Journal Articles - SAE Mobilus

SAE journals provide rigorously peer-reviewed, archival research by subject matter experts--basic and applied research that is valuable to both academia and industry.

Items (10,602)

A Comprehensive Review of Vehicle and Road Condition Estimation Techniques

10-09-02-0014

04/30/2025

This article reviews the key physical parameters that need to be estimated and identified during vehicle operation, focusing on two key areas: vehicle state estimation and road condition identification. In the vehicle state estimation section, parameters such as longitudinal vehicle speed, sideslip angle, and roll angle are discussed, which are critical for accurately monitoring road conditions and implementing advanced vehicle control systems. On the other hand, the road condition identification section focuses on methods for estimating the tire–road friction coefficient (TRFC), road roughness, and road gradient. The article first reviews a variety of methods for estimating TRFC, ranging from direct sensor measurements to complex models based on vehicle dynamics. Regarding road roughness estimation, the article analyzes traditional methods and emerging data-driven approaches, focusing on their impact on vehicle performance and passenger comfort. In the section on road gradient

Chen, Zixuan, Duan, Yupeng, Wu, Jinglai, Zhang, Yunqing

Influence of Exhaust Gas Recirculation on Knock in a Spark Ignition Engine Fueled with Ethanol–Gasoline Blends

03-18-03-0019

04/28/2025

Exhaust gas recirculation (EGR) is widely used in spark ignition engines to reduce throttling losses, decrease exhaust gas temperatures, increase efficiency, and suppress knock. However, the effectiveness of EGR as a knock suppressor is dependent on the fuel type and operating condition. In this study, the effectiveness of EGR to suppress knock was tested with E10, E30, E50, E75, and E100 at a moderately boosted condition. It was found that EGR was effective at suppressing knock with E10, but high EGR rates were required to achieve a knock suppression effect with E30 and E50. No knock suppression effect was observed with E75 and E100 across all tested EGR rates. With E30 and E50, EGR that was passed through a three-way catalyst was more effective at suppressing knock at all EGR rates. Chemkin modeling with neat ethanol revealed that nitric oxide enhanced ignition by increasing the hydroxyl radical concentration in the end gas, resulting in earlier auto-ignition. Directly seeding nitric

Gandolfo, John, Gainey, Brian, Lawler, Benjamin

Damping and Vibration Characteristics of Carbon Fiber Sandwich Beams with Corrugated Cores

05-19-01-0005

04/26/2025

Composite sandwich beams are widely favored for their high strength-to-weight ratio, so understanding their vibration characteristics is important for optimizing designs in critical industries. This study investigates, through experimental and statistical analyses, the impact of core geometry on the vibration characteristics of epoxy/carbon fiber composite sandwich beams featuring sinusoidal and trapezoidal cores. Modal tests were conducted to determine natural frequencies, damping ratios, and mode shapes. The height and angle of the cores were treated as key independent factors influencing the beams’ vibration characteristics. In both of the cores the damping ratio values increased about 25% and 35% with increasing the height and angle of the sinusoidal and trapezoidal cores, respectively. Additionally, response surface methodology (RSM) was used for statistical analysis of these input parameters’ effects on damping properties, and the optimal values of core’s geometries were

Alwan, Majeed A., Abbood, Ahmed Sh., Farhan, Arkan J., Azadi, Reza

Effect of Moisture Content and Salinity on Impact Strengths of Glass-Reinforced Plastics and Aluminum Honeycomb Sandwich Composites: An Experimental Investigation

05-19-01-0001

04/26/2025

Polymer composites, such as fiber-reinforced plastics (FRPs), are widely used in shipbuilding, aerospace, and automobile industries due to their lightweight and high strengths. In real-world conditions, ship hulls are exposed to harsh environmental factors, including variations in moisture and salinity. FRPs tend to absorb water and moisture, leading to an increase in weight and a reduction in strengths over time, which is undesirable for ship and aircraft structures. This study investigates the reduction in energy absorption and specific energy absorption of glass FRPs (GFRP) and aluminum honeycomb sandwich composites (AHSC) due to exposure to moisture and salinity. Experimental analysis was conducted by immersing the materials in saline and non-saline water. A comparative assessment of the percentage reduction in specific energy absorption (SEA) of GFRP and AHSC is presented. Additionally, the influence of honeycomb parameters such as cell size (CS), foil thickness (FT), and core

Rajput, Arun, Kumar, Ashwin, Sunny, Mohhamed Rabius, Chavhan, Harikrishna

Development of an Imperceptible Brake Failure Control Technology and Real Vehicle Application

10-09-02-0015

04/26/2025

With the advancement of control technology in the automotive field, there is a possibility of cross-system redundant control between various actuators. As for the braking system, current brake-by-wire system often uses mechanical backup braking methods to give the vehicle a certain braking capacity after failure. However, in the mechanical backup braking mode, the brake master cylinder is connected to the supporting wheel cylinder, and the brake assist is lost, which leads to an increase in brake pressure and makes it difficult for the driver to step on the brake pedal. Meanwhile, due to the limitation of the brake master cylinder stroke, the maximum braking deceleration of the vehicle is only 3 m/s2 after the driver fully presses the brake pedal. The above two defects greatly affect the safety of the vehicle during backup braking. To solve the above problems, this article takes electric vehicles as the research object, designs a new type of hydraulic circuit for the braking system

Tian, Boshi, Li, Liang, Liao, Yinsheng, Lv, Haijun, Hu, Zhiming, Sun, Yue, Qu, Wenying

Experimental and Numerical Study on Ballistic Testing and Failure Mechanism of Ultra-High Hard and Rolled Homogeneous Armor Steels

05-19-01-0003

04/25/2025

The escalating weight of main battle tanks (MBTs) has compelled designers to innovate with Ultra-high hard armor (UHA) steel against the current generation rolled homogenous armor (RHA). This study delves into investigating the experimental and numerical ballistic performance of 15 mm–thick UHA steel and 15 mm–thick RHA steel against a 7.62 mm armor-piercing (AP) small-arm projectile. Finite element (FE) simulations were executed using ANSYS software, incorporating the Johnsons Cook model and shock Rankine–Hugoniot equations. The outcomes highlight that the UHA steel arrests the projectile’s advancement at a depth of penetration (DoP) of 3 mm, where the mode of failure is projectile break-up with cleavage failure. Conversely, the RHA base metal demonstrates perforation accompanied by ductile hole growth as the mode of failure. This perforation is attributed to plastic deformation and material extrusion, aligning well with the FE model. In the second scenario, the ballistic limit of a

Naveen Kumar, Subramani, Balasubramanian, V., Malarvizhi, S., Sonar, Tushar, Hafeezur Rahman, A., Balaguru, V.

