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 (11,326)
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, BeibeiWang, QiangSong, Fengxiang
As wire control systems advance, they have given rise to a diverse suite of advanced driver assistance services and sophisticated fusion control capabilities. This article presents an innovative strategy for achieving comfortable braking in electric vehicles, propelled by the unwavering goal of enhancing driving experience. By integrating active suspension systems with brake-by-wire technology, the approach ensures that drivers retain their confidence throughout the braking process. The brake-by-wire system adeptly discerns the driver’s braking intent through the pedal’s displacement sensor. Utilizing this technology, we have developed a pioneering function aimed at delivering comfort braking control (CBC). This function not only refines the braking experience but also solidifies the driver’s trust in the braking system. Designed to counteract the head nodding effect during vehicle deceleration, the CBC system minimizes or even eradicates the jarring sensation of pitching for both the
Tian, BoshiLi, LiangLiao, YinshengLv, HaijunQu, WenyingHu, ZhimingSun, Yue
This article explores the utilization of simple-cubic, diamond, octet-truss, and X-type lattice structures for low-pressure turbine blades in engine turbines to enhance natural frequency and decrease overall engine weight while maintaining structural integrity. The research method involves analyzing polylactic acid (PLA) hollow T106C blades with fully infilled and 50–80 location-based lattice arrangements. The study modifies the strut thickness of lattice structures using both constant and variable-based approaches and applies a generalized formula based on relative density to evaluate how changes in lattice thickness and arrangements influence natural frequencies. Furthermore, the investigation extends to multi-lattice configurations, introducing a parameter 𝑘 to signify the transition between different lattices. The modified blades were 3D printed using PLA and tested for natural frequencies through modal testing. The results demonstrate that location-based 50–80 exponential-based
Reewarabundith, Siwachai
Incremental sheet forming is a dieless forming process. Innovative analysis of deformations in the SPIF process, utilizing four distinct sets of deformed structures. Each set consists of four deformed shapes that are categorized as constant and variable tool path, as well as process characteristics including deformed shape, spindle speed, step size, and feed rate. The objective of this article is to investigate the variation of forming force, surface roughness, hardness value, strain rate, forming limit curve (FLC), and strain against forming depth and is to optimize its process parameters. Pyramid frustums have a lower surface roughness than conical frustums. Deformation depth affects hardness at different points along the frustum. The hardness value of the pyramid frustum is often higher than that of the conical frustum. As no single parameter is demonstrated to be significant in determining strain rate, the deformed shape is more relevant than the other process parameters. This
Bhasker, Radhe ShyamKumar, YogeshKumar, SantoshSingh, Rajnish
Intelligent vehicles can utilize a variety of sensors, computing, and control technologies to autonomously perceive the environment and make decisions to achieve safe, efficient, and automated driving. If the speed planning of intelligent vehicles ignores the vehicle dynamics state, it leads to unreasonable planning speed and is not conducive to improving the accuracy of trajectory tracking control. Meanwhile, trajectory tracking usually does not consider the road and speed information beyond the prediction horizon, resulting in poor tracking precision that is not conducive to improving driving comfort. To solve these problems, this study proposes a new longitudinal speed planning method based on variable universe fuzzy rules and designs the piecewise preview model predictive control (PPMPC) to realize the vehicle trajectory tracking. First, the three-degrees-of-freedom vehicle dynamics model and trajectory tracking model are established and verified. Then, the variable universe fuzzy
Zhang, JieTeng, ShipengGao, JianjieZhou, XingxingZhou, Junchao
Widely used as power equipment, diesel engines emit NO x , which significantly threatens the well-being of both the ecosystem and individuals. The SCR system, which is employed to reduce NO x emissions from diesel engines, relies on precise control of the NO x emission levels. Addressing the challenge that traditional NO x emission prediction methods struggle to accurately forecast the emissions under transient operating conditions, this article introduces a deep learning model that integrates CNN, ECA, and BIGRU. The model’s necessary experimental data were collected during the hot phase of the WHTC, and input parameters were screened through correlation analysis. The model employs a CNN for feature extraction, integrates an ECA module to refine key feature processing, and utilizes BIGRU to capture temporal dynamics and dependencies, yielding predictive outcomes. Additionally, the model employs the Adam optimizer and combines it with BWO to adjust hyperparameters, thereby elevating
Peng, YunlongWang, GuiyongWang, YuhuaWang, FeiyangWang, ZhiyuanHe, Shuchao
Parallel hybrid commercial vehicles equipped with automated manual transmissions are extensively utilized in the commercial vehicle sector due to their minimal configuration changes, high energy efficiency, and multi-mode driving capabilities. The key to enhancing the fuel economy of these vehicles lies in the mode switching and gear shift control strategy. To meet the driving requirements of these vehicles and optimize their fuel efficiency, this study introduces a mode switching and gear shift control strategy based on dynamic programming for a parallel hybrid commercial vehicle. First, dynamic programming is applied to the energy management strategy of the hybrid electric vehicle to determine the optimal fuel-efficient power output. Subsequently, the results from dynamic programming simulations are utilized to establish the mode switching boundaries and gear shift patterns. An improved mode switching and gear shift control strategy is then proposed and compared with the control
