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 (10,472)

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

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

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

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

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

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.

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

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.

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

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.

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

Flow Channel Optimization and Performance Analysis of Forced Air-Cooling Thermal Management for Lithium-ion Battery Energy Storage Modules

05-18-04-0027

03/05/2025

The maximum temperature and the maximum temperature difference of lithium battery energy storage systems are of great importance to their lifespan and safety. The energy storage module targeted in this research utilizes a forced air-cooling thermal management system. In this article, the maximum battery temperature, temperature difference, and cooling fan power are used as evaluation indicators. The thermal–fluid coupling simulation technology is utilized to restore the real structure of the module, ensuring the reliability of the simulation results. The P-Q curve is introduced for the boundary conditions of the heat dissipation fan to investigate the influence of the flow channel structure on the airflow volume and distribution. First, the thermal–fluid coupling simulation results of the original structure were compared with the measured parameters. Subsequently, the study on the airflow and temperature distribution of the original flow channel structure reveals that a significant

Guo, YuCheng, Bao, YiDong, Jiang, BingYun, Lu, FeiFei

Exploring H ₂ /O ₂ Injection in an Active Pre-Chamber Ignition Engine

03-18-02-0013

03/04/2025

Active fuel injection into a pre-chamber (PC) promotes high-temperature and highly turbulent jets, which ignite the cylinder gas with a very high exhaust gas recirculation (EGR) ratio, reducing emissions such as NOx. In the present study, two active PC injection strategies were designed to investigate the effect of injected hydrogen mass and PC mixture air-to-fuel equivalence ratio λ on PC combustion, jet formation, and main chamber (MC) combustion. Stoichiometric or rich hydrogen/oxygen mixtures are actively injected into the PC to enhance the combustion processes in the PC and the MC. A three-dimensional numerical engine model is developed using the commercial CFD code CONVERGE. The engine geometry and parameters adopt a modified GM 4-cylinder 2.0 L GDI gasoline engine. The local developments of gas temperature and velocity are resolved with the adaptive mesh refinement (AMR). The turbulence of the flow is computed with the k-epsilon model of the Reynolds-averaged Navier–Stokes (RANS

Yu, Tianxiao, Lee, Dong Eun, Alam, Afaque, Gore, Jay P., Qiao, Li

CFD-Based Comfort Parameter Evaluation of a Flow Vectoring Air Vent System for Car Cabins Using a Reduced Order Model

15-18-02-0012

03/03/2025

This computational fluid dynamics (CFD) study examines the comfort parameters of an innovative air vent concept for car cabin interiors using a reduced order model (ROM) and proper orthogonal decomposition (POD). The focus is on the analysis of the influence of geometric and fluid mechanical parameters on the resulting jet, in particular on the deflection angle of the airflow and the total pressure difference along the outlet geometry. Different parameters of the investigated system, such as the surface orientation, the outlet height, the separator distance, and the separator height, lead to different effects on the airflow structure. The results show that changes in the air vent surface orientation are always accompanied by an increase in the deflection angle and the total pressure difference. In contrast, the variation of the outlet height ratio positively influences the deflection angle and the total pressure difference in terms of the requirements for air vent geometries. The study

Langhorst, Sebastian, Mrosek, Markus, Boughanmi, Nesrine, Schmeling, Daniel, Wagner, Claus

Analysis of Speeding and Crashes on Bridges in Mugling to Narayanghat Highway Segment in Nepal

09-13-01-0002

03/03/2025

Driving speed affects road safety, impacting crash severity and the likelihood of involvement in accidents on highway bridges. However, their impacts remain unclear due to inconsistent topography and consideration of crash types. This study aimed to identify the status of accidents and factors associated with accidents occurring on bridges along the Mugling to Narayanghat highway segment in Nepal. The study area involves the selected highway segment stretching from Aptari junction (CH: 2+42) to Mugling junction (CH: 35+677). Spanning 33.25 km, the road traverses through both hilly and Terai regions. The study employs descriptive and correlation statistics to analyze crash data from 2018 to 2023, aiming to achieve its research objectives. The study reveals overspeeding as the primary cause of crashes, notably head-on and rear-end collisions. Two-wheelers frequently exceed the speed limit of 40 km/h limit (29–88 km/h), and four-wheelers do similarly (18–81 km/h), leading to overspeeding

