bluuebunny/crossref_metadata_2025 huggingface dataset:
A Study on a Prognostics and Health Management (PHM) Based on Fracture Mechanics Using Deep Learning
Authors: Moon Byungwoo , Lee SangWon , Nam DongJin , Kim Jeonghwan , Bae JaeWoong , Shin JeongMin
Published: April 2024

This paper presents deep learning-based prognostics and health management (PHM) for predicting fractures of an electric propulsion (eP) drivetrain system using real-time CAN signals. The deep learning algorithm, based on autoencoders, resamples time-series signals and converts them into 2D images using recurrence plots (RP). Subsequently, through unsupervised learning of DeepSVDD, it detects anomalies in the converted 2D images and predicts the failure of the system in real-time. Also, reliability analysis based on fracture mechanics was performed using the detected signals and big data. In particular, the severity of the eP drivetrain system is proportional to the maximum shear stress (τmax) in terms of linear elastic fracture mechanics (LEFM) and can be calculated by summarizing the relationship between cracks (a) and the stress intensity factor (KIII). During this process, the system status can be checked by comparing the stress intensity factor and fracture toughness (KIIIc), and the time from the detection of an abnormal signal in the system to complete failure can be quantitatively determined. Therefore, it is possible to continuously maintain the status of the system by detecting failure signals using deep learning before vehicle parts fail, and with the detected failure prediction signals, a process can be established to enable users to repair defects in the vehicle system before breakdown occurs. By predicting the remaining life of the system and calculating field reliability through these procedures, we introduce innovative technologies aimed at preventing safety accidents, reducing economic costs, and addressing quality issues. In the future, we expect to achieve high business performance by extending and applying this deep learning-based PHM approach to all vehicle components.
Fatigue Analysis and Rapid Design Process of Anti-vibration Rubber Parts for Automobiles
Authors: Sugimoto Nao
Published: April 2024

In recent years, an increase in vehicle weight due to the electrification of automobiles, specifically EVs, has increased the input loads on anti-vibration rubber parts. Moreover, the characteristics of these loads have also changed due to the rotational drive of electric motors, regenerative braking, and other factors.

When designing a vehicle, in advance it is necessary to set specifications that take into account the spring characteristics and durability of the anti-vibration rubber parts in order to meet functional requirements. In this study, the hyperelastic and fatigue characteristics (S-N diagram and Haigh diagram) of Rubbers which is widely used for anti-vibration rubber parts, were experimentally obtained, and structural and fatigue analyses using FEM (Finite Element Method) were conducted in conjunction with spring and fatigue tests of anti-vibration rubber parts to determine the correlation between their spring and fatigue characteristics. Parameter studies were conducted by performing structural and fatigue analyses on anti-vibration rubber parts of various shapes and sizes, and it was shown that the volume of rubber in an anti-vibration rubber part is largely related to its spring and fatigue characteristics. A “performance catalog” was then constructed to store various information linking the spring and fatigue characteristics of the parts and their dimensions as design data. By utilizing this catalog during the planning stage of vehicle development, when detailed part geometry has not yet been determined, it is now possible to instantly derive the volume and dimensions of the rubber part that can help ensure durability against the required input load through reverse engineering, thereby enabling evidence-based performance design.
A Study on Fatigue Life Prediction Technique considering Bead Notch Shape in Arc Welding of Steel Components under Multi-Axial Load
Authors: Kim Dooyoung , Kong Ho Young , Park Jaehong
Published: April 2024

This study deals with the fatigue life prediction methodology of welding simulation components involving arc welding. First, a method for deriving the cyclic deformation and fatigue properties of the weld metal (that is also called ER70S-3 in AWS, American Welding Standard) is explained using solid bar specimens. Then, welded tube specimens were used with two symmetric welds and subjected to axial, torsion, and combined in-phase and out-of-phase axial-torsion loads. In most previous studies the weld bead’s start/stop were arbitrarily removed by overlapping the starting and stop point. Because it can reduce fatigue data scatter. However, in this study make the two symmetric weld’s start/stops exposed to applying load. Because the shape of the weld bead generated after the welding process can act as a notch (Ex. root notch at weld start / Crater at weld stop) to an applied stress. Accordingly, they were intentionally designed to cause stress concentrations on start/stops. A geometric 3D model of the weld was created followed by detailed finite element analyses to obtain fatigue notch factors under axial and torsion loadings. Fatigue life predictions were performed using nominal stress-life and the predictions were conducted by comparing with actual experimental results for validation.
Computational Modeling and Optimization of a Flapping Mechanism Based on the Scotch Yoke Principle
Authors: Rayed Ashraf Mahmud , Esakki Balasubramanian , Banik Sajal Chandra , Nahin Ashrafun
Published: April 2024