Influence of Coolant Properties on Battery Thermal Management in Electric Buses during Cold Starts

02-18-03-0013

04/25/2025

Improving electric vehicles’ overall thermal management strategy can directly or indirectly improve battery efficiency and vehicle range [1]. In this study, the effect of the coolant type used in BTMS (battery thermal management system) units used for heating batteries in cold weather conditions was investigated in electric buses. In this investigation, tests were performed with two types of antifreeze, which have different characteristics. The study evaluated the impact of coolant flow, BTMS circulation pump performance, and battery heating using these two types of antifreeze in the BTMS coolant line. In addition to carrying out tests, 1D computational fluid dynamics models’ simulations were carried out for both types of antifreeze, and the results were validated with experimental findings. In this study, a 12-m EV Citivolt vehicle of Anadolu Isuzu was used for tests. As a result, it was observed that differences in the properties of the antifreeze that is used in BTMS coolant line

Çetir, Özgür, Birgül, Çağrı Emre

Traffic Flow Prediction Based on the Optuna–CNN–BiLSTM–GBRT Model

12-09-01-0001

04/24/2025

Abstract Traffic flow prediction is very important in traffic-related fields, and increasing prediction accuracy is the primary goal of traffic prediction research. This study proposes a new traffic flow prediction method, which uses the CNN–BiLSTM model to extract features from traffic data, further models these features through GBRT, and uses Optuna to tune important hyperparameters of the overall model. The main contribution of this study is to propose a new combination model with better performance. The model integrates two deep learning models that are widely used in this field and creatively uses GBRT to process the output features of the front-end model. On this basis, the optimal hyperparameters and the robustness of the model are deeply explored, providing an effective and feasible solution to the difficult problems in traffic flow prediction. This model is experimentally studied using three different data transformation methods (original data, wavelet transform, Fourier

Ma, Changxi, Jin, Renzhe

Cross-Scene Traffic Target Detection and Recognition Based on Improver YOLOv5s

12-09-01-0003

04/24/2025

Abstract Aiming at the problem of insufficient cross-scene detection performance of current traffic target detection and recognition algorithms in automatic driving, we proposed an improved cross-scene traffic target detection and recognition algorithm based on YOLOv5s. First, the loss function CIoU of insufficient penalty term in the YOLOv5s algorithm is adjusted to the more effective EIoU. Then, the context enhancement module (CAM) replaces the original SPPF module to improve feature detection and extraction. Finally, the global attention mechanism GCB is integrated with the traditional C3 module to become a new C3GCB module, which works cooperatively with the CAM module. The improved YOLOv5s algorithm was verified in KITTI, BDD100K, and self-built datasets. The results show that the average accuracy of mAP@0.5 is divided into 95.1%, 72.2%, and 97.5%, respectively, which are 0.6%, 2.1%, and 0.6% higher than that of YOLOv5s. Therefore, it shows that the improved algorithm has better

Ning, Qianjia, Zhang, Huanhuan, Cheng, Kehan

A Novel Model for Short-Term Traffic Flow Prediction on Highways Utilizing Multi-Head Attention–BiLSTM–BiGRU

12-09-01-0002

04/24/2025

Abstract With the development of intelligent transportation systems and the increasing demand for transportation, traffic congestion on highways has become more prominent. So accurate short-term traffic flow prediction on these highways is exceedingly crucial. However, because of the complexity, nonlinearity, and randomness of highway traffic flows, short-term prediction of its flows can be difficult to achieve the desired accuracy and robustness. This article presents a novel architectural model that harmoniously fuses bidirectional long–short-term memory (BiLSTM), bidirectional gated recurrent unit (BiGRU), and multi-head attention (MHA) components. Bayesian optimization (BO) is also used to determine the optimal set of hyperparameters. Based on the PeMS04 dataset from California, USA, we evaluated the performance of the proposed model across various prediction intervals and found that it performs best within a 5-min prediction interval. In addition, we have conducted comparison and

Chen, Peng, Wang, Tao, Ma, Changxi, Chen, Jun

Research on the Influence of Door and Window Sealing on Interior Wind Noise Based on Statistical Energy Analysis

10-09-03-0026

04/24/2025

Wind noise is an important indicator for evaluating cabin comfort, and it is essential to accurately predict the wind noise inside the vehicle. In the early stage of automotive design, since the geometry and properties of the sealing strip are often unknown, the contribution of the sealing strip to the wind noise is often directly ignored, which makes the wind noise obtained through simulation in the pre-design stage to be lower than the real value. To investigate the effect of each seal on wind noise, an SUV model was used to simulate the cases of not adding body seals, adding window seals, and further adding door seals, respectively. The contribution of each seal to wind noise was obtained and verified by comparing it with the test results. The influence of the cavity formed at the door seal was also addressed. In the simulations, a CFD solver based on the lattice Boltzmann method (LBM) was used to solve the external flow field, and the noise transmitted into the interior of the

Zhang, Yingchao, He, Tengsheng, Wang, Yuqi, Niu, Jiqiang, Zhang, Zhe, Shen, Chun, Zhang, Chengchun

Aerated Oil in the Rotating Channel

03-18-03-0018

04/24/2025

In this article we examine the behavior of oil in the lubrication channel between the main bearing and the connecting rod bearing in the crankshaft of an internal combustion engine. The requirement for high service life and proper operation of these bearings, while minimizing input power of the lubrication system, lead to the need to understand the function of these structural parts in detail. To simulate and visualize this process, an experimental device was created. The device allows the experimenters to change individual parameters such as rotation speed, oil pressure, oil temperature, and aeration, while simultaneously visualizing the process with the help of a special rotating camera. These parameters are then obtained by image processing. In this way, the following influences are investigated here: at oil temperatures of 30, 50, and 80°C, relative oil pressures of 1, 2, 3, and 4 bar, at undissolved air in the oil of 5 and 10 vol% and crankshaft station speeds from 0 to 6000 1/min