Giri, Om Prakash, Shahi, Padma Bahadur, Kunwar, Deepak Bahadur

Fault-Tolerant Control of a Quadcopter Using Reinforcement Learning

01-18-01-0006

03/03/2025

This study presents a novel reinforcement learning (RL)-based control framework aimed at enhancing the safety and robustness of the quadcopter, with a specific focus on resilience to in-flight one propeller failure. This study addresses the critical need of a robust control strategy for maintaining a desired altitude for the quadcopter to save the hardware and the payload in physical applications. The proposed framework investigates two RL methodologies, dynamic programming (DP) and deep deterministic policy gradient (DDPG), to overcome the challenges posed by the rotor failure mechanism of the quadcopter. DP, a model-based approach, is leveraged for its convergence guarantees, despite high computational demands, whereas DDPG, a model-free technique, facilitates rapid computation but with constraints on solution duration. The research challenge arises from training RL algorithms on large dimension and action domains. With modifications to the existing DP and DDPG algorithms, the

Qureshi, Muzaffar Habib, Maqsood, Adnan, Fayyaz ud Din, Adnan

Experimental Investigation of Minimum Quantity Lubrication Strategy during Machining of Ti6Al4V Alloy

05-18-03-0022

03/03/2025

The experimental investigation analyzed the performance of three machining conditions: dry machining, cryogenic machining, and cryogenic machining with minimum quantity lubrication (MQL) on tool wear, cutting forces, material removal rate, and microhardness. The outcome of this study presents valuable knowledge regarding optimizing conditions of turning operations for Ti6Al4V and understanding the machinability under cryogenic-based cooling strategies. Based on the experimentation, cryogenic machining with MQL is the most beneficial approach, as it reduces cutting force and flank wear with a required material removal rate. This strategy significantly enhances the machining efficiency and quality of Ti6Al4V under variable feed rates (0.05 mm/rev, 0.1 mm/rev, 0.15 mm/rev, 0.2 mm/rev, 0.25 mm/rev) where cutting velocity (120 m/min) and depth of cut (1 mm) are constant. The effects of the main cutting force, feed force, thrust force, material removal mechanism, flank wear, and

Misra, Sutanu, Kumar, Yogesh, Paul, Goutam, Forouhandeh, Fariborz

Effects of Emergency Vehicle Warning Lighting System Characteristics on Driver Perception and Behavior

09-13-01-0003

02/28/2025

Secondary crashes, including struck-by incidents are a leading cause of line-of-duty deaths among emergency responders, such as firefighters, law enforcement officers, and emergency medical service providers. The introduction of light-emitting diode (LED) sources and advanced lighting control systems provides a wide range of options for emergency lighting configurations. This study investigated the impact of lighting color, intensity, modulation, and flash rate on driver behavior while traversing a traffic incident scene at night. The impact of retroreflective chevron markings in combination with lighting configurations, as well as the measurement of “moth-to-flame” effects of emergency lighting on drivers was also investigated. This human factors study recruited volunteers to drive a closed course traffic incident scene, at night under various experimental conditions. The simulated traffic incident was designed to replicate a fire apparatus in the center-block position. The incident

D. Bullough, John, Parr, Scott, Hiebner, Emily, Sblendorio, Alec

Quantifying the Impact of Electric Vehicles and Distributed Energy Resources on Load Profile Sensitivity: A Comprehensive Analysis

13-06-01-0008

02/27/2025

This research investigates how distributed energy resources (DERs) and electric vehicles (EVs) affect distribution networks. With sensitivity analysis, the research focuses on how these integrations affect load profiles. The research focuses on sizing of various DERs and EV charging/discharging strategies to optimize the load profile, voltage stability, and network loss minimization. System parameters including load profile, EV charging pattern, weather conditions, DER sizes, and electricity pricing are analyzed to quantify their individual and combined impacts on load variability. However, with increased capacity of DERs, network losses increase. A mathematical model with system and operational constraints has been developed and simulated in MATLAB Simulink environment, validation of the proposed approach in improving the load profile, and reduction in network losses, with the intermittent power generation from DERs and EV integration. Simulation result shows that optimal capacity of