The flight mechanisms of birds have long inspired efforts to develop bioinspired aerial vehicles. This study presents a computational framework to analyze a flapping mechanism's structural behavior and performance based on the Scotch yoke principle. A three-dimensional CAD model is developed and meshed for finite element analysis in ANSYS. Structural steel is chosen as the material. Static analysis is performed under simulated flapping loads to predict deformation, stresses, fatigue life, and failure points. Preliminary results identify regions of high-stress concentration requiring optimization. Topology optimization is conducted to determine an optimal material layout within defined constraints. Additional shape and compliance optimizations are employed. Comparison of initial and optimized designs significantly reduces maximum deformation and stresses throughout the structure. Fatigue life and safety factors are markedly improved. This study enhances understanding of Scotch yoke flapping mechanisms through computational modelling and optimization techniques. Insights gained can aid in the engineering design and reliability assessment of bioinspired flying machines.
Electrification and control of a 1:5 scale vehicle for automotive testing methodologies
Authors: Vella Angelo Domenico , Biondo Luca , Tota Antonio , Vigliani Alessandro
Published: April 2024

The design and testing of innovative components and control logics for future vehicular platform represents a challenging task in the automotive field. The use of scale model vehicles constitutes an interesting alternative for testing assessment by decreasing time and cost efforts with a potential benefit in terms of safety.

The target of this research work is the development of a customized scale vehicle platform for verifying and validating innovative control strategies in safe conditions and with cost reduction. Consequently, the electrification of a radio-controlled 1:5 scale vehicle is carried out and a customized remote real-time controller is installed onboard. One of the main features of this commercial product is its modular characteristics that allows the modification of some component properties, such as the viscous coefficient of the shock absorbers, the stiffness of the springs and the suspension geometry. The original vehicle is equipped with a 2-stroke internal combustion engine, whose throttle command is provided by a common radio transceiver/receiver unit. The original configuration is commonly adopted for radio-controlled race car competitions, but the presence of a noisy combustion engine is not well suited for implementing a precise and accurate control logic based on onboard sensor measurements; hence, the conversion into an electric vehicle represents the adopted solution in this research activity.

In particular, the electrification process accounts for the replacement of the internal combustion engine and fuel tank with a brushless DC motor, a battery pack, and a planetary gearbox. CAD tools are exploited for the selection of the replacement components and the design of the mounting systems. Additionally, a Speedgoat Baseline Real-Time Target Machine is installed for implementing the customized control logic, developed in MATLAB/Simulink environment, for controlling the traction electric motor and the steering servomotor.

After a preliminary bench testing phase, a remote control is implemented for the validation of the system through maneuvers typically carried out for vehicle handling analysis.
Modeling and Time Discrete Characteristics Analysis of the Oil Filling Process of Wet Clutch for a Specialized Vehicle’s Automatic Transmission
Authors: Guo Jun , Feng Guangjun , Wu Jinglai , Zhang Yunqing
Published: April 2024

The automatic transmission of a specialized vehicle encountered challenges in achieving stable oil filling time due to the considerable variability of related parameters and the non-linear trends in the variation of individual product parameters over time. To investigate the underlying causes of this phenomenon and enhance the oil filling efficiency, a detailed model of the clutch oil filling process during gear shifting was established in this paper, which included dynamic models of the key components such as the hydraulic system, clutch, proportional valve, and oil passages. Physical experiments were performed on the test bench to compare with the simulation results. The results showed that the correlation between the simulation model and the test bench was well, which verified the effectiveness of the simulation model. Based on analyzing the clutch filling process, the effects of parameters such as orifice diameter, piston cavity clearance, clutch gap, and oil injection pressure on the filling time response of the system were primarily considered, and dynamic simulations were carried out to investigate the influence of these parameters on the clutch filling time. These results provided substantial theoretical support for the optimization and calibration of relevant parameters in the subsequent design iterations of the specialized vehicle's automatic transmission.
Vibration Control of MR-Damped Half Truck Suspension System Using Proportional Integral Derivative Controller Tuned by Ant Colony Optimization
Authors: Gad Sherif , Metered Hassan , Bassiuny A. M. , Abdel-Ghany Abdel-Ghany
Published: April 2024

Proportional integral derivative (PID) control technique is a famous and cost-effective control strategy, in real implementation, applied in various engineering applications. Also, the ant colony optimization (ACO) algorithm is extensively applied in various industrial problems. This paper addresses the usage of the ACO algorithm to tune the PID controller gains for a semi-active heavy vehicle suspension system integrated with cabin and seat. The magnetorheological (MR) damper is used in main suspension as a semi-active device to enhance the ride comfort and vehicle stability. The proposed semi-active suspension consists of a system controller that calculate the desired damping force using a PID controller tuned using ACO, and a continuous state damper controller that predict the input voltage that is required to track the desired damping force. The ACO algorithm is used to solve the nonlinear optimization problem to search the PID controller gains by finding the optimal problem solution. A mathematical model of an eight degree-of-freedom MR-damped heavy vehicle suspension system is derived and simulated using Matlab/Simulink software. The proposed ACO PID controlled suspension is compared to both MR semi active (ON-OFF) and conventional passive system. System performance criteria are evaluated under different road disturbances to quantify the success of the proposed controller. The simulated results reflect that the proposed ACO PID controller of the MR-damped heavy vehicle suspension offers a significant enhancement in ride comfort and vehicle stability.
A Survey of Vehicle Dynamics Models for Autonomous Driving
Authors: Jin Lingge , Zhao Shengxuan , Xu Nan
Published: April 2024

