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Intelligent vehicle-to-everything connectivity is an important development trend in the automotive industry. Among various active safety systems, Autonomous Emergency Braking (AEB) has garnered widespread attention due to its outstanding performance in reducing traffic accidents. AEB effectively avoids or mitigates vehicle collisions through automatic braking, making it a crucial technology in autonomous driving. However, the majority of current AEB safety models exhibit limitations in braking modes and fail to fully consider the overall vehicle stability during braking. To address these issues, this paper proposes an improved AEB control system based on a risk factor (AERF). The upper-level controller introduces the risk factor (RF) and proposes a multi-stage warning/braking control strategy based on preceding vehicle dynamic characteristics, while also calculating the desired acceleration.

Under complex and extreme operating conditions, the road adhesion coefficient emerges as a critical state parameter for tire force analysis and vehicle dynamics control. In contrast to model-based estimation methods, intelligent tire technology enables the real-time feedback of tire-road interaction information to the vehicle control system. This paper proposes an approach that integrates intelligent tire systems with machine learning to acquire precise road adhesion coefficients for vehicles. Firstly, taking into account the driving conditions, sensor selection is conducted to develop an intelligent tire hardware acquisition system based on MEMS (Micro-Electro-Mechanical Systems) three-axis acceleration sensors, utilizing a simplified hardware structure and wireless transmission mode. Secondly, through the collection of real vehicle experiment data on different road surfaces, a dataset is gathered for machine learning training.

In the last decades, the locomotion of wheeled and tracked vehicles on soft soils has been widely investigated due to the large interest in planetary, agricultural, and military applications. The development of a tire-soft soil contact model which accurately represents the micro and macro-scale interactions plays a crucial role for the performance assessment in off-road conditions since vehicle traction and handling are strongly influenced by the soil characteristics. In this framework, the analysis of realistic operative conditions turns out to be a challenging research target. In this research work, a semi-empirical model describing the interaction between a tire and homogeneous and fine-grained soils is developed in Matlab/Simulink. The stress distribution and the resulting forces at the contact patch are based on well-known terramechanics theories, such as pressure-sinkage Bekker’s approach and Mohr-Coulomb’s failure criterion.

As the automotive industry accelerates its virtual engineering capabilities, there is a growing requirement for increased accuracy across a broad range of vehicle simulations. Regarding control system development, utilizing vehicle simulations to conduct ‘pre-tuning’ activities can significantly reduce time and costs. However, achieving an accurate prediction of, e.g., stopping distance, requires accurate tire modeling. The Magic Formula tire model is often used to effectively model the tire response within vehicle dynamics simulations. However, such models often: i) represent the tire driving on sandpaper; and ii) do not accurately capture the transient response over a wide slip range. In this paper, a novel methodology is developed using the MF-Tyre/MF-Swift tire model to enhance the accuracy of ABS braking simulations.

When the aircraft towing operations are carried out in narrow areas such as the hangars or parking aprons, it has a high safety risk for aircraft that the wingtips may collide with the surrounding aircraft or the airport facility. A real-time trajectory prediction method for the towbarless aircraft taxiing system (TLATS) is proposed to evaluate the collision risk based on image recognition. The Yolov7 module is utilized to detect objects and extract the corresponding features. By obtaining information about the configuration of the airplane wing and obstacles in a narrow region, a Long Short-Term Memory (LSTM) encoder-decoder model is utilized to predict future motion trends. In addition, a video dataset containing the motions of various airplane wings in real traction scenarios is constructed for training and testing.

General Motors (GM) is working towards a future world of zero crashes, zero emissions and zero congestion. It’s “Ultium” platform has revolutionized electric vehicle drive units to provide versatile yet thrilling driving experience to the customers. Three variants of traction power inverter modules (TPIMs) including a dual channel inverter configuration are designed in collaboration with LG Magna e-Powertrain (LGM). These TPIMs are integrated with other power electronics components inside Integrated power electronics (IPE) to eliminate redundant high voltage connections and increase power density. The developed power module from LGM has used state-of-the art sintering technology and double-sided cooled structure to achieve industry leading performance and reliability. All the components are engineered with high level of integration skills to utilize across TPIM variants.