Khedar, Kamlesh Kumar, Goyal, Govind Rai, Singh, Pushpendra

Refining Control, Charging, and Battery Chemistry for CO ₂ e Savings in Heavy-Duty Off-Road Plug-In Series Hybrid

14-14-02-0009

02/27/2025

With current and future regulations continuing to drive reductions in carbon dioxide equivalent (CO2e) emissions in the on-road industry, the off-road industry is also likely to be regulated for fuel and CO2e savings. This work focuses on converting a heavy-duty off-road material handler from a conventional diesel powertrain to a plug-in series hybrid, achieving a 49% fuel reduction and 29% CO2e reduction via simulation. Control strategies were refined for energy savings, including a regenerative braking strategy to increase regenerative braking and a load-following hydraulic strategy to decrease electrical energy consumption. The load-following hydraulic control shuts off the hydraulic electric machine when it is not needed—an approach not previously seen in a load-sensing, pressure-compensated system. These strategies achieved a 24.1% fuel savings, resulting in total savings of 61% in fuel and 41% in CO2e in the plug-in series compared to the conventional machine. Beyond control

Goodenough, Bryant, Czarnecki, Alexander, Robinette, Darrell, Worm, Jeremy, Subert, David, Kiefer, Dylan, Heath, Matthew, Brunet, Bob, Kisul, Robert, Latendresse, Phil, Westman, John, Black, Andrew

Toward a Methodology for Safety—Performance Trade-Off Analysis for Connected Automated Vehicles Supported by a Smart Infrastructure

12-08-02-0020

02/24/2025

Introducing connectivity and collaboration promises to address some of the safety challenges for automated vehicles (AVs), especially in scenarios where occlusions and rule-violating road users pose safety risks and challenges in reconciling performance and safety. This requires establishing new collaborative systems with connected vehicles, off-board perception systems, and a communication network. However, adding connectivity and information sharing not only requires infrastructure investments but also an improved understanding of the design space, the involved trade-offs and new failure modes. We set out to improve the understanding of the relationships between the constituents of a collaborative system to investigate design parameters influencing safety properties and their performance trade-offs. To this end we propose a methodology comprising models, analysis methods, and a software tool for design space exploration regarding the potential for safety enhancements and requirements

Fornaro, Gianfilippo, Törngren, Martin, Gaspar Sánchez, José Manuel

Experimental Case Study of Sonic Perception of a First-Generation Electric Truck

14-14-02-0008

02/24/2025

The sound generated by electric propulsion systems differs compared to the prevalent sound generated by combustion engines. By exposing listeners to various sound situations, the manufacturer can start understanding which direction to take to achieve compelling battery electric vehicle trucks from a sound perspective. The main objective of this study is to understand what underlying aspects decide the experience and perception of heavy vehicle–related sounds in the context of electrified propulsion. Using a thematic analysis of data collected at a listening experiment conducted in 2020, factors affecting the perception of novel sounds generated by a first-generation electric truck are investigated. A hypothesis is that the experience of driving or being a passenger in electric trucks will affect the rating and response differently compared to listeners not yet experienced with this sound. The results show that the combination of individual preference and experience, hearing function

Nyman, Birgitta, Fagerlönn, Johan, Nykänen, Arne

Temperature-Dependent Analysis of the Tire–Road Interaction Characteristics for a Passenger Car Tire Using Finite Element Analysis

15-18-02-0010

02/20/2025

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

Fathi, Haniyeh, El-Sayegh, Zeinab, Ren, Jing

Study of Different Types of Ventilation and Cooling Systems of Bulb Hydrogenerators in a Three-Dimensional Setting