Autonomous driving technology is more and more important nowadays, it has been changing the living style of our society. As for autonomous driving planning and control, vehicle dynamics has strong nonlinearity and uncertainty, so vehicle dynamics and control is one of the most challenging parts. At present, many kinds of specific vehicle dynamics models have been proposed, this review attempts to give an overview of the state of the art of vehicle dynamics models for autonomous driving. Firstly, this review starts from the simple geometric model, vehicle kinematics model, dynamic bicycle model, double-track vehicle model and multi degree of freedom (DOF) dynamics model, and discusses the specific use of these classical models for autonomous driving state estimation, trajectory prediction, motion planning, motion control and so on. Secondly, data driven or AI based vehicle models have been reviewed, and their specific applications in automatic driving and their modeling and training processes are introduced. At the end of this review, the advantages and disadvantages of these vehicle models are summarized, and the future research directions and possible explorations are discussed to guide readers.
Identification of Low Vibration Damping Areas on Automotive Door Panel and Improvement Using Natural Fibers
Authors: Jawale Pradeep , Mache Ashok , Chhatlani Chirag , Wagh Omkar , Pandit Sakshi
Published: April 2024

Vibrations constitute a pivotal factor affecting passenger comfort and overall vehicle performance in both Conventional Internal Combustion Engine (ICE) vehicles and Electric Vehicles (EVs). These vibrations emanate from various sources, including vehicle design and construction, road conditions, and driving patterns, thereby leading to passenger discomfort and fatigue. In the pursuit of mitigating these issues, natural fibers, known for their exceptional damping properties, have emerged as innovative materials for integration into the automotive industry. Notably, these natural fiber-based materials offer a cost-effective alternative to traditional materials for vibration reduction. This research focuses on evaluating natural fibers mainly hemp, jute and cotton fibers for their damping characteristics when applied to a steel plate commonly used in the automotive sector. Using Fast Fourier Transform (FFT) analyzer, the natural frequency and damping properties of these materials are estimated experimentally, with the aim of creating an optimal damping solution when combined with the steel plate to effectively reduce vibrations. Furthermore, the investigation centers on the critical proximity of the passenger door to the passengers. A low vibration damping area on the door has been identified by grid points. Thereafter, natural fibers used strategically applying to areas with the least damping and checked for improvements. The door vibration damping is significantly improved by 30%. This novel approach offers an environmentally friendly and sustainable alternative to the conventional synthetic materials traditionally used in the automotive industry.
Optical diagnostic study on ammonia-diesel and ammonia-PODE dual fuel engines
Authors: Mao Jianshu , Zhang Yixiao , Ma Yue , Ma Xiao , Wang Zhi , Wang Zhenqian , Shuai Shijin
Published: April 2024

Ammonia shows promise as an alternative fuel for internal combustion engines (ICEs) in reducing CO2 emissions due to its carbon-free nature and well-established infrastructure. However, certain drawbacks, such as the high ignition energy, the narrow flammability range, and the extremely low laminar flame speed, limit its widespread application. The dual fuel (DF) mode is an appealing approach to enhance ammonia combustion. The combustion characteristics of ammonia-diesel dual fuel mode and ammonia-PODE3 dual fuel mode were experimentally studied using a full-view optical engine and the high-speed photography method. The ammonia energy ratio (ERa) was varied from 40% to 60%, and the main injection energy ratio (ERInj1) and the main injection time (SOI1) were also varied in ammonia-PODE3 mode. The findings demonstrate that ammonia-PODE3 mode exhibits better ignition characteristics than ammonia-diesel mode, resulting in an earlier ignition start, a larger flame area, a larger flame expansion speed, a shorter ignition delay time (IDT) and a shorter combustion duration (CD) due to the higher cetane number (CN) and a greater injection mass of PODE3 at the same energy input. Ammonia-PODE3 mode achieves larger maximum cylinder pressure (Pmax) and peak heat release rate (HRR) compared to ammonia-diesel mode. Furthermore, almost no soot was observed in ammonia-PODE3 mode throughout the entire combustion process. The results also indicate the start of the ignition is delayed and the first peak flame expansion speed decreases at a higher ammonia energy ratio. The maximum flame area is the largest at ERa = 60%, but the peak cylinder pressure and IMEP reach their highest values at ERa = 50%. Both the first peak flame area and the first peak flame expansion speed increase with the increase of ERInj1, and the Pmax and first peak HRR also increase. The IDT slightly extends with the increase of ERInj1, while CA50 advances and CD reduces. The start of the ignition is delayed with the advancement of the main injection time, and the largest flame area is observed at SOI1 = -12.5 °CA. Both the first Pmax and the maximum IMEP occur at SOI1 = -15 °CA. This is because the cylinder temperature and pressure are lower during combustion when the main injection time is early, while a later main injection time leads to inadequate fuel-air mixing and a delayed combustion phase.
A Rapid Catalyst Heating System for Gasoline-Fueled Engines
Authors: Disch Christian , O'Donnell Ryan , Singh Ripudaman , Chutipassakul Somjai , Krein William , Heinzelmann Frank , Oesterle Matthias
Published: April 2024