Currently, the rapid expansion of the global road transport industry and the imperative to reduce carbon emissions are propelling the advancement of electrified highways (EH). In order to conduct a comprehensive economic analysis of EH, it is crucial to develop a detailed /8.and comprehensive economic model that takes into account various transportation modes and factors that influence the economy. However, the existing economic models for EH lack comprehensiveness in terms of considering different transportation modes and economic factors. This study aims to fill this gap by designing an economic model for an EH-based Online DC-driven system (ODS) for long distance heavy-duty transport vehicle incorporating multi-factor sensitivities. Firstly, the performance parameters of the key components of the system are calculated using vehicle dynamics equations which involves selecting and matching the relevant components and determining the fundamental cost of vehicle transformation.

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.

The experimental control findings of increasing the handling performance so that the yaw motion of the vehicle is nimble and stable utilizing the upgraded rear wheel steering system equipped with dual-link actuators are shown in this work. In most automobiles, the steering axis is well defined in front suspension. However, unless the vehicle's rear suspension is a sort of double wishbone, the steering axis is not clearly defined in regular multi-link rear suspensions. As a result, most current automobiles have a suspension geometry feature in which the camber and toe angles change at the same time when the assist link is changed to steer the back wheels. To create lateral force from the rear tire while preserving maximum tire grip, the dual-link actuators control for modifying the strokes of suspension links must keep the camber angle constant and adjust only the toe angle.

Symbolic code execution is a powerful cybersecurity testing approach that facilitates the systematic exploration of all paths within a program to uncover previously unknown cybersecurity vulnerabilities. This is achieved through a Satisfiability Modulo Theory (SMT) solver, which operates on symbolic values for program inputs instead of using their concrete counterparts. However, in complex code bases, this approach faces significant limitations, such as program path explosions or unavailable dependencies, which can result in conditions that the SMT solver cannot reason about. Consequently, SMT solvers are often considered as too costly to implement for automotive testing use cases and are rarely employed within this domain. In contrast, fuzz testing has recently gained traction in the automotive industry as an invaluable testing technique for identifying previously unknown vulnerabilities. Its initial setup is straightforward and typically yields useful findings.

Wound rotor synchronous machines (WRSM) without rare-earth magnets are becoming more popular for traction applications, but their potential in drive performance has not yet been fully explored. This paper presents a Pulse Width Modulation (PWM) scheme optimization procedure to minimize motor and inverter losses. It leverages different PWM schemes with different PWM switching strategies and switching frequencies. First, a generic PWM-induced motor loss calculation tool developed by BorgWarner is introduced. This tool iteratively calculates motor losses with PWM inputs across the entire operating map, significantly improving motor loss prediction accuracy. The inverter losses are then calculated analytically using motor and wide-bandgap (WBG) switching device characteristics. By quantifying these various scenarios, the optimal PWM scheme for achieving the best system efficiency across the entire operating map is obtained.

The aim of this study is to determine if the degradation of one or more dampers of a passenger car with ABS leads to a statistically significant reduction of vehicle safety. Therefore, a compact and a mid-size car are tested on a flat test track and on an uneven test track by straight braking maneuvers at different levels of damper degradation. Both test tracks are scanned using a 3D laser scanner. For every level of damper degradation (on each test track) a new set of tires is used, a preconditioning routine is applied and 30 successful measurements are conducted to allow using statistical methods to evaluate the results. The results show that any level of damper degradation with each type of car and test track leads to a significant increase in braking distance and, therefore, to a significant reduction of vehicle safety. The braking distance extension varies heavily with the level of damper degradation and the road properties.

Disc brakes are the most popular type of brakes used in the two-wheeler segment and are easily available in the market. The improper brakes result in serious problems in vehicles. The main idea of this paper is to design a braking system for a two-wheeler application. The paper discusses the design, analysis, and simulation of disc brakes. The disc is first selected using the standard brake disc calculation. To verify the selection of disk, torque at wheel and torque at the disc are compared. Thermomechanical (Transient) analysis is done on ANSYS 2021 to check for the effect of braking force applied by the disc on the rotor disc. The mathematical model of the ABS model is done on Scilab Xcos. The main aim of studying the system using a mathematical model is to verify if the selected disc brakes are safe enough to be installed on a two-wheeler. The mathematical model also has stopping distance and the stopping time as the output which validates the selection of the disc.