05-18-03-0020

02/20/2025

The Object of research in the article is the ventilation and cooling system of bulb hydrogenerators. The Subject of study in the article is the design and efficiency of using the cooling system of various structural types for bulb hydro units. The Purpose of the work is to carry out a three-dimensional study of two cooling systems (axial and radial) of the bulb hydro unit of the Kanivskaya HPP with a rated 22 MW. Research Tasks include analysis of the main design solutions for effective cooling of bulb-type hydrogenerators, in particular, the use of radial, axial, and mixed cooling systems; formulation of the main assumptions for the three-dimensional ventilation and thermal calculation of the bulb hydrogenerator; carrying out a three-dimensional calculation for a hydrogenerator with axial ventilation; determining airflow speeds in the channels and temperatures of active parts of the hydrogenerator under the conditions of using discharge fans and without them; carrying out a three

Tretiak, Oleksii, Arefieva, Mariia, Makarov, Pavlo, Serhiienko, Serhii, Zhukov, Anton, Shulga, Iryna, Penkovska, Nataliia, Kravchenko, Stanislav, Kovryga, Anton

Multi-Objective Optimization of Powder-Mixed Electro-Discharge Machining of Tool Steel Using Advanced Algorithm

05-18-03-0021

02/20/2025

Electrical discharge machining (EDM) technology is one of the unconventional machining processes with an ability to machine intricate geometrics with micro finishing. Powder-mixed EDM (PMEDM) extends the EDM process by adding conductive powder to the dielectric fluid to improve performance. This set of experiments summarizes the effect of brass and copper electrode on HcHcr D2 tool steel in chromium powder-mixed dielectric fluid. Powder concentration (PC), peak current (I), and pulse on-time (Ton) are considered as variable process parameters. General full factorial design of experiment (DOE) and ANOVA has been used to plan and analyze the experiments where powder concentration is observed as the most significant process parameter. The results also reveal that a brass electrode offers a high material removal rate (MRR). Whereas, the copper electrode has reported noteworthy improvement in surface roughness (Ra). Moreover, teaching–learning-based optimization (TLBO) algorithm has been

Sonawane, Gaurav Dinkar, Sulakhe, Vishal, Dalu, Rajendra, Kaware, Kiran, Motwani, Amit

Model-Based Vehicle Mass Estimation for Enhanced Adaptive Cruise Control Performance

02-18-02-0009

02/19/2025

This study presents the development and integration of a vehicle mass estimator into the ZF’s Adaptive Cruise Control (ACC) system. The aim is to improve the accuracy of the ACC system’s torque control for achieving desired speed and acceleration. Accurate mass estimation is critical for optimal control performance, particularly in commercial vehicles with variable loads. The incorporation of such mass estimation algorithm into the ACC system leads to significant reductions in the error between requested and measured acceleration during both flat and uphill driving conditions, with or without a preceding vehicle. The article details the estimator’s development, integration, and validation through comprehensive experimental testing. An electric front-wheel drive van was used. The vehicle’s longitudinal dynamics were modeled using D’Alembert’s principle to develop the mass estimation algorithm. This algorithm updates the mass estimate based on specific conditions: zero brake torque, high

Marotta, Raffaele, D’Itri, Valerio, Irilli, Alessandro, Peccolo, Marco

Quantifying Hydroplaning Risk: Insights from Water Film Thickness Measurements on Maryland Highways

02-18-02-0010

02/19/2025

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

Vilsan, Alexandru, Sandu, Corina, Anghelache, Gabriel

Leveraging Triggering Conditions for Efficient Scenario-Based Testing of Automated Vehicles

12-08-04-0035

02/19/2025

Scenario-based testing has become a central approach of safety verification and validation (V&V) of automated driving. The standard ISO 21448: Safety of the intended functionality (SOTIF) [1] proposes triggering conditions (e.g., an occluded traffic sign) as a new aspect to be considered to organize scenario-based testing. In this contribution, we discuss the requirements and the strategy of testing triggering conditions in an iterative, SOTIF-oriented V&V process. Accordingly, we illustrate a method for generating test scenarios for evaluating potential triggering conditions. We apply the proposed method in a two-fold case study: We demonstrate how to derive test scenarios and test these with a virtual automated driving system in simulation. We provide an analysis of the testing result to show how triggering condition-based testing facilitates spotting the weakness of the system. Besides, we exhibit the applicability of the method based on multiple triggering conditions and nominal