Increasingly stringent tailpipe emissions regulations have prompted renewed interest in catalyst heating technology – where an integrated device supplies supplemental heat to accelerate catalyst ‘light-off’. Bosch and Boysen, following a collaborative multi-year effort, have developed a Rapid Catalyst Heating System (RCH) for gasoline-fueled applications. The RCH system provides upwards of 25 kW of thermal power, greatly enhancing catalyst performance and robustness. Additional benefits include reduction of precious metal loading (versus a ‘PGM-only’ approach) and avoidance of near-engine catalyst placement (limiting the need for enrichment strategies). The following paper provides a technical overview of the Bosch/Boysen (BOB) Rapid Catalyst Heating system – including a detailed review of the system’s architecture, key performance characteristics, and the associated impact on vehicle-level emissions.
Research on Thermal Control of High Voltage Electronic Control System in Dual Hybrid Vehicles
Authors: Jing Junchao , Wang Zhentao , Liu Yiqiang , Huang Weishan , Dai Zhengxing
Published: April 2024

The hybrid system's thermal strategy is centered around controlling the cooling of the motor, inverter, DCDC and evaporator. In this electric drive circuit system, the water temperature sensor is positioned at the radiator outlet rather than within it. Consequently, when determining the required air volume for radiator cooling and water demand for sub-components of the electric drive circuit, an estimation of the inlet water temperature becomes necessary. This estimation relies on a heat transfer formula that converts heat released by circuit sub-components into their contribution to temperature rise within the circuit plus the outlet temperature from the previous round through the radiator to determine inlet water temperature. The inverter's heat transfer power depends on voltage and current levels. Adjusting motor torque leads to rapid changes in current flow while maintaining a low speed for optimal flow rate through the electric drive pump. As a result, there should be a significant increase in cooling liquid temperature passing through the inverter. To ensure accurate signal tracking without any signal noise or interference (signal burrs), it is important to compare estimated temperatures with actual temperatures during this process. In our existing system design, we calculate separate flow demands for motor flow, DCDC flow, OBC flow, and radiator flow. Once these individual flows reach their maximum limits after considering hardware limitations and compensations calculated by HVG inverter, DCDC converter and OBC request level; they are combined together as requested flows using wave filtering techniques. Finally, the desired pump speed is determined based on both requested flow rate and electric drive water temperature by referencing lookup tables. The compressor speed request incorporates feedforward control along with PID control algorithms. Its value depends on both battery cooling requirements and evaporator cooling needs.
Computational Fluid Dynamics Simulations of Aerodynamic Performance of Low-Pressure Axial Fans with Upstream Blockage
Authors: Ghosh Debarshee , Andersson Niklas , Etemad Sassan
Published: April 2024

Rotor-only ducted low-pressure axial fans play a crucial role in automotive thermal management of the tightly packed under-hood region. Most current scientific work concerning low-pressure axial fans investigate the aerodynamic performance of these fans while operating with uniform inlet flow conditions. This is rarely the case in real-world applications. This work aims to investigate the aerodynamic performance of low-pressure axial fans operating with upstream blockages. First, a validation study is performed in the absence of any upstream blockage. Numerical results are compared against publicly available experimental data. Steady-state, Reynolds-Averaged Navier Stokes (RANS) analysis is performed on a single-blade passage. The validation study also evaluates the choice of turbulence model and suggests the use of the k- ε turbulence model with wall functions for the best comparison against experimental data. To study the effect of upstream blockage, a generic blockage disc is positioned upstream of the fan inlet. Three different radial extents of the blockage disc is evaluated, such that different radial extents of the blade span is blocked. A strong influence of the upstream blockage is observed on the fan performance and flow distribution along the blade span. The total-to-static pressure coefficient and the total-to-static efficiency decrease proportionately to the extent of blockage in the radial direction. The peak total-to-static efficiency moves to a lower flow coefficient with increase in upstream flow blockage. This is deemed undesirable for automotive applications where it is desirable to have maximum aerodynamic efficiency at the highest possible flow coefficient.
A 3-D CFD Investigation of Ball Bearing Weir Geometries and Design Considerations for Lubrication
Authors: Mohapatra Chinmoy K. , Schlautman Jeff , Pandey Ashutosh , Wang Chengjie , Srinivasan Chiranth
Published: April 2024

