Browse Topic: Tire friction
In order to manage the serious global environmental problems, the automobile industry is rapidly shifting to electric vehicles (EVs) which have a heavier weight and a more rearward weight distribution. To secure the handling and stability of such vehicles, understanding of the fundamental principles of vehicle dynamics is inevitable for designing their performance. Although vehicle dynamics primarily concerns planar motion, the accompanying roll motion also influences this planar motion as well as the driver's subjective evaluation. This roll motion has long been discussed through various parameter studies, and so on. However, there is very few research that treats vehicle sprung mass behavior as “vibration modes”, and this perspective has long been an unexplored area of vehicle dynamics. In this report, we propose a method to analytically extract the vibration modes of the sprung mass by applying modal analysis techniques to the governing equations of vehicle handling and stability
As global warming and environmental problems are becoming more serious, tires are required to achieve a high level of performance trade-offs, such as low rolling resistance, wet braking performance, driving stability, and ride comfort, while minimizing wear, noise, and weight. However, predicting tire wear life, which is influenced by both vehicle and tire characteristics, is technically challenging so practical prediction method has long been awaited. Therefore, we propose an experimental-based tire wear life prediction method using measured tire characteristics and the wear volume formula of polymer materials. This method achieves practical accuracy for use in the early stages of vehicle development without the need for time-consuming and costly real vehicle tests. However, the need for improved quietness and compliance with dust regulations due to vehicle electrification requires more accuracy, leading to an increase in cases requiring judgment through real vehicle tests. To address
Advanced driver assistance systems (ADASs) and driving automation system technologies have significantly increased the demand for research on vehicle-state recognition. However, despite its critical importance in ensuring accurate vehicle-state recognition, research on road-surface classification remains underdeveloped. Accurate road-surface classification and recognition would enable control systems to enhance decision-making robustness by cross-validating data from various sensors. Therefore, road-surface classification is an essential component of autonomous driving technologies. This paper proposes the use of tire–pavement interaction noise (TPIN) as a data source for road-surface classification. Traditional approaches predominantly rely on accelerometers and visual sensors. However, accelerometer signals have inherent limitations because they capture only surface profile properties and are often distorted by the resonant characteristics of the vehicle structure. Similarly, image
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. One open problem is the design of the production controller, which relies on a detailed sensitivity study of the system frequency response to changes in the bearing and system design parameters. Recently, an analytical model was developed for multi-row tapered roller bearings that includes all appropriate bearing and power transmission system design parameters. During the assembly process, some of the parameters related to the roller positions cannot be controlled. These parameters include the actual position of the first roller compared to the vertical axis, the relative position of the rollers between the bearing rows, and others. This work presents a sensitivity analysis of the effects of those uncontrollable parameters on the analytical model. The sensitivity study determines the percentage change
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 preload setting 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 high accuracy and fast cycle time using the frequency response characteristics of the power transmission system. One open problem is the design of the production controller, which relies on a detailed sensitivity study of the system frequency response to changes in the bearing and system design parameters. Recently, an analytical model was developed for multi-row tapered roller bearings that includes
With better performance and usage of clean and renewable energy, electric vehicles have ushered in more and more consumers’ favor nowadays. However, insufficient driving range especially in hot and cold ambient conditions still greatly restricts the extensive application of electric vehicles. This paper presents a methodology of establishing multi-discipline coupled full vehicle model in AMESim to investigate the energy consumption and driving range of an electric vehicle in normal and hot ambient conditions. Full vehicle energy consumption test was carried out in the climate chamber to check the accuracy of simulation results. Firstly, basic framework of the full vehicle model established in AMESim was introduced. Next, modeling details of sub-systems including vehicle dynamic system, electrical system, coolant circuit system, air-conditioning system and control strategy were illustrated. Then, full vehicle energy consumption tests were carried out in 23°C and 38°C ambient conditions