Rychtar, Vaclav

Advancements in Lightning Strike Damage Modeling: Finite Element Model to Predict Thermal Damage Induced on Composites

01-18-02-0007

04/21/2025

Modern aircraft, ships, and offshore structures are increasingly constructed using fiber-reinforced composite materials. However, when subjected to lightning strikes, these materials can suffer significant structural and functional damage due to their electrical and thermal properties. This study aims to develop a novel finite element (FE) model to minimize the error in estimating the thermal damage caused during lightning strikes. This will aid in design and optimization of lightning protection systems. The developed model introduces a simplified numerical approach to model the lightning arc interaction with CFRP laminate. The existing FE model includes idealized loading conditions, leading to high error in estimation of severe damage area and in-depth damage. The proposed methodology incorporates a more realistic lightning-induced loading pattern to improve accuracy. Several cases are analyzed using available FE methods and compared to the proposed model (case 6) to evaluate the

Sontakkey, Akshay, Kotambkar, Mangesh, Kaware, Kiran

TOC

99-07-02-0TOC

04/17/2025

TOC

Tobolski, Sue

Development of a Robust Framework for Fault Detection and Quantification in Automotive Drum Brakes Using Vibration Measurements and ANN

10-09-03-0024

04/15/2025

Passenger safety is of utmost importance in the automotive industry. Hence, the health of the components, especially the brake system, should be effectively monitored. On account of the significance of artificial intelligence in recent times, any brake fault resulting during operation can be accurately detected using a combination of advanced measurement techniques and machine learning algorithms. The current study focuses on developing and evaluating a robust framework to quantify and classify the faults of a general automotive drum brake. For this purpose, a new experiment for a drum brake, which can be operated under a controlled environment with known levels of faults, is developed. The experiment is instrumented to measure the fundamental dynamic signals (such as brake torque, the angular velocity of the brake drum, and brake shoe accelerations) during a braking event. The response signals from several experiments with various faults and operating conditions serve as the input

Yella, Akash, Bharinikala, Yuva Venkat Ajay, Sundar, Sriram

Learned Human Eye Gaze for Object Tracking: A Preliminary Study

09-13-01-0004

04/15/2025

Visual object tracking technology is the core foundation of intelligent driving, video surveillance, human–computer interaction, and the like. Inspired by the mechanism of human eye gaze, a new correlation filter (CF) tracking algorithm, named human eye gaze (HEG) tracking algorithm, was proposed in this study. The HEG tracking algorithm expanded the tracking detection idea from the traditional detection-tracking to detection-judging-tracking by adding a judging module to check the initial and retrack the unreliable tracking result. In addition, the detection module was further integrated into the edge contour feature on the basis of the HOG (histogram of oriented gradients) extracting feature and the color histogram to reduce the sensitivity of the algorithm to factors such as deformation and illumination changes. The comparison conducted on the OTB-2015 dataset showed that the overall overlap precision, distance precision, and center location error of the HEG tracking algorithm were

Jiang, Yejie, Jiang, Binhui, Chou, Clifford C.

Used Motor Oil Regeneration Efficiency of Type X Fly Ash–Based Zeolite Alone and Combined with Other Adsorbents

04-18-03-0013

04/15/2025

This research article assesses the used motor oil’s (UMO) regeneration efficiency of a synthetic type X zeolite (siliceous fly ash–based) alone and combined with other adsorbents (composite adsorbents), namely activated carbon, bentonite, and acid-activated bentonite from Goshica’s (Kosovo) region. The UMO treated with the regenerating mixes has run about 20,000 km. Parameters including density, kinematic viscosity, viscosity index, pour point, and sulfur content were measured in the untreated and treated UMO and compared to those of the reference oil with additives of type SAE 5W-30. All regeneration mixes showed good regeneration efficiency, restoring the UMO’s parameters to almost the original ones of the reference oil with additives (SAE 5W-30). Only the zeolite alone could significantly reduce the sulfur content (removal efficiency 60%). This method deserves further investigation and with some improvements, it can be established as a reliable regeneration method for some UMO.

Korpa, Arjan, Dervishi, Sara, Gecaj, Diana, Shahu, Kristi, Shehu, Alma, Nuro, Aurel

Predicting Real-time Crash Risks during Hurricane Evacuation Using Connected Vehicle Data

09-13-01-0006

04/12/2025

Hurricane evacuations generate high traffic demand with increased crash risk. To mitigate such risk, transportation agencies can adopt high-resolution vehicle data to predict real-time crash risks. Previous crash risk prediction models mainly used limited infrastructure sensor data without covering many road segments. In this article, we present methods to determine potential crash risks during hurricane evacuation from an emerging alternative data source known as connected vehicle data that contain vehicle speed and acceleration information collected at a high frequency (mean = 14.32, standard deviation = 6.82 s). The dataset was extracted from a database of connected vehicle data for the evacuation period of Hurricane Ida on Interstate-10 in Louisiana. Five machine learning models were trained considering weather features and different traffic characteristics extracted from the connected vehicle data. The results indicate that the Gaussian process boosting and extreme gradient

Syed, Zaheen E Muktadi, Hasan, Samiul

Adapting Basic On-Road Data to the Heavy Heavy-Duty Diesel Truck Schedule for Guiding the Electrification of Long-Haul Truck Transport

14-14-02-0011

04/10/2025

Heavy heavy-duty diesel truck (HHDDT) drive cycles for long-haul transport trucks were developed over 20 years ago and have a renewed relevance for performance assessment and technical forecasting for transport electrification. In this study, a model was constructed from sparse data recorded from the real-life on-road activity of a small fleet of class 8 trucks by fitting them into separate driving-type segments constituting the complete HHDDT drive cycle. Detailed 1-s resolution truck fleet raw data were also available for assessing the drive cycle model. Numerical simulations were conducted to assess the model for trucks powered by both 1.0 MW charging and 300 kW-level e-Highway, accounting for elevation and seasonally varying climate conditions along the Windsor–Quebec City corridor in Canada. The modeling approach was able to estimate highway cruising speeds, energy efficiencies, and battery pack lifetimes normally within 2% of values determined using the detailed high-resolution