The study focuses on understanding the air and oil flow characteristics within a ball bearing during high-speed rotation, with a particular emphasis on optimizing frictional heat dissipation and oil lubrication methods. Computational fluid dynamics (CFD) techniques are employed to analyze the intricate three-dimensional airflow and oil flow patterns induced by the motion of rotating and orbiting balls within the bearing. A significant challenge in conducting three-dimensional CFD studies lies in effectively resolving the extremely thin gaps existing between the balls, races, and cages within the bearing assembly. In this research, we adopt the ball-bearing structured meshing strategy offered by Simerics-MP+ to meticulously address these micron-level clearances, while also accommodating the rolling and rotation of individual balls. Furthermore, we investigate the impact of different designs of the lubrication ports to channel oil to other locations compared to the ball bearings. This analysis is pivotal, as it allows us to assess the effects of these bearing weirs on spin loss, which, in turn, has a substantial influence on the overall efficiency of an electric motor. This holistic understanding of spin loss is crucial in the context of battery electric vehicles (BEVs), as it directly affects the vehicle’s range and energy efficiency. In conclusion, this research not only sheds light on the intricate airflow dynamics within ball bearings but also underscores the practical significance of mitigating spin loss in electric motors, thus contributing to the advancement of BEV technology and its environmental sustainability.
A Study on the Evaluation of UX of Mid SUV
Authors: Zoo Heeen , Kim Changsub , Park Keun-Ryang
Published: April 2024

In recent years, with the advent of the Fourth Industrial Revolution and the COVID-19 pandemic, people's lives worldwide have undergone significant changes. Additionally, the emergence of a new generation of consumers known as the millennial generation has led to a high demand for multipurpose family cars. The perspective is shifting towards choosing premium products that enhance the quality of life and pursue their own happiness and comfort through technology, rather than simply selecting a midsize SUV based on the increase in family size. We aim to meet the needs of these global customers by conducting research and developing various new features that were not previously available in midsize SUVs. In this study, we defined the actual target users for midsize SUVs and established UX concepts by analyzing their characteristics. Based on this, we employed an optimal design approach by analyzing the evaluation results by country for the various features implemented within the vehicle. This allowed us to understand the background behind commonalities and differences and integrate them into the actual design process. In addition, during this process, we qualitatively collected the Voice of the Customer (VOC) from actual customers, allowing us to establish the foundation for optimal design. We primarily used In-Depth Interviews (IDI) as our evaluation method, but in order to achieve optimal design, we also incorporated quantitative methods to ensure the quality of the evaluation results. Utilizing 16 categories of UX values, which allow for a more systematic and clear quantitative evaluation of UX, can be extended to evaluations across various vehicle grades and types.
Investigation of the Prediction Model and Assessment Parameters of Head Injury of Children Occupants Based on Machine Learning
Authors: Li Haiyan , Wang Yanxin , He Lijuan , Lv Wenle , Cui Shihai , Ruan Jesse Shijie
Published: April 2024

The head injury mechanisms of occupants in traffic accidents will be more complicated due to the diversified seating postures in autonomous driving environments. The injury risks and assessment parameters in complex collision conditions need to be investigated thoroughly. Mining the simulation data by the support vector machine (SVM) and the random forest algorithms, some head injury predictive models for a 6-year-old child occupant under a frontal 100% overlap rigid barrier crash scenario were developed. In these head injury predictive models, the impact speed and sitting posture of the occupant were considered as the input variables. All of these head injury predictive models were validated to have good regression and reliability (R2>0.93) by the ten-fold cross-validation. When the collision speed is less than 60km/h, rotational load is the primary factor leading to head injury, and the trends of BrIC, von Mise stress, Maxshear stress, and MPS are similar. However, when the speed exceeds 60km/h, brain injuries are primarily affected by linear load. The head 3ms acceleration, HIC15, von Mise stress, Maxshear, and MPS have a consistent trend. The causes of head injury are mainly affected by the collision speed and sitting angle. Therefore, in autonomous driving scenarios, the design of child restraint systems should fully consider the influence of collision speed and sitting posture on the risk and mechanism of injury, improving the phenomenon of occupant submarine and head restraint insufficiency under the large angle sitting posture. This research will establish a theoretical foundation for investigating head injury mechanisms, injury thresholds, and the consistency of injury indices, and will provide data support for enhancing the restraint system and virtual testing.
Analysis of Aerodynamic Characteristics of Fan-Type Wheels
Authors: Shin Yong-su , Lee Jungsoo
Published: April 2024

This research addresses the pressing need for reducing vehicle aerodynamic resistance, with a specific focus on mitigating wheel and tire resistance, which constitutes approximately 25% of the overall vehicle drag. While the prevailing method for reducing resistance in mass production development involves wheel opening reduction, it inadvertently increases wheel weight and has adverse effects on brake cooling performance. To overcome these challenges, novel complementary resistance reduction methods that can be employed in conjunction with an appropriate degree of wheel opening reduction are imperative. In this study, we introduce symmetrical wheels with a fan-like shape as a solution. The fan configuration influences the surrounding flow by either drawing it in or pushing it out, depending on the direction of rotation. Application of these fan-type wheels to a vehicle's wheels results in the redirection of flow inwards or outwards during high-speed driving due to wheel rotation. This, in turn, impacts the vehicle's rear wake deformation and, consequently, induces alterations in vehicle aerodynamic performance. The study begins by introducing the designs of fan-type wheel covers that can be mounted on the base rim. We evaluate the ventilation (suction-blowing) performance of these wheels and their impact on the vehicle's aerodynamic performance through wind tunnel tests. Detailed numerical analysis of the flow field within the wheel cover and around the vehicle, resulting from the rotation of these fan-type wheels, is carried out using Computational Fluid Dynamics (CFD) simulations. These simulations utilize the Moving Reference Frame (MRF) method to simulate wheel rotation.
A Drag-Reduction Prediction Model for Truck Platoons
Authors: McAuliffe Brian
Published: April 2024