Novel experimental and analytical methods were developed with the objective of improving the reliability and repeatability of coast-down test results. The methods were applied to coast-down tests of a SUV and a tractor-trailer combination, for which aerodynamic wind-tunnel data were available for comparison. The rationale was to minimize the number of unknowns in the equation of motion by measuring rolling and mechanical resistances and wheel-axle moments of inertia, which was achieved using novel experimental techniques and conventional rotating-drum tests. This led to new modelling functions for the rolling and mechanical resistances in the equation of motion, which was solved by regression analysis. The resulting aerodynamic drag coefficient was closer to its wind-tunnel counterpart, and the predicted low-speed road load was closer to direct measurements, than the results obtained using conventional methods. It is anticipated that applying the novel techniques to characterize the
An energy-use analysis is presented to examine the potential energy-savings and range-extension benefits of aerodynamic improvements to tractors and trailers used in commercial transportation. The impetus for the study was the observation of aerodynamically-redesigned/optimized tractor shapes of emerging zero-emission commercial vehicles that have the potential for significant drag reduction over conventional aerodynamic tractors. Using wind-tunnel test results, a series of aerodynamic performance models were developed representing a range of tractor and trailer combinations. From modern day-cab and sleeper-cab tractors to aerodynamically-optimized zero-emission cab concepts, paired with standard dry-van trailers or low-drag trailer concepts, the study examines the energy use, and potential savings thereof, from implementing various fleet configurations for different operational duty cycles. An energy-use analysis was implemented to estimate the energy-rate contributions associated
The increased importance of aerodynamics to help with overall vehicle efficiency necessitates a desire to improve the accuracy of the measuring methods. To help with that goal, this paper will provide a method for correcting belt-whip and wheel ventilation drag on single and 3-belt wind tunnels. This is primarily done through a method of analyzing rolling-road only speed sweeps but also physically implementing a barrier. When understanding the aerodynamic forces applied to a vehicle in a wind tunnel, the goal is to isolate only those forces that it would see in the real-world. This primarily means removing the weight of the vehicle from the vertical force and the rolling resistance of the tires and bearings from the longitudinal force. This is traditionally done by subtracting the no-wind forces from the wind at testing velocity forces. The first issue with the traditional method is that a boundary layer builds up on the belt(s), which can then influence a force onto the vehicle’s
This paper investigates the development of a Finite Element model of a Mixed Service Drive truck tire sized 315/80R22.5 equipped with thermal simulating properties. The physical experiments were performed at a high-speed track in Hällered, Sweden for the truck combination travelling at a constant speed of 80 km/h. For this investigation, the Gross Combination Weight is approximately 42 metric tons. In the Finite Element Analysis environment, ESI Virtual Performance Solutions, the truck tire is designed with hyperelastic Ogden solid rubber definitions. The Ogden material definition is used in this application as it is more suitable to perform thermal and wear analysis within the Finite Element environment. The Finite Element truck tire model is simulated to increase in two different temperature rates. The truck tire model simulates the thermal build-up over time for select tires on a High-Capacity transport truck combination, particularly a driven tire on the tractor. Finite element
To further optimize the automatic emergency braking for pedestrian (AEB-P) control algorithm, this study proposes an AEB-P hierarchical control strategy considering road adhesion coefficient. First, the extended Kalman filter is used to estimate the road adhesion coefficient, and the recursive least square method is used to predict the pedestrian trajectory. Then, a safety distance model considering the influence factor of road adhesion coefficient is proposed to adapt to different road conditions. Finally, the desired deceleration is converted into the desired pressure and desired current to the requirements of the electric power-assisted braking system. The strategy is verified through the hardware-in-the-loop (HIL) platform; the simulation results show that the control algorithm proposed in this article can effectively avoid collision in typical scenarios, the safe distance of parking is between 0.61 m and 2.34 m, and the stop speed is in the range of 1.85 km/h–27.64 km/h.
From humble Chevrolet Bolts to six-figure Lucid Airs, every EV can reverse its electric motors to slow the vehicle while harvesting energy for the battery, the efficient tag-team process known as regenerative braking. Today's EVs do this so well that traditional friction brakes, which clamp onto a spinning wheel rotor or drum, can seem an afterthought. Witness Volkswagen's decision to equip its ID.4 with old-fashioned rear drum brakes, with VW claiming drums reduce EV rolling resistance and offer superior performance after long periods of disuse.