Zhai, XumaoLi, YujuanJiang, GuangzongYan, ZhengfengYao, MingyaoSun, Yansen
Sustainable aviation fuels (SAFs) derived from renewable sources are promising solutions for achieving carbon neutrality and further controlling aircraft engine emissions, operating costs, and energy security. These SAFs, primarily consist of branched and normal paraffins and exhibit significantly reduced sooting tendencies compared to conventional petroleum-based jet fuels, due to their lack of aromatics content. Our previous study investigated soot formation in non-premixed combustion for three ASTM-approved alternative jet fuels, namely Fischer–Tropsch synthetic paraffinic kerosene (FT-SPK), hydroprocessed esters and fatty acids from camelina (HEFA-Camelina), and alcohol-to-jet (ATJ), and demonstrated that the varying paraffinic composition within SAFs results in diverse sooting propensities, in the order of ATJ > FT-SPK > HEFA-Camelina. To evaluate the impact of iso-paraffins on sooting tendency and validate the suitability of utilizing binary blends of iso-dodecane (iC12) and
Xue, XinSung, Chih-JenWang, Xiaofeng
In this work, the large-angle rotational movement and vibration suppression of a flexible spacecraft are carried out based on an adjustable system. First the spacecraft model is transformed into a canonical affine control form, then two fuzzy systems are used: The first (of Takagi–Sugeno type) estimates the feedback linearization control law as a whole, while the second (of Mamdani type) adjusts and stabilizes the control parameters using the gradient descent technique and based on the minimization of the control error rather than the tracking error. Stability results are presented in terms of Lyapunov’s theory, and simulation tests illustrate the significant transient robustness of the closed-loop system against perturbations, the accurate trajectory control, and vibration suppression of the flexible spacecraft. Consequently, as will be shown later, the error will stay confined and converges quickly to zero, confirming the smoothing property of the proposed method using fuzzy logic
Bahita, Mohamed
Considered as one of the most promising technology pathways for the transport sector to realize the target of “carbon neutral,” fuel cell vehicles have been seriously discussed in terms of its potential for alleviating environmental burden. Focused on cradle-to-gate (CtG) stage, this article evaluates the environmental impacts of fuel cell heavy-duty vehicles of three size classes and three driving ranges to find the critical components and manufacturing processes in the energy context of China. The findings show that the greenhouse gas (GHG) emissions of the investigated fuel cell heavy-duty vehicle range from 47 ton CO2-eq to 162 ton CO2-eq, with the fuel cell system and hydrogen storage system collectively contributing to 37%–56% of the total. Notably, as the driving range increases, the proportion of GHG emissions stemming from fuel cell-related components also rises. Within the fuel cell system, the catalyst layer and bipolar plate are identified as the components with the most
Mu, ZhexuanDeng, YunFengBai, FanlongZhao, FuquanLiu, ZongweiHao, HanLiu, Ming
Adaptive cruise control (ACC) systems have increasingly become more robust in adapting to the motion of the preceding vehicle and providing safety and comfort to the driver. But conventional ACC hangs with a concern for rear-end safety in the presence of traffic or aggressive car maneuvers. It often leads to getting dangerously close to the vehicle behind in scenarios where there is less space and time for the rear vehicle to adjust. This research article develops an ACC approach that considers the rear vehicle in addition to the front vehicle, thereby ensuring safety with the rear vehicle without compromising the safety of the front vehicle. Two novel methodologies are devised to enhance the ACC system. The first approach involves utilizing fuzzy logic to associate the inputs with the throttle and brake based on the inference rules within a fuzzy logic controller overseeing both vehicles. The other utilizes a cascaded model predictive control (MPC) system framework that integrates a
Sharma, VishrutSengupta, SomnathGhosh, Susenjit
A significant amount of chemical fuel energy in internal combustion engines is wasted through exhaust heat. Waste heat recovery (WHR) systems can transform the heat into electrical energy using thermoelectric generators (TEG). This work utilizes a 1D CFD model to demonstrate the potential of TEG-WHR in improving the thermal efficiency of mass-production, compressed natural gas (CNG) engines used in commercial 22-ton heavy-duty trucks. First, the TEG with heat exchanger experiments are performed to measure thermal and electrical performance data under different fin pitches and inlet gas conditions (Re number, temperature, gas flow rate). These data are used to develop and validate a TEG model, which considers user-defined functions of heat transfer and flow friction coefficients to reproduce measured thermal/electrical characteristics of the integrated TEG with its heat exchanger. The engine experiments are conducted based on the speed–torque map (51 test conditions) of the JE05 heavy
Sok, RatnakKusaka, Jin