Darcovich, Ken, Ribberink, Hajo, Soufflet, Emilie, Lauras, Gaspard

Detecting Piston Ring–Cylinder Liner Metal–Metal Contact in a Fired Large Marine Diesel Engine Using Piezoelectric Transducers

03-18-03-0017

04/09/2025

Shear-polarized ultrasonic sensors have been instrumented onto the outer liner surface of an RTX-6 large marine diesel engine. The sensors were aligned with the first piston ring at top dead center and shear ultrasonic reflectometry (comparing the variation in the reflected ultrasonic waves) was used to infer metal–metal contact between the piston ring and cylinder liner. This is possible as shear waves are not supported by fluids and will only transmit across solid-to-solid interfaces. Therefore, a sharp change in the reflected wave is an indicator of oil film breakdown. Two lubricant injection systems have been evaluated—pulse jet and needle lift-type injectors. The needle lift type is a prototype injector design with a reduced rate of lubricant atomization relative to pulse jet injectors. This is manifested as a smaller reduction in the reflected ultrasonic wave, showing less metal–metal contact had occurred. During steady-state testing, the oil feed rate was varied; the high flow

Rooke, Jack, Li, Xiangwei, Dwyer-Joyce, Robert S.

Compatibility between Stability and Curving Ability of Railway Vehicles Using Conventional and Unconventional Bogie Frame Models

02-18-03-0014

04/09/2025

This article analyses the fundamental curving mechanics in the context of conditions of perfect steering off-flanging and on-flanging. Then conventional, radial, and asymmetric suspension bogie frame models are presented, and expressions of overall bending stiffness kb and overall shear stiffness ks of each model are derived to formulate the uniform equations of motion on a tangent and circular track. A 4 degree of freedom steady-state curving model is formulated, and performance indices such as stability, curving, and several parameters including angle of attack, tread wear index, and off-flanging performance are investigated for different bogie frame configurations. The compatibility between stability and curving is analyzed concerning those configurations and compared. The critical parameters influencing hunting stability and curving ability are evaluated, and a trade-off between them is analyzed. For the verification, the damped natural frequencies and mean square acceleration

Sharma, Rakesh Chandmal, Sharma, Sunil Kumar, Palli, Srihari, Rallabandi, Sivasankara Raju, Sharma, Neeraj

T.R.I.C.K. 2.0: Enhanced Vehicle Dynamics Analysis and Estimation Harnessing Advanced Vehicle Sensors

10-09-03-0025

04/09/2025

Automotive signal processing is dealt with in several contributions that propose various techniques to make the most out of the available data, typically for enhancing safety, comfort, or performance. Specifically, the accurate estimation of tire–road interaction forces is of high interest in the automotive world. A few years ago the T.R.I.C.K. tool was developed, featuring a vehicle model processing experimental data, collected through various vehicle sensors, to compute several relevant virtual telemetry channels, including interaction forces and slip indices. Following years of further development in collaboration with motorsport companies, this article presents T.R.I.C.K. 2.0, a thoroughly renewed version of the tool. Besides a number of important improvements of the original tool, including, e.g., the effect of the limited slip differential, T.R.I.C.K. 2.0 features the ability to exploit advanced sensors typically used in motorsport, including laser sensors, potentiometers, and

Napolitano Dell’Annunziata, Guido, Farroni, Flavio, Timpone, Francesco, Lenzo, Basilio

A Low-Entry Bus Body Structure Performance under the Conditions of the New Car Assessment Program Frontal Crash Tests

09-13-02-0007

04/09/2025

The New Car Assessment Program (e.g., US NCAP and EuroNCAP) frontal crash tests are an essential part of vehicle safety evaluations, which are mandatory for the certification of civil means of transport prior to normal road exploitation. The presented research is focused on the behavior of a tubular low-entry bus frame during a frontal impact test at speeds of 32 and 56 km/h, perpendicular to a rigid wall surface. The deformation zones in the bus front and roof parts were estimated using Ansys LS-DYNA and considered such factors as the additional mass (1630 kg) of electric batteries following the replacement of a diesel engine with an electric one. This caused stabilization of the electric bus body along the transverse axis, with deviations decreased by 19.9%. Speed drop from 56 to 32 km/h showed a reduction of the front window sill deformations from 172 to 132 mm, and provided a twofold margin (159.4 m/s2) according to the 30g ThAC criterion of R80. This leads to the conclusion about

Holenko, Kostyantyn, Dykha, Aleksandr, Koda, Eugeniusz, Kernytskyy, Ivan, Royko, Yuriy, Horbay, Orest, Berezovetska, Oksana, Rys, Vasyl, Humeniuk, Ruslan, Berezovetskyi, Serhii, Chalecki, Marek

Experimental and Kinetic-Modeling Study of Ammonia/n-Heptane Combustion

13-06-03-0020

04/09/2025

In recent years, researchers have increasingly focused on ammonia–diesel dual-fuel engines as a means of reducing CO2 emissions. Analyzing in-cylinder combustion processes is essential for optimizing the performance of ammonia–diesel dual-fuel engines. However, there is currently a lack of suitable reaction kinetics models for ammonia–diesel engine conditions. In this study, the ignition delay of ammonia/n-heptane mixtures was measured, and a reduced chemical mechanism was developed. Using rapid compression machine (RCM) experiments, the ignition delays of ammonia/n-heptane mixtures with different ammonia energy fractions (AEFs) (40%, 60%, and 80%) were measured. The test pressure ranged from 1.5 to 3.0 MPa, while the temperature ranged from 667 to 919 K, with an equivalence ratio of 1. The results showed that as the AEFs increased, the ignition delay of the premixed mixture also increased. When the AEF was 40%, the ammonia/n-heptane premixed mixture exhibited the negative temperature