Zhu, Zhijing, Philipp, Robin, Howar, Falk

Time-Varying Gain-Scheduled Path-Tracking Controller with Delay Compensation (TGDC) for Autonomous Vehicles

10-09-02-0012

02/19/2025

Path-tracking control occupies a critical role within autonomous driving systems, directly reflecting vehicle motion and impacting both safety and user experience. However, the ever-changing vehicle states, road conditions, and delay characteristics of control systems present new challenges to the path tracking of autonomous vehicles, thereby limiting further enhancements in performance. This article introduces a path-tracking controller, time-varying gain-scheduled path-tracking controller with delay compensation (TGDC), which utilizes a linear parameter-varying system and optimal control theory to account for time-varying vehicle states, road conditions, and steering control system delays. Subsequently, a polytopic-based path-tracking model is applied to design the control law, reducing the computational complexity of TGDC. To evaluate the effectiveness and real-time capability of TGDC, it was tested under a series of complex conditions using a hardware-in-the-loop platform. The

Hu, XuePeng, Zhang, Yu, Hu, Yuxuan, Wang, Zhenfeng, Qin, Yechen

A Comparative Study on the Working Efficiency of Journal Bearing Employing Different Micro-Textures

04-18-02-0011

02/19/2025

This study proposed the different micro-textures of the SC (square cylinder), SWS (square wedge shape), HS (hemispherical shape), and CR (cylindrical round) to improve the working efficiency of the journal bearing. A hydrodynamic lubrication model of the journal bearing under the impact of the changing dynamic loads is established to analyze the performance of micro-textures. The maximum oil film pressure and minimum frictional force in the journal bearing are selected as two evaluation indices. Some outstanding research results show that all the SC, SWS, HS, and CR added on the bearing surface improved the working efficiency of the journal bearing better than without the micro-textures. Moreover, the HS also improved the working efficiency of the journal bearing better than other structures of SC, SWS, and CR. To optimize the working efficiency of the journal bearing using HS, the dimension ltex and depth htex of HS should be selected and designed in a range of 3.6 < ltex ≤ 3.9 mm and

Song, Fengxiang, Nguyen, Vanliem, Liu, Yaxi

TOC

99-07-01-0TOC

02/17/2025

TOC

Tobolski, Sue

Cryptographic Method for Secure Object Segmentation for Autonomous Driving Perception Systems

12-08-01-0008

02/14/2025

The modern-day vehicle’s driverless or driver-assisted systems are developed by sensing the surroundings using a combination of camera, lidar, and other related sensors by forming an accurate perception of the driving environment. Machine learning algorithms help in forming perception and perform planning and control of the vehicle. The control of the vehicle which reflects safety depends on the accurate understanding of the surroundings by the trained machine learning models by subdividing a camera image fed into multiple segments or objects. The semantic segmentation system comes with the objective of assigning predefined class labels such as tree, road, and the like to each pixel of an image. Any security attacks on pixel classification nodes of the segmentation systems based on deep learning result in the failure of the driver assistance or autonomous vehicle safety functionalities due to a falsely formed perception. The security compromisations on the pixel classification head of

Prashanth, K.Y., Rohitha , U.M.