In the quest for sustainable materials for automotive interior trim, jute fiber is gaining traction due to its characteristics, which align with other renowned natural fibers. This study aimed to assess the efficacy of sodium bicarbonate as a treatment for jute fibers in comparison to conventional alkaline treatments. Both treated and untreated fibers were examined. Results showed that alkali-processed fibers demonstrated enhanced crystallization, thermal resistance, and surface quality relative to untreated ones. Specifically, alkali-treated jute fibers exhibited a degradation onset at 261.23°C, while those treated with sodium bicarbonate began degrading at 246.32°C. Untreated fibers had a degradation onset at 239.25°C. Although both treatments improved the thermal stability of the fiber, sodium bicarbonate processing, while beneficial, was slightly less effective than the traditional alkaline method.

For any two wheeler vehicle development, rider and pillion comfort while driving the vehicles over different kinds of road perturbations holds high importance. Designing a vehicle for comfort starts at the very beginning of its layout definition through vehicle geometric parameters, key hardpoints, mass-inertia distribution of subsystems and suspension characteristics. There is a need for highly reliable simulation models for comfort predictions as any change in layout during subsequent design stages is a very costly affair. Accurately predicting comfort using a full vehicle model is a challenging task though as it depends on how realistic the Simulation Model is to that of actual vehicle. While suspension stiffness and damping characteristics remain critical parameters for the comfort, selection of tyres are known to hold equal importance in vehicle comfort.

India is one of the largest markets for the automobile sector and considering the trends of road fatalities and injuries related to road accidents, it is pertinent to continuously review the safety regulations and introduce standards which promise enhanced safety. With this objective, various Advanced Driver Assistance Systems (ADAS) regulations are proposed to be introduced in the Indian market. ADAS such as, Anti-lock Braking Systems, Advanced Emergency Braking systems, Lane Departure Warning Systems, Auto Lane Correction Systems, Driver Drowsiness Monitoring Systems, etc., assist the driver during driving. They tend to reduce road accidents and related fatalities by their advanced and artificial intelligent fed programs. This paper will share an insight on the past, recent trends and the upcoming developments in the regulation domain with respect to safety.

An Inertial Measurement Unit (IMU) provides vehicle acceleration that can be used in Active Vehicle Safety Systems (AVSSs). However, the signal output from an IMU is affected by changes in its position in the vehicle and alignment, which may lead to degradation in AVSS performance. Investigators have employed physics and data-based models for countering the impact of sensor misalignment, and the effects of gravity on acceleration measurements. While physics-based methods utilize parameters varying dynamically with vehicle motion, data-based methods require an extensive number of parameters making them computationally expensive. These factors make the above-explored methods practically challenging to implement on production vehicles. This study considers a 6-axis IMU and evaluates its impact on Antilock Braking System (ABS) performance by considering the IMU signal obtained with different mounting orientations, and positions on a Heavy Commercial Road Vehicle (HCRV).

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.

Permanent Magnet Synchronous Motor (PMSM) is a favorite choice for traction applications because of their high power-to-weight ratio, torque-to-current ratio, high efficiency. In PMSM motors to perform the electronic commutation, resolvers are required to detect the rotor position. Resolvers are placed nearer to the end windings of the stator by considering the Mechanical Assembly and interfacing aspects. In high-power traction applications, due to higher current, there will be a significant influence of electric fields (E-fields) and electromagnetic fields (B-fields) on the rotor position sensor due to overhang components. The magnetic field induced by end-winding changes the excitation field, the magnitude of which decides the rotor angular position. This distortion of the excitation field will impact the sensing position and performance of the resolver.

An accurate estimate of vehicle speed is essential for optimal anti-lock braking system (ABS) calculations. Currently, most vehicles including heavy-duty class 8 trucks mainly rely on wheel speed sensors (WSS) to estimate velocity. However, as soon as braking is applied, WSS become inaccurate for determining the velocity due to the longitudinal slip developed in the tires. Using the inertial measurement unit (IMU) to estimate vehicle speed allows for its use in conjunction with the WSS to accurately calculate the slip ratio at each tire. These slip ratio values can then be used as the main control variable in the ABS algorithm to utilize the grip available more fully at each tire, to improve stopping distance and controllability. A steady state braking analysis model is developed and validated against Federal Motor Vehicle Safety Standards (FMVSS) 121 60-0 mph stopping distance data for a loaded class 8 tractor semi-trailer combination.