for improved handling, call for advanced compound and tread pattern designs. EV tyres need to be stiffer, lighter, and low hysteresis, making it very hard to reduce low-frequency (20-200 Hz) interior noise that was previously masked by engine noise. This study investigates the low-frequency (20-200 Hz) structural-borne interior noise performance of EV tyres using both experimental and simulation tools. By wisely tuning the tyre's stiffness, mass, and damping properties, the necessary noise targets can be achieved
Subbian, JaiganeshM, Saravanan
The present study enumerates the effectiveness of using Foam-inside Tyres (FIT) for attenuating the in-cabin noise due to tire-road interaction in Internal Combustion Engines (ICE) converted Electric SUVs (E-SUV). Due to the elimination of the ICE Prime movers in (E-SUV), the Tyre booming, Tyre cavity, and rumbling noise in the structure-borne region are significantly audible in the driver’s & passenger's ears globally for E-SUVs. Foam tyres reduce tyre cavity resonance. However, the effectiveness of the acoustic foam is predominant between 180 to 240 Hz only. In the present study, In Cabin Noise (ICN) measurement was completed on the comfort testing track, and the results of structure-borne in-cabin noise up to 500 Hz were analysed. These measurements identified the vehicle in-cabin sensitive frequencies, which are affected by the tyre and wheel assembly. To analyse the contribution of the Tyre design parameters and to predict the ICN performance in the whole vehicle simulation, CD
Singh, Ram KrishnanDeivasigamani Purushothaman, BalakrishnanPaua, KetanAhire, ManojAdiga, Ganesh N
Transportation sector in India accounts for 12% of total energy consumption. Demand of energy consumption is being met by the imported crude oil, which makes transportation sector more vulnerable to fluctuating international crude oil prices. India is mindful of its commitment in 2016 Paris climate agreement to reduce GHG emissions intensity of its GDP by 40% by 2030 as compared to 2005 levels. To fast track the decarbonization of transportation sector, commercial vehicle manufacturers have been exploring other viable options such as battery electric vehicles (BEVs) as a part of their fleet. As on today, BEV has its own challenges such as range anxiety & high total cost of ownership. Range anxiety can be certainly addressed by optimum sizing of electric powertrain, reduction in specific energy consumption (SEC) & use of effective regeneration strategies. Higher SEC can be more effectively addressed by doing vehicle energy audit thereby estimating the energy losses occurring at each
Gijare, SumantKarthick, K.Juttu, SimhachalamThipse, Sukrut S.A, JothikumarJ, Frederick RoystonSR, SubasreeG, HariniM, Senthil Kumar
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, UmeshDabholkar, AniruddhBardia, VivekSrivastava, HarshitPrasad, Tej Pratap
Today due to time to market requirements, Original Equipment Manufacturers (OEM) prefers platform modularity for Product Development in Automotive Domain. Money and time being main constraint we need to focus on single platform which can give flavors of different category just by changing Ride height and Tyre and some extra tunable. Taking this as challenge still tyre development for new variant demands lot of time and iterations which can lead to delays in time to market. This study provides a virtual development process using driver in loop Simulator and Multi body dynamics simulation which are real time capable and integrating physical tire models. The proposed alteration introduces ride height changes, weight distribution changes, and center of gravity changes from existing vehicle design. The proposed new vehicle variant also introduces tire change from highway terrain type to all-terrain type as it was intended to deliver some off-roading capabilities, thereby vehicle dynamics
Shrivastava, ApoorvAsthana, Shivam
The lateral and longitudinal dynamics of passenger car tyres are critical to overall vehicle safety, handling, and stability. These characteristics directly influence braking, acceleration, and cornering performance. This study investigates the impact of key input parameters, namely inflation pressure, vertical load, and inclination angle, on tyre behaviour using a dual approach: Indoor testing with a Flat-Trac CT+ (FTCT+) and Outdoor evaluation using a skid trailer. Lateral dynamics are evaluated at slip angles to analyze lateral force and aligning moment characteristics. The influence of inclination angle, pressure, and load is quantified through cornering stiffness and aligning stiffness. The tests are conducted in both sweep and steady-state modes. To maintain data consistency, all tests use tyres of a single specification sourced from the same production batch. Longitudinal behaviour of a tyre is characterized by various parameters such as peak friction coefficient, sliding