Deep Learning-Enhanced Direct Torque Control of BLDC Motors for Optimized Electric Vehicle Performance

12-08-04-0036

02/12/2025

Electric vehicles (EVs) represent a promising solution to reduce environmental issues and decrease dependency on fossil fuels. The main drawback associated with the direct torque control (DTC) scheme is that it is incapable of improving the efficiency and response time of the EVs. To overcome this problem, integrating deep learning (DL) techniques into DTC offers a valuable solution to enhance the performance of the drive system of EVs. This article introduces three control methods to improve the output for DTC-based BLDC motor drives: a traditional proportional–integral for speed controller (speed PI), a neural network fitting (NNF)-based speed controller (speed NNF), and a custom neural (CN) network-based speed controller (speed CN). The NNF and CN are DL techniques designed to overcome the limitations of conventional PI controllers, such as retaining the percentage overshoot, settling times, and improving the system’s efficiency. The CN controller reduced the torque ripple by 15

Patel, Sandesh, Yadav, Shekhar, Tiwari, Nitesh

Validating Human Factors-Based Classification Models for Safe and Efficient Mixed-Autonomy Interactions at Intersections Using a Virtual Simulator

12-08-02-0019

02/12/2025

The introduction of autonomous vehicles (AVs) promises significant improvements to road safety and traffic congestion. However, mixed-autonomy traffic remains a major challenge as AVs are ill-suited to cooperate with human drivers in complex scenarios like intersection navigation. Specifically, human drivers use social cooperation and cues to navigate intersections while AVs rely on conservative driving behaviors that can lead to rear-end collisions, frustration from other road users, and inefficient travel. Using a virtual driving simulator, this study investigates the use of a human factors-informed cooperation model to reduce AV reliance on conservative driving behaviors. Four intersection scenarios, each involving a left-turning AV and a human driver proceeding straight, were designed to obfuscate the right-of-way. The classification models were trained to predict the future priority-taking behavior of the human driver. Results indicate that AVs employing the human factors-informed

Ziraldo, Erika, Oliver, Michele

Study on the Impact of Arrangement of Urea Injector and Mixer in Diesel Engine Selective Catalytic Reduction System on Ammonia Uniformity

02-18-02-0007

02/12/2025

With the continuous upgrading of emission regulations for internal combustion engines, the nitrogen oxide treatment capacity of selective catalytic reduction (SCR) aftertreatment needs to be continuously improved. In this study, based on a prototype of SCR aftertreatment, the impact of the arrangement of key components in the SCR system (urea injector, mixer, and catalyst unit) on ammonia uniformity was investigated. First, parameterized designs of the urea injector, mixer, and SCR unit were conducted. Then, using computational fluid dynamics (CFD), numerical simulations of the established aftertreatment system models with different parameter factors were performed under a high-exhaust temperature and a low-exhaust temperature conditions to study the impact of each individual parameter on ammonia uniformity. Finally, an optimized solution was designed based on the observed patterns, and the optimized samples were tested on an engine performance and emission test bench to compare their

Jie, Wang, Jin, Jianjiao, Wu, Yifan

Diesel Engine Performance and Combustion Imaging Analysis of Gas-to-Liquid and Polyoxymethylene Dimethyl Ether Blended Fuels

04-18-02-0010

02/12/2025

To reduce carbon dioxide emissions from automobiles, the introduction of electric vehicles to the market is important; however, it is challenging to replace all existing IC engine vehicles with electric ones. Consequently, there is increasing anticipation for the use of carbon-neutral fuels, such as e-fuels. This study investigates the effects of GTL (gas-to-liquid), as a substitute for e-fuel, produced from natural gas via the Fischer–Tropsch synthesis method and polyoxymethylene dimethyl ether (OMEmix) produced from methanol, on engine performance. Additionally, combustion image analysis was conducted using a rapid compression and expansion machine (RCEM). GTL fuel combusts similarly to conventional diesel fuel but has slightly lower smoke emissions because it does not contain aromatic hydrocarbons. Further, its high cetane number results in better ignition properties. During the combustion, unburnt hydrocarbons and smoke are generated in the spray flame interference region near the

Shibata, Gen, Yuan, Haoyu, Yamamoto, Hiroya, Tanaka, Shusuke, Ogawa, Hideyuki

Real-Time Driver Drowsiness Detection Using YOLOv8 with Whale Optimization Algorithm