Cai, Kaiyuan, Liu, Yi, Chen, Qingchu, Qi, Yunliang, Li, Li, Wang, Zhi

Elongation Prediction of Die-Cast Aluminum Alloy Based on 3D Convolutional Neural Network Model

05-18-04-0032

04/09/2025

This study aims to predict the impact of porosities on the variability of elongation in the casting Al-10Si-0.3Mg alloy using machine learning methods. Based on the dataset provided by finite element method (FEM) modeling, two machine learning algorithms including artificial neural network (ANN) and 3D convolutional neural network (3D CNN) were trained and compared to determine the optimal model. The results showed that the mean squared error (MSE) and determination coefficient (R2) of 3D CNN on the validation set were 0.01258/0.80, while those of ANN model were 0.28951/0.46. After obtaining the optimal prediction model, 3D CNN model was used to predict the elongation of experimental specimens. The elongation values obtained by experiments and FEM simulation were compared with that of 3D CNN model. The results showed that for samples with elongation smaller than 9.5%, both the prediction accuracy and efficiency of 3D CNN model surpassed those of FEM simulation.

Zhang, Jin-sheng, Zheng, Zhen, Zhao, Xing-zhi, Gong, Fu-jian, Huang, Guang-sheng, Xu, Xiao-min, Wang, Zhi-bai, Yang, Yutong

Learning-Based Energy Management Strategy of Fuel Cell City Buses Considering Power Source Degradation

02-18-02-0012

04/02/2025

Fuel cell vehicles (FCVs) offer a promising solution for achieving environmentally friendly transportation and improving fuel economy. The energy management strategy (EMS), as a critical technology for FCVs, faces significant challenges of achieving a balanced coordination among the fuel economy, power battery life, and durability of fuel cell across diverse environments. To address these challenges, a learning-based EMS for fuel cell city buses considering power source degradation is proposed. First, a fuel cell degradation model and a power battery aging model from the literature are presented. Then, based on the deep Q-network (DQN), four factors are incorporated into the reward function, including comprehensive hydrogen consumption, fuel cell performance degradation, power battery life degradation, and battery state of charge deviation. The simulation results show that compared to the dynamic programming–based EMS (DP-EMS), the proposed EMS improves the fuel cell durability while

Song, Dafeng, Yan, Jinxing, Zeng, Xiaohua, Zhang, Yunhe

Use of Methanol in a High-Power Density Generator

13-06-03-0021

04/02/2025

Increasing global pressure to reduce anthropogenic carbon emissions has inspired a transition from conventional petroleum-fueled internal combustion engines to alternative powertrains, including battery electric vehicles (EVs) and hybrids. Hybrids offer a promising solution for emissions reduction by addressing the limitations of pure EVs such as slow recharge and range anxiety. In a previous research endeavor, a prototype high-power density generator was meticulously designed, fabricated, and subjected to testing. This generator incorporated a compact permanent magnet brushless dynamo and a diminutive single-cylinder two-stroke engine with low-technology constructions. This prototype generated 8.5 kW of electrical power while maintaining a lightweight profile at 21 kg. This study investigates the performance and emissions reduction potential by adapting the prototype to operate on methanol fuel. Performance and emissions were experimentally evaluated under varying operating conditions

Gore, Matt, Nonavinakere Vinod, Kaushik, Fang, Tiegang

Machine Learning–Based Modeling for Predicting the Lap Shear Strength of High-Strength Steel Laser Lap Welds

05-18-04-0029

03/29/2025

This study investigates the nonlinear correlation between laser welding parameters and weld quality, employing machine learning techniques to enhance the predictive accuracy of tensile lap shear strength (TLS) in automotive QP1180 high-strength steel joints. By incorporating three algorithms: random forest (RF), backpropagation neural network (BPNN), and K-nearest neighbors regression (KNN), with Bayesian optimization (BO), an efficient predictive model has been developed. The results demonstrated that the RF model optimized by the BO algorithm performed best in predicting the strength of high-strength steel plate-welded joints, with an R 2 of 0.961. Furthermore, the trained RF model was applied to identify the parameter combination for the maximum TLS value within the selected parameter range through grid search, and its effectiveness was experimentally verified. The model predictions were accurate, with errors controlled within 6.73%. The TLS obtained from the reverse-selected

Han, Jinbang, Ji, Yuxiang, Liu, Yong, Liu, Zhao, Wang, Xianhui, Han, Weijian, Wu, Kun

Modeling Vehicle Behavior in Highway On-Ramps: A Game Theory and Deep Reinforcement Learning Method

12-08-04-0037

03/28/2025

With the improvement of autonomous driving technology, the testing methods for traditional vehicles can no longer meet autonomous driving needs. The simulation methods based on virtual scenario have become a current research hotpot. However, the background vehicles are often pre-set in most existing scenarios, making it difficult to interact with the tested autonomous vehicles and generate dynamic test scenarios that meet the characteristics of different drivers. Therefore, this study proposes a method combining game theory and deep reinforcement learning, and uses a data-driven approach to realistically simulate personalized driving behavior in highway on-ramps. The experimental results show that the proposed method can realistically simulate the speed change and lane-change actions during vehicle interaction. This study can provide a dynamic interaction test scenario with different driver style for autonomous vehicle virtual test in highway on-ramps and a more realistic environment

Qiu, Fanke, Wang, Kan, Li, Wenli

Smart Clusters: Functional Safety Concepts and Requirements

12-08-02-0018

03/28/2025

This study presents a detailed review of a contemporary safety concept for a smart cluster, comprising a multipurpose display and a head unit. It focuses on elucidating the fundamental regulatory requirements for smart clusters within the frameworks of the United States and the European Union, and draws connections to their functional safety requirements and concepts. The article explores a range of safety mechanisms and architectures designed to implement these proposed functional safety requirements. For each mechanism, we provide an in-depth analysis of its benefits and drawbacks, as well as a thorough explanation of its operational logic. This comprehensive evaluation offers valuable insights into developing safer and more efficient smart clusters in line with international regulatory standards.