In this article, a finite element analysis for the passenger car tire size 235/55R19 is performed to investigate the effect of temperature-dependent properties of the tire tread compound on the tire–road interaction characteristics for four seasons (all-season, winter, summer, and fall). The rubber-like parts of the tire were modeled using the hyperelastic Mooney–Rivlin material model and were meshed with the three-dimensional hybrid solid elements. The road is modeled using the rigid body dry hard surface and the contact between the tire and road is modeled using the non-symmetric node-to-segment contact with edge treatment. At first, the tire was verified based on the tire manufacturer’s data using numerical finite element analysis based on the static and dynamic domains. Then, the finite element analysis for the rolling resistance analysis was performed at three different longitudinal velocities (10 km/h, 40 km/h, and 80 km/h) under nominal loading conditions. Second, the steady
Wet pavement conditions during rainfall present significant challenges to traffic safety by reducing tire–road friction and increasing the risk of hydroplaning. During high-intensity rain events, the roadway pavement tends to accumulate water, forming a film that can have serious implications for vehicle control. As the longitudinal speed of the vehicle increases, a water wedge forms in front of the tire, leading to partial loss of contact with the road. At critical hydroplaning speed, a complete water layer forms between the tire and the road. Although less common, dynamic hydroplaning poses severe risks when high-intensity rainfall coincides with high vehicle traveling speed, leading to a complete loss of control over vehicle steering capabilities. This study advances hydroplaning research by integrating real-world data from the Road Weather Information System (RWIS) with an existing hydroplaning model. This approach provides more accurate hydroplaning risk assessments, emphasizing
Road loads, encompassing aerodynamic drag, rolling resistance, and gravitational effects, significantly impact vehicle design and performance by influencing factors such as fuel efficiency, handling, and overall driving experience. While traditional coastdown tests are commonly used to measure road loads, they can be influenced by environmental variations and are costly. Consequently, numerical simulations play a pivotal role in predicting and optimizing vehicle performance in a cost-effective manner. This article aims to conduct a literature review on road loads and their effects on vehicle performance, leveraging experimental data from past studies from other researchers to establish correlations between measured road loads and existing mathematical models. By validating these correlations using real-world measurements, this study contributes to refining predictive models used in automotive design and analysis. The simulations in this study, utilizing five distinct empirical
Road friction coefficient is an important characteristic parameter of the interaction force between road surface and tire, which plays a crucial role in vehicle dynamics control. At present, it is difficult to measure the road friction coefficient directly. Therefore, it is a challenge to estimate the road adhesion coefficient accurately and reliably. Considering that tire force is an important reflection of road adhesion coefficient, a road adhesion coefficient estimation method based on nonlinear tire force observation is proposed in this paper. First, based on the nonlinear Dugoff tire model, the nonlinear observer of tire longitudinal force is established. Then a 7-degree-of-freedom (DOF) nonlinear vehicle model is established, and the noise adaptive square root cubature kalman filter (ASRCKF) method is used to estimate the lateral force of the front and rear wheels. Finally, based on the ASRCKF algorithm, combined with the longitudinal force and lateral force information, the all
Since the inception of battery driven electric vehicles in the automotive world, there has been a constant challenge in maximizing the range of an electric vehicles through various means including battery technology, vehicle weight optimization, low drag coefficients etc. The tires being a viscoelastic composite material have now become a vital to the range performance of an EV. The rolling resistance of a tire is now become a hotter topic than ever. The rolling resistance coefficient (RRC) is the measure of energy loss during rolling due to viscoelastic dissipation in the tire. The viscous dissipation in tire arises due to hysteresis in the various components of a tire including tread, sidewall, inner liner, apex etc rubber compounds. The internal friction between layers of body ply, steel belts and tread crown ply also contribute to the internal heat generation. Therefore, the development of ultra-low RRC tires is a serious challenge for tire engineers. Nevertheless, the recent
For all the engineering that takes place at the Treadwell Research Park (TRP), Discount Tire's chief product and technical officer John Baldwin told SAE Media that there's actually something akin to magic in the way giga-reams of test data are converted into information non-engineers can usefully understand. TRP is where Discount Tire generates data used by the algorithms behind its Treadwell tire shopping guide. The consumer-facing Treadwell tool, available in an app, a website and in stores, provides tire shoppers with personalized, simple-to-understand recommendations that are mostly based on a five-star scale. Discount Tire and its partners have tested over 20,000 SKUs, representing 500 to 1000 different types of tires over the years, Baldwin said, including variants and updates. Testing a tire to discover it has an 8.2 rolling resistance coefficient is one thing. The trick is finding a way to explain it to someone standing in a tire shop.
Over the past twenty years, the automotive sector has increasingly prioritized lightweight and eco-friendly products. Specifically, in the realm of tyres, achieving reduced weight and lower rolling resistance is crucial for improving fuel efficiency. However, these goals introduce significant challenges in managing Noise, Vibration, and Harshness (NVH), particularly regarding mid-frequency noise inside the vehicle. This study focuses on analyzing the interior noise of a passenger car within the 250 to 500 Hz frequency range. It examines how tyre tread stiffness and carcass stiffness affect this noise through structural borne noise test on a rough road drum and modal analysis, employing both experimental and computational approaches. Findings reveal that mid-frequency interior noise is significantly affected by factors such as the tension in the cap ply, the stiffness of the belt, and the properties of the tyre sidewall.