09-13-01-0001

02/10/2025

Driver fatigue and drowsiness portray an integral role in the frequency of road accidents. Putting in place policies intended to alert drivers is imperative for averting accidents and saving lives. This work aims to improve road safety by devising a real-time driver drowsiness detection system. To accomplish this, drowsiness is detected using YOLOv8 algorithm optimized with the whale optimization algorithm (WOA). Key facial cues such as eye closure and yawning frequency are monitored to analyze driving behavior by the suggested approach. YOLOv8 model optimized with WOA processes video streams in real time and sets off an alarm on the graphical user interface (GUI) dashboard based on the output. The proposed approach was investigated using two datasets namely UTA-RLDD and D3S. A 640 × 640 pixel image with a frame rate of 50 fps was used in the investigation. The mAP at 0.5 (mean average precision at 0.5 IoU (intersection over union) threshold) of drowsiness detection system using UTA

Nandal, Priyanka, Pahal, Sudesh, Sharma, Tripti, Omesh, Omesh

Active Unmatched Disturbance Rejection Quasi-Sliding Observer for Electronic Throttle Valve System Based on Backstepping Control

03-18-02-0011

02/10/2025

This study addresses the control problem of the electronic throttle valve (ETV) system in the presence of unmatched perturbations. Most previous works have ignored the effect of actuating motor inductance, which results in an approximated model with a matched perturbation structure. However, if this assumption is not permitted, the ETV model turns into an exact model with unmatched perturbation and the control task becomes more challenging. In this article, a backstepping control design based on a quasi-sliding mode disturbance observer (BS-QSMDO) has been proposed to effectively reject the unmatched perturbation in the ETV system. A rigorous stability analysis has been conducted to prove the ultimate boundedness for disturbance estimation error and tracking error. The key to this proposed observer-based control design is to obtain a robust and chattering-free controller based on a quasi-sliding mode methodology. The proposed quasi-sliding mode observer works to estimate the unmatched

Hameed, Akram Hashim, Al-Samarraie, Shibly Ahmed, Humaidi, Amjad Jaleel

Effectiveness of Seat’s Negative Stiffness Structure on Three Different Models of Vehicles

15-18-02-0011

02/08/2025

The effectiveness of the negative suspension structure (NSS) in isolating the driver’s seat vibrations has been demonstrated based on the seat’s model or vehicle’s one-dimensional dynamic model. To fully assess the effectiveness and stability of the seat’s NSS (S-NSS) on different models of vehicles, the three-dimensional models of the vibratory rollers (VR), heavy trucks (HT), and passenger cars (PC) have been built to assess the effectiveness of S-NSS compared to the seat’s passive suspension (S-PC) and seat’s control suspension (S-CS). The effectiveness of S-NSS is then investigated under all operating conditions of vehicles. The investigation results indicate that under a same simulation condition, S-NSS improves the ride comfort and health of the driver better than both S-PS and S-CS on all VR, HT, and PC. However, the effectiveness of S-NSS on PC is lower than on both VR and HT while the effectiveness of S-CS on PC is better than on both VR and HT. Besides, the effectiveness of S

Su, Beibei, Wang, Qiang, Song, Fengxiang

Integration of Muscle Pre-tension and Activation to Evaluate Neck Muscle Strain Injury Risk during Simulated Rear Impacts Using a Finite Element Neck Model

2025-22-000102/07/2025

Prevention of rear-impact neck injuries remains challenging for safety designers due to a lack of understanding of the tissue-level response and injury risk. Soft tissue injuries have been inferred from clinical, cadaveric, and numerical studies; however, there is a paucity of data for neck muscle injury, commonly reported as muscle pain. The goal of this study was to investigate the effect of muscle pre-tension and activation on muscle strain and injury risk resulting from low-severity rear impacts using a detailed finite element head and neck model (HNM). The HNM was extracted from the GHBMC average stature male model and re-postured to match a volunteer study, with measured T1 kinematics applied as boundary conditions to the HNM. Three cases were simulated for three impact severities: the baseline repostured HNM, the HNM including muscle pre-tension, and the HNM with muscle pre-tension and muscle activation. The head kinematics, vertebral kinematics, muscle strains, and three neck

Correia, Matheus A., McLachlin, Stewart D., Cronin, Duane S.

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