Tire Locations Research Articles

Cost/Performance Analysis of Battery Pack placed in Spare Tire Area for Extending the Range of Hybrid, and Electric Vehicles

Recently, electric vehicles have been an alternative form of transportation promising a bright future as sales figures are increasing rapidly beyond expectations. In the near fu-ture, electric vehicles are expected to dominate the market with numerous advantages over vehicles with internal combustion engines. The hybrid electric vehicles are often con-sidered a transition between the two due to added advantages of both models. Out of hy-brid models, plugin hybrid vehicles have more resemblance to the fully electric vehicles because of longer electric range and lower cost per mile. This paper investigates the use of the spare tire location to convert an existing battery pack or to install a new battery pack for a hybrid vehicle. Cost and range calculations are performed based on two most com-monly sold vehicles that use 16”, 17” and 18” size tires. Resulting battery packs are demonstrated through various battery dimensions and chemistries. Results are provided with cost and environmental benefits of utilizing an electric power for driving.

A Machine Learning–Based Tire Life Prediction Framework for Increasing Life of Commercial Vehicle Tires

Abstract In the commercial freight industry, tire retreading decisions are often conservative due to limited knowledge of a tire’s remaining service life. This practice leads to increased costs and material waste. This paper proposes a machine learning–based approach for estimating tire casing life and retreadability, focusing on usage data rather than wear information. This approach could extend the tire’s lifespan and reduce landfill waste. Data integration from diverse tire casing measurement sources presents challenges, including imbalanced removal data. Our methodology addresses these challenges by using historical inspection, telematics, and finite element modeling (FEM) datasets. We introduce “Tire Casing Energy” as a comprehensive usage input and apply a Variance-Reduction Synthetic Minority Oversampling Technique (VR-SMOTE) for data imbalance rectification. A random forest model is used to estimate the state of the tire casing and the casing removal probability, with Bayesian optimization applied for hyperparameter tuning, enhancing model accuracy. The proposed prediction framework is able to differentiate different truck fleets and tire locations based on their usage parameters. With the aid of this machine learning model, the importance and sensitivity of different tire usage parameters can be obtained, which is beneficial to maximize tire life.

Computationally Efficient Modeling of Lightweight Expeditionary Airfield Surfacing Systems at Large Length Scales

Expeditionary airfield matting systems are lightweight, portable surfaces that enable the rapid deployment of infrastructure to support aircraft operations. Individual matting components are assembled via interlocking joints to construct arrays that serve as temporary aircraft operating surfaces. The paper outlines the homogenization of the AM2 portable airfield matting system and its interlocking mechanisms to permit computationally efficient analyses toward understanding mechanisms that influence the global behavior of these arrays and underlying subgrade during aircraft maneuvers. An equivalent orthotropic two-dimensional continuum was developed from finite element analysis of a detailed three-dimensional model and its flexural behavior was validated against experimental data and solid finite element models. Interlocking joints were characterized using node-to-node connector elements based on subscale finite element studies. Both components were implemented into a full-scale model representative of a typical test section, and responses to static high tire pressure aircraft loads were analyzed over a soil foundation representing a California bearing ratio of 6%, yielding promising agreement with experimental data. Results of this study reveal an inherent coupling between load transfer, mat deflection, and near-surface subgrade stress with dependence on tire location, mat core shear flexibility, and joint stiffness.

R(refracted)-PIV measurements of water film flow: application to flow under a rolling tire

An analysis of the water flow generated by a tire rolling over a water film has been carried out on an experimental level. The present investigation is focused on a commercial tire with a winter V-shaped complex sculpture. Flow measurements were performed using an optical technique derived from the standard 2D-PIV, the so-called r(refracted)-PIV. Some specific image processing tools have been developed in order to take into account the jitter of the tire location inside the camera field of view when analyzing a set of independent runs. Considering the analysis of the flow either inside the grooves or in front of the tire, different approaches are proposed. On one hand, a geometrical segmentation of the grooves allows a flow analysis inside these tread elements. A characteristic water velocity deduced from measurements performed over a set of independent runs appears to correlate with the position of the segment under consideration along the contact patch area. It has been considered as the hydrodynamic signature of the present tread design. On the other hand, inside the water-bank in front of the tire, an ensemble averaging process of the local velocity is performed to show the influence of groove presence at small scale and the impact of tread design at large scale.Graphical abstract

Road profile estimation and half-car model identification through the automated processing of smartphone data

This paper proposes a robust road profile estimation method and vehicle parameter identification method through an optimization with an objective function and constraint conditions on estimated profiles. The methods require only vehicle response measurements, enabling easy and inexpensive, yet effective, road condition monitoring through the automated processing of smartphone data. A half-car (HC) model, representing both bouncing and pitching motions, is employed for the profile estimation. The road profiles at the front and rear tire locations are included as state variables in the augmented state vector and are estimated by combining the augmented Kalman filter (AKF), Robbins–Monro (RM) algorithm, and Rauch–Tung–Striebel (RTS) smoothing. The two independent state variables, however, correspond to a single physical profile, while their distance coordinates differ by the wheelbase. Therefore, the vehicle parameters are optimized through the minimization of the difference between the identified road profiles at the front and rear tire locations using a genetic algorithm. Three objective functions and three constraint conditions are proposed to automatically select the best vehicle parameters. With this HC model, the road profile is subsequently estimated by combining the AKF, RM, and RTS methods. Through numerical simulations, the accuracy of the profile estimation and validity of the parameter identification are clarified. The influences of different drive speeds and difference between the left and the right profiles are numerically investigated. Drive tests with three different vehicles and a reference laser profiler show that the algorithm can automatically compensate for differences among vehicles with different drive speeds and estimate profiles accurately.