Truck platooning is an emerging technology that exploits the drag reduction experienced by bluff bodies moving together in close longitudinal proximity. The drag-reduction phenomenon is produced via two mechanisms: wake-effect drag reduction from leading vehicles, whereby a following vehicle operates in a region of lower apparent wind speed, thus reducing its drag; and base-drag reduction from following vehicles, whereby the high-pressure field forward of a closely-following vehicle will increase the base pressure of a leading vehicle, thus reducing its drag.

This paper presents a physics-guided empirical model for calculating the drag-reduction benefits from truck platooning. The model provides a general framework from which the drag reduction of any vehicle in a heterogeneous truck platoon can be calculated, based on its isolated-vehicle drag-coefficient performance and limited geometric considerations. The model is adapted from others that predict the influence of inter-vehicle distance for vehicle platoons, but extends the concept to account for cross winds and for lateral offsets between sequential vehicles, thus permitting its use for a range of modelling and simulation applications. Good agreement with experimental data sets from wind-tunnel and track tests is demonstrated in the paper.
FRAM Optimization: 3D Print Orientation and Concurrent Topology Optimization for Minimize Mass Problem Statements
Authors: Ray Noah , Kim Il Yong
Published: April 2024

Fiber reinforced additive manufacturing (FRAM) is a fused deposition modelling (FDM) additive manufacturing (AM) process which produces composite print layers - polymer matrix and reinforcing fiber. This work proposes a novel method which utilizes FRAM design freedom and simultaneously optimizes 3D print orientation and component topology to improve the response of a mass minimization problem statement. The method is robust and is designed to solve industry-applicable problem statements (mass minimization) with complex geometry and loading. Design sensitivities of 3D print orientation design variables, (θ1, θ2, θ3), are calculated using finite differencing and gradient descent is used to converge to an optimized print orientation. Changing 3D print orientation alters anisotropic material properties to improve the structural response of the component in the prescribed load-cases. The numerical method optimizes the anisotropic material properties of the component and concurrently optimizes topology within the anisotropic state. The method is applied to a case study: a mass minimization problem statement subject to four displacement constraints. Print orientation is iteratively altered, improving response of the displacement constraints by optimizing anisotropic material properties for the applied load-cases of the component. Optimized topology of the component is re-established at each iteration, improving the mass minimization objective function as a result of the print orientation optimization. The solution of the case study is compared to alternative FRAM and metallic solutions to demonstrate the capabilities of the proposed method.
Maximizing FCEV Stack Cooling Performance: Developing a Performance Prediction Model Based on Machine Learning for Evaporative Cooling Radiator
Authors: Lee Dong Keon , Kim Dong Seok , Byun Hyung Suk , Kang Hyun Sung , Shin Yoon Hyuk , Lee Ho Seong
Published: April 2024

Recently, regulations on automobile emission have been significantly strengthened to address climate change. The automobile industry is responding to these regulations by developing electric vehicles that use batteries and fuel-cells. Automobile emissions are environmentally harmful, especially in the case of vehicles equipped with high-temperature and high-pressure diesel engines using compression-ignition, the proportion of nitrogen oxides (NOx) emissions reaches as high as 85%. Additionally, air pollution caused by particulate matter (PM) is six to ten times higher compared to gasoline engines. Therefore, the electrification of commercial vehicles using diesel engines could potentially yield even greater environmental benefits. For commercial vehicles battery electric vehicles (BEVs) require a large number of batteries to secure a long driving range, which reduces their maximum payload capacity. However, fuel-cell electric vehicles (FCEVs) use hydrogen as a fuel to generate electricity, allowing them to achieve a long driving range with relatively fewer batteries. Therefore, FCEVs are more suitable for heavy-duty trucks. However, FCEVs require a significant increase in the number of cooling components to ensure the performance of key parts, including fuel-cell. As a result, the development of a new cooling system is essential in FCEVs to achieve high cooling performance within the constraints of the vehicle package. In this study, we addressed the insufficient fuel-cell cooling performance by harnessing the evaporative cooling effect of exhaust water, a byproduct of fuel-cell power generation, which is injected into the stack cooling radiator using the nozzles. Through test on the ‘Hyundai XCIENT Fuel-Cell’ and conducting 108 times of system evaluations, we confirmed that injecting water into the stack cooling radiator resulted in an additional cooling performance of 4~5°C due to evaporation. We also analyzed the key factors for improving cooling performance through data analysis. Furthermore, we implemented a predictive model, using machine learning techniques such as Python’s PyCaret, to optimize and maximize cooling performance based on ‘cooling perfomance improvement’ and ‘evaporation contrifbution’ when applying the evaporative cooling effect in acutal vehicles.
Study of the Connection between E-Machine and Gearbox of a Hybrid Powertrain
Authors: Hay Maxime , Dutfoy Laurent , Ligier Jean-louis , Merçay Patrice
Published: April 2024