AEB systems are critical in preventing collisions, yet their effectiveness hinges on accurately estimating the distance between the vehicle and other road users, as well as understanding road conditions. Errors in distance estimation can result in premature or delayed braking and varying road conditions alter road-tire friction coefficients, affecting braking distances. The integration of advanced sensors like LiDARs has significantly enhanced distance estimation. Cameras and deep neural networks are also employed to estimate the road conditions. However, AEB systems face notable challenges in urban environments, influenced by complex scenarios and adverse weather conditions such as rain and fog. Therefore, investigating the error tolerance of these estimations is essential for the performance of AEB systems. To this end, we develop a digital twin of our test vehicle in the IPG CarMaker simulation environment, which includes realistic driving dynamics and sensor models. Our simulated
The problem of transport-related greenhouse gas (GHG) emissions is common knowledge. In recent years, the electrification of cars is being prompted by many as the best solution to this issue. However, due to their rather big battery packs, the embedded ecological footprint of electric cars has been shown to be still quite high. Therefore, depending on the size of the vehicle, tens -if not hundreds- of thousands of kilometres are needed to offset this burden. Human-powered vehicles (HPVs), thanks to their smaller size, are inherently much cleaner means of transportation, yet their limited speed impedes widespread adoption for mid-range and long-range trips, favouring cars, especially in rural areas. This paper addresses the challenge of HPVs speed, limited by their low input power and non-optimal distribution of the resistive forces. The article analyses dissipation sources from rolling resistance, aerodynamics, inertia, and more for various vehicles, emphasizing the fundamental role of
This article introduces an innovative method for predicting tire–road interaction forces by exclusively utilizing longitudinal and lateral acceleration measurements. Given that sensors directly measuring these forces are either expensive or challenging to implement in a vehicle, this approach fills a crucial gap by leveraging readily available sensor data. Through the application of a multi-output neural network architecture, the study focuses on simultaneously predicting the longitudinal, lateral, and vertical interaction forces exerted by the rear wheels, specifically those involved in traction. Experimental validation demonstrates the efficacy of the methodology in accurately forecasting tire–road interaction forces. Additionally, a thorough analysis of the input–output relationships elucidates the intricate dynamics characterizing tire–road interactions. This research underscores the potential of neural network models to enhance predictive capabilities in vehicle dynamics, offering
Emissions and fuel economy certification testing for vehicles is carried out on a chassis dynamometer using standard test procedures. The vehicle coastdown method (SAE J2263) used to experimentally measure the road load of a vehicle for certification testing is a time-consuming procedure considering the high number of distinct variants of a vehicle family produced by an automaker today. Moreover, test-to-test repeatability is compromised by environmental conditions: wind, pressure, temperature, track surface condition, etc., while vehicle shape, driveline type, transmission type, etc. are some factors that lead to vehicle-to-vehicle variation. Controlled lab tests are employed to determine individual road load components: tire rolling resistance (SAE J2452), aerodynamic drag (wind tunnels), and driveline parasitic loss (dynamometer in a driveline friction measurement lab). These individual components are added to obtain a road load model to be applied on a chassis dynamometer. However
In order to study the tire friction characteristics under wet skid surface, the “pseudo” hydrodynamic pressure bearing effect is used to be equivalent to the hydrodynamics of water film, and an advanced Lugre tire hydroplaning dynamic model is developed by combining the arbitrary pressure distribution function. The water hydroplaning dynamic tests were carried out for 285/70R19.5 tire under wet of different water film thickness and dry conditions, and the parameters of the advanced Lugre tire dynamic model were identified. The results show that the tire water-skiing model proposed in this paper can effectively simulate the friction characteristics of tires under different water film thicknesses. Under dry conditions, 0.5mm water film and 1mm water film road conditions, the relative errors of the maximum tire friction coefficient between the tested and advanced Lugre tire model are 1.11%, 0.12% and 0.16%, respectively. The root mean square (RMS) relative errors of tire friction