Sethumadhavan, ArjunDuryodhana, DasariTomer, AvinashGhosh, PrasenjitMukhopadhyay, Rabindra
In autonomous vehicles, it is vital for the vehicle to drive in a manner that ensures the driver is comfortable and has confidence in the system, which ensures he does not feel compelled to intervene or take control of the vehicle. The system must consider environmental factors and other aspects to provide the driver with a comfortable and stress-free drive. In this regard, the road friction coefficient, which quantifies the grip experienced by the tire on a road, is a critical parameter to be considered by several comfort and safety functions. An inaccurate estimation of road friction coefficient can lead to discomfort in worst case safety risks for the driver, as the system would be over or underestimating the tire’s grip on the road and this alters the vehicle’s response to control inputs. In the context of Advanced Driver Assistance Systems (ADAS), dynamically estimating the road friction coefficient can significantly improve the safety and comfort of driving functions. However
Rangarajan, RishiSukumar Rajammal, Prem KumarSingh, Akshay PratapKumaravel, Sujeeth SelvamKop, AnandBharadwaj, Pavan
With increasing demand for improving the vehicle Ride and Handling (R&H) performance, the synergy between vehicle subsystems such as suspension, chassis, brakes & tyres play a major role towards it. In this regard, the interaction between wheel rim width and tyre performance characteristics is a key focus area in vehicle development process. Detailed research is being conducted worldwide to understand their dynamics of interaction and based on the tested data, vehicle manufacturers make the design selection. In this context, the proposed study aims to provide a in-depth analysis of how variations in wheel rim width affect key tyre performance parameters such as lateral force characteristics, damping property, tyre footprint, and pinch cut resistance. Also, the subsequent influence on vehicle-level performance parameters such as R&H, braking, steering, and durability is captured. Based on these analysis, appropriate wheel rim size selection is done which is most optimal for the project
Singh, Ram KrishnanPaua, KetanSundaramoorthy, RagasruobanLenka, Visweswaraahire, ManojAdiga, Ganesh N
Tyre rolling resistance is a fundamental parameter in automotive engineering, directly impacting vehicle fuel efficiency and overall performance. The Rolling Resistance Coefficient (RRC) is influenced by tyre construction, material properties, and operational conditions such as inflation pressure, vehicle speed, ambient temperature, and road surface roughness. This study investigates the influence of critical parameters—including test speed, inflation pressure, temperature on the rolling resistance of tyres of various sizes. While previous research has predominantly focused on radial tyres, this paper extends the analysis to include bias-ply tyres. The findings aim to offer valuable insights for policymakers and researchers by examining the behavior of bias tyres under real-world conditions. The results will be particularly beneficial for vehicle and steering system designers, offering data-driven insights to support future tyre and vehicle development. Additionally, the study presents
Joshi, AmolBelavadi Venkataramaiah, ShamsundaraKhairatkar, Vyankatesh
Sustainability and environmentally friendly business practices are becoming essential. Tyre industries are embracing the green initiatives to reduce its impact on the environment by exploring the eco-friendly strategies. Starting from the ethical raw material sourcing to a creative recycling technique, strategies are widely distributing in every step of tyre manufacturing to disposition. Each stage of a tyre’s life cycle viz. raw material procurement, manufacturing, transportation both upstream and downstream as well as during the end-of-life phases have an emission-saving potential. It is important to reduce emissions at every stage of tyre’s lifecycle. We have recently developed a Sustainable Tyre with 11% less GHG emission through sustainable raw material approach. Bio sourced or bio attributed raw materials like Styrene Butadiene Rubber (SBR), Polybutadiene Rubber (PBR), Rubber process oil (RPO) and Silica along with natural rubber (NR) had been used. Beside the raw materials from
Bhandary, TirthankarSingha Roy, SumitPaliwal, MukeshDasgupta, SaikatChattopadhyay, DipankarDas, MahuyaMukhopadhyay, Rabindra
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