As part of the development of its new powertrain consisting of two electric motors, a combustion engine and a gearbox, Renault SAS followed an original approach to achieve an assembly with an optimized, robust, and reliable link between the main electric motor and the gearbox. The running operation optimization as well as the high reliability is achieved by processing the following topics: filtration of vibrations and operating jolts; solving of tribological problems specific to splined connections, such as fretting corrosion and abrasive tooth wear; avoidance of potential seizure of elements with cyclic relative slippage under load; and eventually, control of wear and tear on the sealing and damping O-rings, which must accept oscillating translational movements at the same time as torque transfer. The aim of this article is to retrace the main steps taken to achieve the desired reliability and performance targets for this type of product. The most remarkable points of this approach are: the modelling and simulation of the behaviour of a misaligned splined connection, with respect to all degrees of freedom of the components being part of the portion of the kinematic chain; the strong links between theoretical and experimental approaches to describe the behaviour of various components such as roller bearings, O-rings, and wave washers; and the quality and richness of the digital model which allows to simulate a wide range of configurations and provide access to essential variables needed for assessing the correct design and operation of the electric motor/gearbox linkage.
Development of a Direct-Injection Heavy-Duty Hydrogen Engine
Authors: Osborne Richard , Hughes John , Loiudice Angela , Penning Richard , Valenta Lukáš
Published: April 2024

Hydrogen-fuelled internal combustion engines (ICEs) offer a zero-carbon fuel option for many applications. As part of the global effort to study hydrogen ICEs Ricardo has developed single-cylinder and multi-cylinder heavy-duty engines.

The engines are representative of a 13 litre Euro VI heavy-duty production application converted to run on hydrogen fuel with limited changes. The engine is fitted with direct hydrogen injectors which enable flexible injection strategies and reduce hydrogen in the intake system. Steady-state testing was carried out over an array of speed and load points covering a typical heavy-duty drive-cycle area.

Engine test results are presented and analysed in this paper. The combustion system can run to values exceeding lambda 5 and 40% exhaust gas recirculation (EGR) can be tolerated. The impact of lambda, EGR, injection and ignition timing variations are presented and demonstrate how the system responds to the corresponding changes in specific heat capacity, mixture preparation, and combustion phasing.

Abnormal combustion events present a sizeable challenge for hydrogen ICEs due to very large knocking pressures and pre-ignition risks. These events are analysed and mitigation measures presented.
A 3-D CFD Study of the Lubricating Oil Flow Path in a Hybrid Vehicle Transmission System
Authors: Mohapatra Chinmoy K. , Schlautman Jeff , Liu Zhe , Raj Gowtham , Gao Haiyang
Published: April 2024

Effective design of the lubrication path greatly influences the durability of any transmission system. However, it is experimentally impossible to estimate the internal distribution of the automotive transmission fluid (ATF) to different parts of the transmission system due to its structural complexities. Hybrid vehicle transmission systems usually consist of different types of bearings (ball bearings, thrust bearings, roller bearings, etc.) in conjunction with gear systems. It is a perennial challenge to computationally simulate such complicated rotating systems. Hence, one-dimensional models have been the state of the art for designing these intricate transmission systems. Though quantifiable, the 1D models still rely heavily on some testing data. Furthermore, HEVs (hybrid electric vehicles) desire a more efficient lubrication system compared to their counterparts (Internal combustion engine vehicles) to extend the range of operation on a single charge. Thus, this paper includes a detailed, transient, three-dimensional CFD analysis of the lubricating oil flow path in an HEV transmission system using the commercial CFD software Simerics-MP+. The modeled transmission system includes scores of bearings, rotating components, and planetary gear systems. Using this modeling framework, we can predict the lubrication state of the various components of the transmission system. Furthermore, this paper reveals the effect of the centrifugal force on the oil distribution and the wetting fraction of different components. Additionally, two different designs of lubricating flow paths inside the roller bearings are explored to study the effect on the wetting of the rollers. The current simulation framework adopts the volume of fluid (VOF) technique to accurately model the two-phase interface development in the rotating systems.
The Development of a Zeolite-Based Cold-Start Catalyst (CSC) for China 6b Vehicles (Conventional & Hybrid) to Meet the Next Chinese Vehicle Emission Standard, Part II
Authors: Xu Lifeng , Zhao Fucheng , Wei Hong , Zhao Pengfei , Zhao Jiajia , Wang Lin , Qian Wangmu , Qian Menghan
Published: April 2024