This paper investigates the tire-road interaction for tires equipped with two different solid rubber material definitions within a Finite Element Analysis virtual environment, ESI PAMCRASH. A Mixed Service Drive truck tire sized 315/80R22.5 is designed with two different solid rubber material definitions: a legacy hyperelastic solid Mooney-Rivlin material definition and an Ogden hyperelastic solid material definition. The popular Mooney-Rivlin is a material definition for solid rubber simulation that is not built with element elimination and is not easily applicable to thermal applications. The Ogden hyperelastic material definition for rubber simulations allows for element destruction. Therefore, it is of interest and more suited for designing a tire model with wear and thermal capabilities. Both the Mooney-Rivlin and Ogden-equipped Mixed Service Drive truck tires are subjected to a simulated static vertical stiffness test to validate their static domain characteristics against
Planning for charging in transport missions is vital when commercial long-haul vehicles are to be electrified. In this planning, accurate range prediction is essential so the trucks reach their destinations as planned. The rolling resistance significantly influences truck energy consumption, often considered a simple constant or a function of vehicle speed only. This is, however, a gross simplification, especially as the tire temperature has a significant impact. At 80 km/h, a cold tire can have three times higher rolling resistance than a warm tire. A temperature-dependent rolling resistance model is proposed. The model is based on thermal networks for the temperature at four places around the tire. The model is tuned and validated using rolling resistance, tire shoulder, and tire apex temperature measurements with a truck in a climate wind tunnel with ambient temperatures ranging from -30 to 25 °C at an 80 km/h constant speed. Dynamic tire simulations were conducted using a heat
The dynamic model is built in Siemens Simcenter Amesim platform and simulates the performances on track of JUNO, a low energy demanding Urban Concept vehicle to take part in the Shell Eco-Marathon competition, in which the goal is to achieve the lowest fuel consumption in covering some laps of a racetrack, with limitations on the maximum race time. The model starts with the longitudinal dynamics, analysing all the factors that characterize the vehicle’s forward resistance, like aerodynamic forces, altimetry changes and rolling resistance. To improve the correlation between simulation and track performances, the model has been updated with the implementation of a Single-Track Model, including vehicle rotation around its roll axis, and a 3D representation of the racetrack, with an automatic trajectory following control implemented. This is crucial to characterise the vehicle’s lateral dynamics, which cannot be neglected in simulating its performances on track. Analysis of suspension
The standard usage of Combined Braking System (CBS) in lower cc/power 2-wheeler vehicles serves to reduce stopping distance and improve braking stability. The CBS system achieves this by engaging both the front and rear wheel brakes, taking advantage of the high load transfer characteristic during 2-wheeler braking. However, the current design of the CBS system relies on linear system analysis, based on vehicle geometry, load distribution, and tire-road friction. This approach overlooks the non-linearities inherent in braking dynamics, such as tire behavior and dynamic Center of Gravity (CoG) location. Consequently, the current CBS design methodology exhibits limitations, particularly in extreme scenarios where wheel lock-up may occur, such as on low friction surfaces or during panic braking. This paper proposes the incorporation of tire non-linearities into the design of CBS systems using Pacejka’s tire model. Initially, calculations are performed to optimize the braking
Climate change and global warming are one of the major challenges faced by the world today. A significant number of Indian cities rank among the most polluted globally, with vehicular emissions being the primary contributor. To address this issue, the Government of India is actively advocating for the adoption of zero-emission vehicles such as electric vehicles through policies and initiatives like FAME II [1], PMP and the National Mission for Transformative Mobility and Storage. The acceptance of electric vehicles is growing in the Indian market seeing more than 200% increase in sales in the year 2022 compared to 2021 with a large share of 2-wheelers, 3-wheelers and compact cars getting electrified. Further adoption of electrification on a much larger scale currently faces the major challenge of high overall vehicle cost compared to conventional vehicles, with the major contribution coming from the HV battery which is the costliest system on the electric vehicles. An electric vehicle
Knowing the tire pressure during driving is essential since it affects multiple tire properties such as rolling resistance, uneven wear, and how prone the tire is to tire bursts. Tire temperature and cavity pressure are closely tied to each other; a change in tire temperature will cause an alteration in tire cavity pressure. This article gives insights into which tire temperature measurement position is representative enough to estimate pressure changes inside the tire, and whether the pressure changes can be assumed to be nearly isochoric. Climate wind tunnel and road measurements were conducted where tire pressure and temperature at the tire inner liner, the tire shoulder, and the tread surface were monitored. The measurements show that tires do not have a uniform temperature distribution. The ideal gas law is used to estimate the tire pressure from the measured temperatures. The results indicate that of the compared temperature points, the inner liner temperature is the most