Anisimov, Valentin, Babaev, Islam, Shinde, Chaitanya

Vehicle–Vehicle Collaborative Control Strategy for Dedicated Lanes of Connected Vehicles

12-08-02-0012

03/28/2025

To alleviate the problem of reduced traffic efficiency caused by the mixed flow of heterogeneous vehicles, including autonomous and human-driven vehicles, this article proposes a vehicle-to-vehicle collaborative control strategy for a dedicated lane in a connected and automated vehicle system. First, the dedicated lane’s operating efficiency and formation performance are described. Then, the characteristics of connected vehicle formations are determined, and a control strategy for heterogeneous vehicle formations was developed. Subsequently, an interactive strategy was established for queueing under the coordination of connected human-driven and autonomous vehicles, and the queue formation, merging, and splitting processes are divided according to the cooperative interaction strategy. Finally, the proposed lane management and formation strategies are verified using the SUMO+Veins simulation software. The simulation results show that the dedicated lane for connected vehicles can

Zhang, Xiqiao, Cui, Leqi, Yang, Longhai, Wang, Gang

Letter from the Guest Editors

13-06-01-0001

03/27/2025

Letter from the Guest Editors

Kolhe, Mohan Lal, Zhang, Ronghui

GA-BP Neural Network-Based Prediction of Impact Resistance in Electric Vehicle Charging Piles

05-18-04-0028

03/27/2025

Impact resistance is crucial for assessing charging pile safety and reliability. This study proposes a prediction model, called GA-BP neural network, which achieved prediction errors below 5% and reduced computation time by over 95% in comparison to finite element analysis (FEA). Initially, the charging pile impact test platform is constructed, and a matching finite element simulation model is developed. The correctness of the simulation model is then verified by integrating the experimental findings. Furthermore, the Latin hypercube approach is used to create 200 sets of simulation schemes, and using the Python programming language, the impact resistance performance indicators of charging piles are automatically collected. Next, a genetic algorithm is used to optimize the initial weight and bias of the BP neural network, lastly, fine-tune the hyperparameters in the neural network to develop a prediction model for the impact resistance performance of the charging pile. The GA-BP model

Jiang, Bingyun, Hu, Peng, Liu, Zhenyu, Yuan, Pengfei, Liu, Hui

Multidimensional Coupling Effects and Vibration Suppression for In-Wheel Motor–Driven Electric Vehicle Suspension Systems: A Review

10-09-02-0013

03/26/2025

In this article, a comprehensive review regarding the vibration suppression for electric vehicles with in-wheel motors is provided. Most of the current reviews on the suspension performance of the in-wheel motor electric vehicles have seldom discussed the issue of the multidimensional coupling between the vertical and longitudinal dynamics of the vehicle. This article not only addresses this shortcoming, but also provides an all-inclusive review of these effects while considering the electrical–mechanical coupling on the vehicle dynamics. This article uses a state-of-the-art search strategy to search and process relevant and high-quality studies in the area. First, various negative effects of the deployment of the in-wheel motor, such as the increased unsprung mass, multidimensional electromagnetic–mechanical coupling, and the coupled vehicle vertical–longitudinal dynamics, are discussed. A review of the studies related to the unbalanced electromagnetic force and its coupling with the

Marral, Usman Iqbal, Du, Haiping, Naghdy, Fazel

Performance Evaluation and Thermal Analysis of Various Electric Drives for Automotive Electric Propulsion

14-14-02-0010

03/26/2025

Electric vehicles (EVs) represent a significant stride toward environmental sustainability, offering a multitude of benefits such as the reduction of greenhouse gas emissions and air pollution. Moreover, EVs play a pivotal role in enhancing energy efficiency and mitigating reliance on fossil fuels, which has propelled their global sales to unprecedented heights over the past decade. Therefore, choosing the right electric drive becomes crucially important. The main objective of this article is to compare various conventional and non-conventional electric drives for electric propulsion in terms of electromechanical energy conversion ratio and the thermal response under continuous [at 12 A/mm2 and 6000 rpm] and peak [at 25 A/mm2 and 4000 rpm] operating conditions. The comparative analysis encompasses torque density, power density, torque pulsation, weight, peak and running efficiencies of motor, inverter and traction drive, electromechanical efficiency, and active material cost. This

Patel, Dhruvi Dhairya, Fahimi, Babak, Balsara, Poras T.

Multi-objective Optimization of Process Parameters for Dual-Color Injection Molding of the Middle Cover of Electric Vehicle Charging Pile

05-18-04-0031

03/26/2025

This article takes the cover of the AC charging pile as the research object and studies the process parameters of dual-color injection molding. First, the optimal Latin hypercube experimental design is carried out by using optimization software by taking the melt temperature and mold temperature of the first shot and the second shot and the holding pressure as the influencing factors. Injection simulation is carried out based on mold flow software. A high-precision neural network model RBF is constructed according to the test factors and results. Second, based on the obtained RBF prediction model, the multi-objective NSGA-II algorithm is used for optimization. The obtained optimal combination of molding process parameters is: the melt temperature of the first shot is 266.8°C, the mold temperature is 107°C, the melt temperature of the second shot is 230.3°C, the mold temperature is 59.5°C, the holding pressure of the first shot is 95 MPa, the holding pressure of the second shot is 89.9

Liu, Hao, Jiang, Bingyun, Jiang, Hong, Hu, Peng, Cheng, Shan

Analysis and Prediction of Thermal Performance on Charging Equipment of Electric Vehicle

05-18-04-0030

03/26/2025

For the heat dissipation design of charging equipment for electric vehicles, a study is conducted on the thermal performance and its influencing factors of a specific alternating current (AC) charging device. First, based on heat dissipation theory and CFD simulation software, the corresponding finite element model is established and verified through experiments. Next, using the verified finite element model and applying the orthogonal experimental method, the factors influencing the heat dissipation performance of the AC charging pile, such as ambient temperature, output current of the AC charging pile, and surface radiation characteristics, are investigated. Finally, a prediction model for the maximum temperature of the main board is established using the response surface method (RSM), and the effects of each factor on the maximum main board temperature are analyzed, enabling rapid prediction of the heat dissipation performance of the AC charging pile. The analysis of the orthogonal