Extraction of bridge fundamental frequency from estimated vehicle excitation through a particle filter approach

A bridge's natural frequencies are important dynamic properties reflecting the structural condition of the bridge. Numerous studies have been conducted in the field to extract a bridge's natural frequencies from responses of passing vehicles. The bridge frequency peaks are, however, not easily observed, because pavement roughness often influences the spectra of vehicle responses. In this research, a method that extracts the fundamental frequency of a bridge from the responses of an ordinary vehicle with its parameters calibrated in advance is proposed. The method is based on the idea that the vehicle passing across a bridge is excited by two sources, i.e., pavement roughness and bridge vibration. The excitation inputs to the vehicle, i.e., displacement inputs at the front and rear tire locations, are estimated from vehicle responses using a particle filter method. The estimated displacement inputs at the front and rear tires are then subtracted from each other after shifting by a wheel–base distance to eliminate the roughness influence, which commonly appears in both signals. The signal after the subtraction contains only the bridge vibration influence and is used to extract the fundamental frequency of the bridge. This indirect method of bridge frequency extraction is investigated through numerical simulations. A field measurement was also conducted, and it showed that the bridge's fundamental frequency was successfully extracted with a good accuracy for several driving-speed cases.

FE-DEM with interchangeable modeling for off-road tire traction analysis

This study examines a new finite element/discrete element method (FE-DEM) with interchangeable modeling between FEM and DEM for tire traction analysis. In the method, named iFE-DEM, the soil in a soil bin is modeled initially by FEM except for the region under or near the tire, which is modeled using DEM. When the FEM tire model starts to travel over DEM soil elements, the updated tire location will activate new conversion of modeling from FEM to DEM so that the zone of influence around the contact interface between tire and soil can be analyzed continuously using DEM. Those mobilized DEM elements rearward of the tire might be converted again to FEM elements by assuming that the effect of the stress state in DEM generated by tire travel might be negligible. The computational time for two-dimensional iFE-DEM analysis of a slip of 40% using the smallest region of initial DEM under the tire could be reduced to 23% of that obtained using DEM only soil modeling.

A Statistical Study of Tire Pressures on Road Going Vehicles

Published information on studies of something so critical to safety as passenger vehicle tire pressures can be found [1, 2]; however, they only account for rolling tires. Studies related to spare tire pressures are lacking. This paper is the result of measurements on 150+ vehicles and the most surprising results are presented regarding the influence of Tire Pressure Monitoring Systems (TPMS) and the new spare tire locations and use. A statistical study was performed on the collected data to determine the correlation between tire pressures, vehicle age and TPMS. One particular topic of investigation was the relationship between various factors that influence spare tire pressure. Some newer models, particularly some mini-vans, have placed the spare tire in an unusual and inconvenient place for regular maintenance. Based on the data collected, TPMS has a positive influence on rolling tires but not on spare tires. The results support the need for TPMS to also monitor spare tire pressures. Language: en

Larval mosquito communities in discarded vehicle tires in a forested and unforested site: detritus type, amount, and water nutrient differences

Discarded tires are an important habitat for larvae of multiple species of disease-transmitting mosquitoes. Although tire locations likely influence composition and abundance of vectors, there are few data linking vector populations to the characteristics of the aquatic tire environment. We sampled water-filled tires at three times at a forested and an unforested site to evaluate how differences in detritus inputs or nutrients in these two macrohabitats may be associated with composition of mosquito-dominated invertebrate communities. The forested site had significantly greater inputs of leaves, twigs, seeds, and fine detritus at the first sampling, but subsequent sampling indicated no differences in inputs of any detritus type. Total phosphorous levels were significantly greater in the forested site, but there was no difference in total nitrogen or total ion concentrations during any sampling. Chlorophyll a levels were not different between sites, even though light levels were greater and canopy cover was less at the unforested site. Culex restuans dominated at the unforested site, and Ochlerotatus triseriatus, Anopheles barberi, and Orthopodomyia signifera were found primarily in the forest. Tires at the forested site had significantly more species but not more individuals than at the unforested site. Leaf amount was a good predictor of densities of Oc. triseriatus and overall abundance of mosquitoes in the forest, whereas the amount of seeds was a good predictor of overall invertebrate richness and of Oc. triseriatus numbers in the unforested site. Differences in mosquito assemblage composition between forested and unforested locations may be explained by greater inputs of plant-based detritus and some nutrients, but other factors, such as macrohabitat or host preferences of adult mosquitoes, also may be important.

Biology of Aedes triseriatus (Diptera: Culicidae) developing in tires in Louisiana.

Aedes triseriatus (Say) pupae and host-seeking females were collected over 19 wk in a tire dump located in southwestern Louisiana. Tire location influenced production of mosquitoes, sex ratio, and body size of adults. Tires located in a wooded area of the dump produced 3.6 times more adult Ae. triseriatus than did tires in the sun. However, tires in the sun produced mosquitoes with significantly longer wings than did tires in shade. Also, average wing length of females in shaded tires increased significantly later in the summer. Average wing length of host-seeking parous females was significantly greater than nulliparous host-seeking females, and average wing lengths of both host-seeking populations were significantly greater than that of emerging females. Thus, body size was related to survival and blood-feeding success in Ae. triseriatus .