Over the last few years, the Electric Vehicle Market (EV’s) has experienced significant growth. One of the major challenges faced by electric vehicles is its tyre performance requirements. Reduced range, Increased vehicle weight, higher motor torque and absence of engine needs lower rolling resistance, higher load capacity, low tread wear & low noise tyre, respectively. All these demands will lower the ride comfort performance of the Electric Vehicle. The objective of this work is to investigate the impact of tyre parameters on the ride comfort performance of EV’s. Tyre construction, tread compound and tyre pressure have a significant impact on the ride comfort performance. Tests like drive point mobility, modal analysis and cleat test are conducted experimentally as well as using virtual tools, the ride comfort performance of tyres is evaluated. The results show that tyre construction and inflation pressure have major influence on the ride comfort performance of EV tyres. Finally, the
The increasing demand for electric mobility has brought about significant advancements in tyre design. This paper covers the latest developments in tyre design that cater specifically to the needs of electric vehicles (EVs). EVs have unique performance characteristics that place greater emphasis on tyre requirements like High traction, Wear resistance, Low Cavity & pattern noise, Low Rolling resistance and High load carrying capacity. Hence, the tyre manufacturers have been working relentlessly to create advanced designs that can meet these requirements. This paper will cover various aspects of tyre design, including tyre cavity, tread patterns, sidewall design, compound & reinforcement design, and various construction techniques. The tyre cavity and tread pattern play a crucial role in the overall performance of an EV. The new tyre cavity with flat tread and adaptive tread pattern are optimized to provide low rolling resistance, pattern noise reduction and enhanced dry and wet
Precise vehicle state and the surrounding traffic information are essential for decision-making and dynamic control of intelligent connected vehicles. Tremendous research efforts have been devoted to developing state estimation techniques. This work investigates the research progress in this field over recent years. To be able to describe the state of multiple traffic elements uniformly, the concept of a vehicle neighborhood system is proposed to describe the system composed of vehicles and their surrounding traffic elements and to distinguish it from the traditional macroscopic traffic research field. In this work, the vehicle neighborhood system consists of three main traffic elements: the host vehicle, the preceding vehicle, and the road. Therefore, a review of state estimation methods for the vehicle neighborhood system is presented around the three traffic objects mentioned earlier. This article performs a comprehensive analysis of these approaches and depicts their strengths and
Non-pneumatic tires (NPTs) have been widely used due to their advantages of no occurrence of puncture-related problems, no need of air maintenance, low rolling resistance, and improvement of passenger comfort due to its better shock absorption. It has a variety of applications as in earthmovers, planetary rover, stair-climbing vehicles, and the like. Recently, the unique puncture-proof tire system (UPTIS) NPT has been introduced for passenger vehicles segment. The spoke design of NPT-UPTIS has a significant effect on the overall working performance of tire. Optimized tire performance is a crucial factor for consumers and original equipment manufacturers (OEMs). Hence to optimize the spoke design of NPT-UPTIS spoke, the top and bottom curve of spoke profile have been described in the form of analytical equations. A generative design concept has been introduced to create around 50,000 spoke profiles. Finite element model (FEM) model is developed to evaluate the stiffness and damage
This SAE Recommended Practice describes a test method for determination of heavy truck (Class VI, VII, and VIII) tire force and moment properties under cornering conditions. The properties are acquired as functions of normal force and slip angle using a sequence specified in this practice. At each normal force increment, the slip angle is continually ramped or stepped. The data are suitable for use in vehicle dynamics modeling, comparative evaluations for research and development purposes, and manufacturing quality control. This document is intended to be a general guideline for testing on an ideal machine. Users of this SAE Recommended Practice may modify the recommended protocols to satify the needs of specific use-cases, e.g., reducing the recommended number of test loads and/or pressures for benchmarking purposes. However, due care is necessary when modifying the protocols to maintain data integrity.