Connected and autonomous vehicles (CAVs) rely on communication channels to improve safety and efficiency. However, this connectivity leaves them vulnerable to potential cyberattacks, such as false data injection (FDI) attacks. We can mitigate the effect of FDI attacks by designing secure control techniques. However, tuning control parameters is essential for the safety and security of such techniques, and there is no systematic approach to achieving that. In this article, our primary focus is on cooperative adaptive cruise control (CACC), a key component of CAVs. We develop a secure CACC by integrating model-based and learning-based approaches to detect and mitigate FDI attacks in real-time. We analyze the stability of the proposed resilient controller through Lyapunov stability analysis, identifying sufficient conditions for its effectiveness. We use these sufficient conditions and develop a reinforcement learning (RL)-based tuning algorithm to adjust the parameter gains of the
Javidi-Niroumand, FarahnazSargolzaei, Arman
Hydropneumatic Struts (HPS) are widely implemented in automobile, aerospace, and construction industries, mainly for the purpose of vibration and shock absorption. The HPS design with integrated gas–oil chamber is relatively more compact and robust, while mixing gas and oil inside the HPS generates gas–oil emulsion and more nonlinearities. This study formulated a nonlinear analytical model of the compact HPS with gas–oil emulsion, considering the real gas law and pressure-dependent LuGre friction model. The polytropic version of the van der Waals (vdW) method for real gas is applied to represent the thermodynamic behavior of nitrogen. The experimental data were collected at a near temperature of 30°C with three charging pressures under excitations in the frequency range of 0.5–6 Hz, considering two flow connection configurations between chambers as one- and two-bleed orifice. The nonlinear behavior of the gas volume fraction of the emulsion was identified based on peak strut velocity
Seifi, AbolfazlYao, YumengYin, YumingMoore, MasihRakheja, Subhash
This study investigates the influence of tungsten inert gas (TIG) welding parameters on the dilution and hardness of AA5052 aluminum alloy. Employing Taguchi’s L27 orthogonal array, the research systematically explores the effects of current, voltage, and welding speed. Analysis of the experimental data utilizes signal-to-noise ratio, analysis of variance (ANOVA), and regression techniques. The study compares a traditional regression model with a fuzzy logic approach for result validation, finding that the latter exhibits marginally better predictive accuracy. Optimal welding parameters are identified as 150 A current, 20 V voltage, and 45 mm/s welding speed, yielding a maximum dilution of 52.81% and hardness of 145.3 HV 0.5. Current emerges as the most significant factor influencing both dilution and hardness. Microstructural examination, hardness profiling, and tensile testing of specimens welded under optimized conditions reveal a characteristic hardness distribution across the weld
Omprakasam, S.Raghu, R.Balaji Ayyanar, C.
The increased popularity of electric vehicles featuring distributed powertrains is enabling an easy and cost-effective implementation of torque vectoring. This is a renowned technique for controlling vehicle lateral dynamics having the objective of improving both vehicle handling and stability. Nevertheless, the application of torque vectoring at the front axle can increase the difficulty of usual driving tasks. This is because differential longitudinal forces at front tires generate a steering wheel torque, which can be badly perceived by the driver, up to the point of jeopardizing the benefits of having a torque vectoring control. The aim of this article is thus to study in detail the steering torque corruption caused by front axle torque vectoring for proposing some electric power steering control strategies compensating for this effect. Indeed, the electric power steering controllers developed in this study are designed based on the analytical derivation of the torque steer theory
Asperti, MicheleVignati, MicheleSabbioni, Edoardo
Light detection and ranging (LiDAR) sensors are increasingly applied to automated driving vehicles. Microelectromechanical systems are an established technology for making LiDAR sensors cost-effective and mechanically robust for automotive applications. These sensors scan their environment using a pulsed laser to record a point cloud. The scanning process leads in the point cloud to a distortion of objects with a relative velocity to the sensor. The consecutive generation and processing of points offers the opportunity to enrich the measured object data from the LiDAR sensors with velocity information by extracting information with the help of machine learning, without the need for object tracking. Turning it into a so-called 4D-LiDAR. This allows object detection, object tracking, and sensor data fusion based on LiDAR sensor data to be optimized. Moreover, this affects all overlying levels of autonomous driving functions or advanced driver assistance systems. However, since such
Haas, LukasHaider, ArsalanKastner, LudwigKuba, MatthiasZeh, ThomasJakobi, MartinKoch, Alexander Walter
The advantages of magnesium alloy composites over traditional engineering materials include their high strength and lightweight for automotive applications. The proposed work is to compose the AZ61 alloy composite configured with 0–12% silicon nitride (Si3N4) via semisolid-state stir processing assisted with a (sulfur hexafluoride—SF6) inert environment. The prepared AZ61 alloy and AZ61/4% Si3N4, AZ61/8% Si3N4, and AZ61/12% Si3N4 are machined by electrical discharge machining (EDM) under varied source parameters such as pulse On/Off (Ton/Toff ) time (100–115/30–45 μs), and composition of composite. The impact of EDM source parameters on metal removal rate (MRR) and surface roughness (Ra) is measured. For finding the optimum source for higher MRR and good surface quality of EDM surface, the ANOVA optimization tool with L16 design is executed and analyzed via a general linear model approach. With the influence of ANOVA, the Ton/Toff and composite composition found 95.42%/1.27% and 0.36
Venkatesh, R.