Tang, Yu, Yan, Chongjing, Lu, Feifei, Jiang, Bingyun, Bao, Yidong, Hu, Peng

Longitudinal Analysis of Forward Blind Zone Changes in Popular Vehicle Models (1997–2023)

09-13-01-0005

03/26/2025

Background. In 2022, vulnerable road user (VRU) deaths in the United States increased to their highest level in more than 40 years. At the same time, increasing vehicle size and taller front ends may contribute to larger forward blind zones, but little is known about the role that visual occlusion may play in this trend. Goal. Researchers measured the blind zones of six top-selling light-duty vehicle models (one pickup truck, three SUVs, and two passenger cars) across multiple redesign cycles (1997–2023) to determine whether the blind zones were getting larger. Method. To quantify the blind zones, the markerless method developed by the Insurance Institute for Highway Safety was used to calculate the occluded and visible areas at ground level in the forward 180° arc around the driver at ranges of 10 m and 20 m. Results. In the 10-m forward radius nearest the vehicle, outward visibility declined in all six vehicle models measured across time. The SUV models showed up to a 58% reduction

Epstein, Alexander K., Brodeur, Alyssa, Drake, Juwon, Englin, Eric, Fisher, Donald L., Zoepf, Stephen, Mueller, Becky C., Bragg, Haden

Experimental Analysis of Soot and NOx Mitigation during Energy-Buffered Diesel Engine Transients

03-18-02-0014

03/24/2025

Transient operation of a diesel-fueled compression ignition engine will produce significant levels of engine-out criteria pollutants such as NOx and soot emissions due to turbocharger lag. Conventional pollutant mitigation strategies during tip-ins (large increases in load) are constrained by the soot–NOx trade-off—strategies that mitigate soot/NOx emissions often result in an increase in NOx/soot emissions. Hybridization offers the ability to use an e-machine as an energy buffer during a tip-in, allowing the engine to tip-in slower to give the turbocharger time to spin up and provide the necessary amount of air for clean, high-load operation. In this work, an in-line six-cylinder 12.8 L Detroit Diesel DD13 engine was used to study the impact of slowing the torque ramp rate of a tip-in on the effectiveness of transient emission reduction strategies for turbocharged diesel engines, including exhaust gas recirculation (EGR) valve closing, start of injection retard, and the air–fuel ratio

Gainey, Brian, Datar, Aditya, Bhatt, Ankur, Lawler, Benjamin

Improving Safety of Autonomous Vehicles: A Verifiable Method for Graceful Degradation of Decision and Control Responsibilities

12-08-02-0021

03/24/2025

Developing safe and reliable autonomous vehicles is crucial for addressing contemporary mobility challenges. While the goal of autonomous vehicle development is full autonomy, up to SAE Level 4 and beyond, human intervention remains necessary in critical or unfamiliar driving scenarios. This article introduces a method for gracefully degrading system functionality and seamlessly transferring decision-making and control between the autonomous system and a remote safety operator when needed. This transfer is enabled by an onboard dependability cage, which continuously monitors the vehicle’s performance during its operation. The cage communicates with a remote command control center, allowing for remote supervision and intervention by a safety driver. We assess this methodology in both lab and test field settings in a case study of last-mile parcel delivery logistics and discuss the insights and results obtained from these evaluations.

Aniculaesei, Adina, Aslam, Iqra, Zhang, Meng, Buragohain, Abhishek, Vorwald, Andreas, Rausch, Andreas

Editorial

09-13-01-0008

03/24/2025

Driving Change: NHTSA’s Role in Advancing Road Safety

Hardy, Warren N.

Advancing Road Sensing Technology: Functional Observer for Vehicle Road Profile Estimation

12-08-04-0038

03/24/2025

Having an in-depth comprehension of the variables that impact traffic is essential for guaranteeing the safety of all drivers and their automobiles. This means avoiding multiple types of accidents, particularly rollover accidents, that may have the capacity of causing terrible repercussions. The non-measured factors in the system state can be estimated employing a vehicle model incorporating an unknown input functional observer, this gives an accurate estimation of the unknown inputs such as the road profile. The goal of the proposed functional observer design constraints is to reduce the error of estimation converging to a value of zero, which results in an improved calculation of the observer parameters. This is accomplished by resolving linear matrix inequalities (LMIs) and employing Lyapunov–Krasovskii stability theory with convergence conditions. A simulator that enables a precise evaluation of environmental factors and fluctuating road conditions was additionally utilized. This

Saber, Mohamed, Ouahi, Mohamed, Naami, Ghali, El Akchioui, Nabil

Experimental Methodology for Tire Ride Analysis Based on Outdoor Cleat Testing

10-09-03-0023

03/21/2025

Handling and ride comfort optimization are key vehicle design challenges. To analyze vehicle performance and investigate the dynamics of the vehicle and its subcomponents, we rely heavily on robust experimental data. The current article proposes an outdoor cleat test methodology to characterize tire dynamics. Compared to indoor procedures, it provides an effective tire operating environment, including the suspensions and the vehicle chassis motion influence. In addition, it overcomes the main limitation of existing outdoor procedures, the need for dedicated cleat test tracks, by using a set of removable cleats of different sizes. A passenger vehicle was equipped with sensors including an inertial measurement unit, a noncontact vehicle speed sensor, and a wheel force transducer, providing a setup suitable to perform both a handling test routine and the designed cleat procedure, aimed at ride testing and analysis. Thus, the outdoor cleat test data were compared with indoor test

Gravante, Gerardo, Napolitano Dell’Annunziata, Guido, Barbaro, Mario, Farroni, Flavio

Strain-Controlled High-Temperature (400°C) Low-Cycle Fatigue of Additive Manufactured Ti6Al4V Alloy

05-18-03-0024

03/21/2025

The tensile and low-cycle fatigue (LCF) properties of Ti6Al4V specimens, manufactured using the selective laser melting (SLM) additive manufacturing (AM) process and subsequently heat-treated in argon, were investigated at elevated temperatures. Specifically, fully reversed strain-controlled tests were performed at 400°C to determine the strain-life response of the material over a range of strain amplitudes of industrial interest. Fatigue test results from this work are compared to those found in the literature for both AM and wrought Ti6Al4V. The LCF response of the material tested here is in-family with the AM data found in the literature. Scanning electron microscopy performed on the fracture surfaces indicate a marked increase in secondary cracking (crack branching) as a function of increased plastic deformation and demonstrating equivalent performance when compared to the wrought Ti6AL4V at RT (room temperature) at 1.4% strain amplitude and better performance when compared to the

Gadwal, Narendra Kumar, Barkey, Mark E., Hagan, Zach, Amaro, Robert, McDuffie, Jason G.