The pending Euro 7 vehicle-emissions regulations include a significant new sustainability wrinkle: first-ever restrictions for PM emissions from brakes. In a proposal submitted in November of 2022, the European Commission detailed its new Euro 7 vehicle emissions standard, which is widely expected to be approved by the European Parliament and Council and begin phase-in starting on July 1, 2025. Another phase of emissions legislation is nothing new, but one critical element of Euro 7 is new to the regulation chessboard: first-ever limits on how much particulate matter (PM) can be generated by a vehicle's brakes. This element of Euro 7 has auto and commercial-vehicle brake-component suppliers scurrying. Commercial vehicles are subject to their own compliance levels as they interpret how the new regulations will impact their existing technologies and what new solutions will be required. The proposed Euro 7 regulations also address the emissions of fine microplastic particles created by
The automotive industry’s journey towards fully autonomous vehicles brings more and more vehicle control systems. Additionally, the reliability and robustness of all these systems must be guaranteed for all road and weather conditions before release into the market. However, the ever-increasing number of such control systems, in combination with the number of road and weather conditions, makes it unfeasible to test all scenarios in real life. Thus, the performance and robustness of these systems needs to be proven virtually, via vehicle simulations. The key challenge for performing such a range of simulations is that the tire performance is significantly affected by the road/weather conditions. An end user must therefore have access to the corresponding tire models. The current solution is to test tires under all road surfaces and operating conditions and then derive a set of model parameters from measurements. The key disadvantages of this approach are high costs and turnaround times
Safety is considered one of the most important parameters when designing a ground vehicle. The adverse effect of weather on a vehicle can lead to a surge in safety issues and accidents. Several safety assistance systems are available in modern vehicles, which are designed to lessen the negative effects of weather hazards. Although these safety systems can intervene during crucial conditions to avoid accidents, driving a vehicle on snowy or icy terrain can still be a challenging task. Road conditions with the least tire-road friction often results in poor vehicle handling, and without any kind of safety system it can lead to mishaps. With the use of Adams Car software and vehicle dynamics modeling, a realistic relationship between the vehicle and road surface may be established. The simulation can be used to have a better understanding of vehicle handling in snowy and icy conditions, tire-ice interaction, and tire modeling. In this work a vehicle dynamics model is created using the
The physical characteristics of Mars's soil have an impact on how easily a spacecraft can land and navigate the planet's surface. On the surface of Mars, wheeled robots known as "rovers" were planted to carry out scientific investigations on the planet's historical temperature, surface geology, and possibilities for past or current life. The challenges of guiding mobile robots across terrain that is sloping, rocky, and deformable have brought to light the significance of creating precise simulation models of the tire and mars soil interaction. In this paper, current efforts to create a terramechanics-based model of rover movement using a Non-Pneumatic (NP) tire on planetary surfaces are discussed. Since no rocks or soils have been brought back to Earth from Mars, Martian simulants are frequently used for testing rovers and other devices for Mars terrain research. Using a Finite Element Analysis-based NP tire model that is modeled and tested, in addition to a dry loose Martian soil that
Tire-road friction condition is crucial to the safety of vehicle driving. The emergence of autonomous driving makes it more important to estimate the friction limit accurately and at the lowest possible excitation. In this paper, an early detection method of tire-road friction coefficient based on pneumatic trail under cornering conditions is proposed using an intelligent tire system. The previously developed intelligent tire system is based on a triaxial accelerometer mounted on the inner liner of the tire tread. The friction estimation scheme utilizes the highly sensitive nature of the pneumatic trail to the friction coefficient even in the linear region and its approximately linear relationship with the excitation level. An indicator referred as slip degree indicating the utilization of the road friction is proposed using the information of pneumatic trail, and it is used to decide whether the excitation is sufficient to adopt the friction coefficient estimate. The friction
A large increase in GHG emissions has led to a substantial increase in EV adoption. Due to its complexity, predicting the states of LIB remains to be a roadblock for mass adoption. Furthermore, the ability to predict the performance of an EV through its lifetime continues to be a difficult task. The following work provides how a detailed electro-thermal P2D battery model, GT-AutoLion1D, can be implemented along with a 1D vehicle model to predict how the system will age over 40 weeks of operation. The battery is calibrated using experimental data and is capable of predicting performance and aging. It considers aging mechanisms like solid electrolyte interphase (SEI) layer growth, active material isolation (AMI), and SEI cracking. It is also coupled with a lumped thermal model. The 1D vehicle model considers aerodynamic, rolling resistance, driveline inefficiency, motor-inverter losses, battery resistive losses and auxiliaries. The results showed that simulation is over 30000 times
There have been many studies regarding the stability of vehicles following a sudden air loss event in a tire. Previous works have included literature reviews, full-scale vehicle testing, and computer modeling analyses. Some works have validated physics-based computer vehicle simulation models for passenger vehicles and other works have validated models for heavy commercial vehicles. This work describes a study wherein a validated vehicle dynamics computer model has been applied to extrapolate results to higher event speeds that are consistent with travel speeds on contemporary North American highways. This work applies previously validated vehicle dynamics models to study the stability of a five-axle commercial tractor-semitrailer vehicle following a sudden air loss event for a steer axle tire. Further, the work endeavors to understand the analytical tire model for tires that experience a sudden air loss. The studies discussed include executing physics-based vehicle dynamics models at