This is a follow-up report about the development of a cost-effective Palladium (Pd) zeolite-based (HC/NOx trap type) cold-start catalyst (CSC) [1] to meet the future more stringent Chinese vehicle tailpipe emission standard. The impacts of Pd /stabilizer combination within zeolite for the HC/NOx trapping efficiency, the high temperature aging and the durability of the CSCs will be demonstrated by the laboratory results within this paper. The feasibility of a Cu zeolite, a popular non-precious metal ion- zeolite CSC for vehicle applications with respect to cost saving options will be demonstrated. A more complete picture of the effects of PGM/stabilizer within the zeolite to the functions of a CSC will also be summarized in this paper. All results indicate clearly that without the PGM/stabilizer within the zeolite, it would be difficult for the zeolite-based HC/NOx trap type CSC catalyst to be practically used for a vehicle application. The bag and second by second vehicle test results with a Pd/stabilizer-zeolite based CSC showing the decrease in cold-start emissions on a China 6b hybrid vehicle (HEV) will meet the projected future more stringent Chinese tailpipe emission standard. The future development plan for a CSC as a new catalyst technology in vehicle applications will also be outlined.
Analysis of Geo-Location Data to Understand Power and Energy Requirements for Main Battle Tanks
Authors: Patel Mihir , Mittal Vikram
Published: April 2024

Tanks play a pivotal role in swiftly deploying firepower across dynamic battlefields. The core of tank mobility lies within their powertrains, driven by diesel engines or gas turbines. To better understand the benefits of each power system, this study uses geo-location data from the National Training Center to understand the power and energy requirements from a main battle tank over an 18-day rotation. This paper details the extraction, cleaning, and analysis of the geo-location data to produce a series of representative drive cycles for an NTC rotation. These drive-cycles serve as a basis for evaluating powertrain demands, chiefly focusing on fuel efficiency. Notably, findings reveal that substantial idling periods in tank operations contribute to diesel engines exhibiting notably lower fuel consumption compared to gas turbines. Nonetheless, gas turbines present several merits over diesel engines, notably an enhanced power-to-weight ratio and superior power delivery. This analysis underscores the intricate interplay between powertrain selection, operational profiles, and fuel consumption in the pursuit of optimizing modern tank performance and a better understanding of operational sustainment on the battlefield.
VISION: Vehicle Infrared Signature Aware Off-Road Navigation
Authors: Lonari Yashodeep , Naber Jeffrey , Korivi Vamshi , Tison Nathan , Rynes Peter , Yeefeng Ruan
Published: April 2024

Vehicle navigation in off-road environments is challenging due to terrain uncertainty. Various approaches that account for factors such as terrain trafficability, vehicle dynamics, and energy utilization have been investigated. However, these are not sufficient to ensure safe navigation of optionally manned ground vehicles that are prone to detection using thermal infrared (IR) seekers in combat missions. This work is directed towards the development of a vehicle IR signature aware navigation stack comprised of global and local planner modules to realize safe navigation for optionally manned ground vehicles. The global planner used A* search heuristics designed to find the optimal path that minimizes the vehicle thermal signature metric on the map of terrain’s apparent temperature. The local planner used a model-predictive control (MPC) algorithm to achieve integrated motion planning and control of the vehicle to follow the path waypoints provided by the global planner. Vehicle apparent temperature-aware kinodynamic motion planning MPC was developed to minimize the vehicle thermal signature metric -- while respecting local mobility constraints due to the terrain grade to prevent vehicle rollover. Additionally, a surface energy model with the inclusion of a vegetation layer was developed to simulate the apparent temperature of the background terrain. The effectiveness of the developed algorithm is demonstrated for the scenario where the adversarial threat perspective is assumed to be from the top looking down at the vehicle.
Optimal Use Cases for Electric and Hybrid Tactical Vehicles
Authors: Konopa Bridget , Miller Mark , Revnew Luke , Muraco John , Mayfield Logan , Rutledge Maxwell , Crocker Matthew , Mittal Vikram
Published: April 2024

In alignment with the U.S. Army's Climate Strategy and the broader trend in automotive technology, there is a strategic shift towards electrification and hybridization of the vehicle fleet. While a major goal of this effort is to mitigate the carbon footprint of the U.S. Army's vehicle operations, this transition also presents an opportunity to harness advancements in automotive electrification. Among the key vehicles in focus are tactical wheeled vehicles, which provide military forces with versatile and rugged transportation solutions for various combat scenarios, ensuring mobility, protection, and adaptability on the battlefield. This study investigates the potential of electrified tactical wheeled vehicles by conducting a survey involving a diverse group of vehicle operators across various ranks within the U.S. Army. The aim is to identify novel applications achievable through electrification or hybridization, encompassing functions such as establishing command posts, prolonged silent overwatch missions, silent approach to an objective, bivouac operations, and opportunity charging. Complementing the survey insights, geospatial data obtained from the National Training Center sheds light on the real-world operational use of these vehicles. The resulting use cases serve as a foundational framework for deriving potential technical requirements tailored to an electrified tactical wheeled vehicle. By expanding the traditional roles of the tactical wheeled vehicle through electrification, this research contributes to the Army's vision of a more versatile, environmentally conscious, and technologically advanced tactical vehicle fleet.