Real-World Vehicle Estimation and Control of Indirect Emissions Control and Performance Evaluation of Electric Vehicles with In-Wheel Motors

03-18-02-0016

03/17/2025

The growing number of automobiles on the road has raised awareness about environmental sustainability and transportation alternatives, sparking ideas about future transportation. Few short-term alternatives meet consumer needs and enable mass production. Because they do not accurately reflect real-world driving. Current models are unable to estimate vehicle emissions. However, the purpose of this research is to present an application of an adaptive neuro-fuzzy inference system for managing the various factors contributing to vehicle gasoline engine exhaust emissions. It examines how well the three known standardized driving cycles (DSCs). Accurately reflect real-world driving and evaluate the impact of real-world driving on vehicle emissions. Indirect emissions are inversely proportional to the vehicle’s fuel consumption. The methodology used is Eco-score methodology to calculate indirect emissions of light vehicles. Expected emission charge estimates for different using styles

Shiba, Mohamed S., Abouel-Seoud, Shawki A., Aboelsoud, W., Abdallah, Ahmed S.

Mixing-Controlled Combustion of Ethanol Enabled by Prechamber Ignition (PC-MCC): A Preliminary Experimental Demonstration

04-18-02-0012

03/17/2025

This experimental study presents preliminary investigations of prechamber-enabled mixing-controlled combustion (PC-MCC) at −2 bar brake mean effective pressure (BMEP) and 2200 rpm with fuel-grade ethanol (E98). Experimental results are conducted on a prechamber retrofitted single-cylinder Caterpillar C9.3B test engine. First, a series of prechamber-only experiments were conducted with a motored engine to evaluate the salient combustion trends in response to relevant prechamber operating parameters. Under firing conditions, the prechamber operating strategy was assessed with respect to the impact on ignition assistance of direct-injected E98 and overall engine performance. The preliminary results indicate the jet-induced ignition process is robust and prompts diffusion combustion of E98 at diesel-like boundary conditions. The effect of external exhaust gas recirculation (EGR) on the residual tolerance of the prechamber combustion process was also investigated and showed stable

Zeman, Jared, Dempsey, Adam

Optimization of Abrasive Water Jet Machining of Al 6061-T6 Alloy Using Taguchi-Based Gray Relational Analysis-Coupled Principal Component Analysis Hybrid Approach

05-18-03-0023

03/13/2025

Abrasive water jet (AWJ) machining is the most effective technology for processing various engineering materials particularly difficult-to-cut materials such as aluminum alloys, steels, brass, ceramics, composites, and the like. The present study focuses on the experimental study on surface roughness and kerf taper is carried out during AWJ machining of Al 6061-T6 alloy with 40 mm thickness, and the influence of process parameters includes water jet pressure, standoff distance, and abrasive flow rate on the kerf taper and surface roughness is analyzed. The number of experiments is designed using Taguchi’s L9 orthogonal array. Experimental results are statistically analyzed using ANOVA. Also gray relational analysis (GRA) coupled with principal component analysis (PCA) hybrid approach was implemented to optimize the performance parameters. From the results it is found that standoff distance and hydraulic jet pressure are the most influencing parameters on surface roughness and kerf

Kolluri, Siva Prasad, Srikanth, V., Ismail, Sk., Bhanu, C.H.

Probabilistic Analysis Approach to Evaluate Gear Tooth Strength in the Hypocycloid Engine

03-18-02-0015

03/08/2025

This study introduces a probabilistic analysis approach to evaluate the gear tooth strength for the hypocycloid engines, which are particularly significant in internal combustion (IC) engine applications due to their unique design and critical requirements for both efficiency and durability. The research utilizes the stress–strength interference (SSI) theory within a “design for reliability” framework to develop a robust methodology for designing the internal gear mechanism required for the hypocycloid gear mechanism (HGM) engine, in accordance with American Gear Manufacturers Association (AGMA) standard gear rating practices. This approach incorporates probabilistic factors to address variations in HGM component parameters, gear material properties, and engine operational conditions. To validate the design and ensure accuracy, a finite element method (FEM)-based verification is employed, to identify potential failure points and enhance the overall reliability of the HGM engine. The

ElBahloul, Mostafa A., Aziz, ELsayed S., Chassapis, Constantin

Research on Automatic Emergency Braking Pedestrian System Considering Road Adhesion Coefficient

10-09-03-0022

03/08/2025

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.

Wang, Zijun, Wang, Liang, Ma, Liang, Sun, Yong, Li, Chenghao, Yang, Xinglong

A Study for Electric Vehicles Lithium-Ion Battery State Joint Estimation: Based on 2-RC Fractional Model

13-06-01-0007

03/08/2025

In the pursuit of enhancing the reliability of battery health management methods, accurate estimation of state of charge (SOC) and state of health (SOH) remains a critical challenge. This article presents a novel fusion estimation algorithm, combining a dual extended Kalman filter (EKF) with a particle filter (PF), based on a fractional-order 2-RC battery model (FOEKPF–EKF). The 2-RC fractional-order model (FOM) is first implemented to accurately depict the battery’s discharge behavior, outperforming traditional integer-order models (IOM) due to its ability to capture the cell’s intrinsic diffusion and dispersion characteristics. An adaptive genetic algorithm (AGA) is then employed for optimal parameter identification of the FOM, ensuring precise modeling. Following this, the FOEKPF–EKF algorithm is developed, leveraging the strengths of FOM, EKF, and PF to effectively handle uncertain, time-varying noise, thereby improving SOC estimation accuracy. The reliability of the proposed

Wang, Ke, Mo, Jian, Li, Dan, Zhou, Ying, Yuan, Zhangyong

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