The tire frictional characteristics, which are the most critical factors of braking performance, depend on the road condition. Unsafe accidents always occur when driving in a hostile environment, especially under snowy road conditions. The coupled dynamic behaviors between the tire and the snow on the road are closely related to the water film generated from the tire rolling on the snow. The winter tire and summer tire with specification 175/65R14 are modeled separately by the finite element method (FEM), and the stiffness characteristics of the winter tire are analyzed. Further, the coupled dynamic model between the tire and the snowy road is built by considering the tire motion effects of the water film. The tires’ friction coefficient is investigated under the straight snowy road with different velocities. It shows that the friction decreases as the velocity increases, and vice versa because the intermediate water film thickness between the tire and snow depends on the tire motion
Tire rolling resistance and temperature are the main parameters for the design and driving of the heavy-duty tires due to their effects on fuel economy and safety. In this paper, the influence of many factors on the tire rollingresistance and temperature is studied, including speed, inflation pressure and normal load; the relationship between rolling resistance properties and temperature of heavy tires is studied based on several experiments to explore the physical mechanism and characteristics of tire rolling resistance for heavy-duty vehicles. The effects of the driving time and temperature of the tire on the rolling resistance are performed on tire’s experimental platform, in which the empirical models involved in the driving time and temperature of the tire for the rolling resistance are established using the least square method for fitting the experimental data. The experimental results demonstrate that the rolling resistance decreases significantly in the first 30 mins, and tends
Low rolling resistance tires are a technology used to improve fuel economy and reduce greenhouse gas emissions in the transportation sector. This project analyzed current relationships between environmental and safety performance properties of commercially available light-duty tire models in Canada. This paper presents the results of a blinded multi-year light-duty vehicle tire research project conducted by Transport Canada & Natural Resources Canada. The study follows on an update to SAE WCX 2018-01-1336 which presented results for tires tested between MY2014-2018. Tire performance was evaluated in a variety of tire categories with a focus on wet grip and rolling resistance. Correlations between key performance indicators were charted to analyze trends in new model tires available on the Canadian tire market. Manufacturer specifications were also charted to evaluate the relations of wet grip and rolling resistance with price, UTQG ratings, and marketing categories. Testing for rolling
SEAT Department of SAIC Motor Vehicle Company starts innovatively applying the single motor and P2.5 configuration scheme from EDU G2(Electric Drive Unit Generation 2), which consists of six engine gears and four motor gears. EDU G2 is very compact and adaptable through the coupling design. Gear coupling make the engine and motor coordination limited, so as to the high efficiency zone of the engine and the high efficiency zone of the motor cannot match in some working conditions, which affect the performance of the vehicle. Therefore, SEAT developed the second generation of single-motor plug-in hybrid system EDU G2 Plus EDU G2(Electric Drive Unit Generation 2 Plus), which realized the decoupling design of 5 engine gears and 2 motor gears, so that the power output of engine and motor is freely. With excellent power and economic performance, the vehicle has been well received by customers. The article mainly describes the system design and development on the themes of motor performance
This paper investigates the impact of tread design on the tire-terrain interaction of two similar-sized truck tires with distinctly different tread designs running over various terrains and operating conditions using advanced computation techniques. The two truck tires used in the research are off-road tires sized 315/80R22.5 wide which were designed through Finite Element Analysis (FEA). The truck tire models were validated in static and dynamic domains using several simulation tests and measured data. The terrain includes a flooded surface and a snowed surface which were modelled using Smoothed-Particle Hydrodynamics (SPH) technique and calibrated using pressure-sinkage and direct shear tests. Both truck tire models were subjected to rolling resistance and cornering tests over the various flooded surface and snowed surface terrain conditions on the PAM-CRASH software. Other tire operating conditions included varying vertical loads, terrain depths, longitudinal speeds, and slip angles
Different tire models are applied in agricultural mobility, but the impacts on the ground are not completely known. Some models of industrial tires, with applications in construction machines, could meet the agricultural demand since there is a shortage offer exclusive models for agriculture. The aim of this research was to analyze in a Fixed Tire Testing Unit (FTTU), under controlled conditions, the performance of two tire types, the first for agricultural construction and the second for industrial construction on two different agricultural soils (two surfaces). The characteristics of the tires evaluated were: 620/75R26 (agricultural tire) and 23.5-25 (industrial tire). The soil used to simulate the agricultural surface were: Red Yellow Latosol and the Distroferric Red Nitosol, chosen because they are representative of agricultural areas in Brazil. The research response variables were soil penetration resistance (Cone Index), deformation caused by tires, real and total contact area
This procedure covers vehicle operation and electric dynamometer (dyno) load coefficient adjustment to simulate track road load within dynamometer inertia and road load simulation capabilities.
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