This study presents a method for identifying the reliability state of diesel engines by utilizing artificial neural networks (ANNs). The Sulzer 6AL20/24 marine diesel engine was selected as the test subject for this research. Vibration signals were collected during tests conducted on a laboratory test stand under normal operating conditions and during simulations of six different engine faults. Next, the recorded signals were analyzed and transformed into labeled samples for supervised learning. In this phase, the time histories of the vibration signals were divided into segments and augmented, with several key features calculated for each segment. Highly correlated signals were excluded from further analysis based on the Pearson correlation coefficient. The processed samples were then used to train and fine-tune the ANN. The trained ANN was subsequently used to identify the engine’s reliability state and classify the present fault type. To evaluate the effectiveness of the proposed
Pająk, MichałKluczyk, MarcinMuślewski, ŁukaszLisjak, Dragutin
This article provides a comprehensive review of existing literature on AI-based functions and verification methods within vehicular systems. Initially, the introduction of these AI-based functions in these systems is outlined. Subsequently, the focus shifts to synthetic environments and their pivotal role in the verification process of AI-based vehicle functions. The algorithms used within the AI-based functions focus primarily on the paradigm of deep learning. We investigate the constituent components of these synthetic environments and the intricate relationships with vehicle systems in the verification and validation domain of the system. In the following, alternative approaches are discussed, serving as complementary methods for verification without direct involvement in synthetic environment development. These approaches include data-oriented methodologies employing statistical techniques and AI-centric strategies focusing solely on the core deep learning algorithm.
Aslandere, TurgayDurak, Umut
This article presents a height control method for air suspension systems, which are influenced by strong nonlinearity and multiple coupling factors, based on model-free adaptive control (MFAC) using full-form dynamic linearization (FFDL). To address the impact of different damping coefficients of the shock absorber on the height control effect, an improved genetic algorithm is employed to globally optimize the relevant parameters involved in the design of the control law, thereby enhancing the height control performance. The precision of modeling the air suspension system has a direct impact on the simulation of both static and dynamic vehicle models, as well as the accuracy of height control. In this article, an equivalent thermodynamic model of the air suspension system is established based on the principle of energy conservation for height control research. Considering the nonlinearity of the air suspension system and the need to make additional assumptions before modeling, a MFAC
Yao, JiyangWu, GuangqiangWu, JianYang, YuchenYan, Xudong
The application of short burn durations at lean engine operation has the potential to increase the efficiency of spark-ignition engines. To achieve short burn durations, spark-assisted compression ignition (SACI) as well as active pre-chamber (PC) combustion systems are suitable technologies. Since a combination of these two combustion concepts has the potential to achieve shorter burn durations than the application of only one of these concepts, the concept of jet-induced compression ignition (JICI) was investigated in this study. With the JICI, the fuel is ignited in the PC, and the combustion products igniting the charge in the main combustion chamber (MC) triggered the autoignition of the MC charge. A conventional gasoline fuel (RON 95 E10) and a Porsche synthetic fuel (POSYN) were investigated to assess the fuel influence on the JICI. Variations of the relative air/fuel ratio in the exhaust gas (λex) were performed to evaluate both the occurrence of the JICI and the dilution
Burkardt, PatrickGünther, MarcoVillforth, JonasPischinger, Stefan
The aim of the article is to evaluate the effect of the cooling system on the NVH behavior of traction permanent magnets synchronous motors (PMSMs). An effective numerical method is proposed for modeling the fluid–structure interaction in the cooling system of PMSMs. A simplified physical prototype of a cooling jacket of a PMSM is realized by welding two concentric tubes with an internal cavity filled by coolant. A finite element model of the structure is realized. The coolant is modeled as an acoustic domain to account for the fluid–structure interaction in the cavity and a coupled acoustic–structural dynamic problem is solved. The model is validated by experimental modal tests conducted on the prototype of the cooling jacket both with and without the presence of coolant. The validated model is employed to quantify the effect of the cooling system on a real PMSM. The structure of a 10-poles, 12-slots electric machine is modeled by means of finite element method. The model includes the
Barri, DarioSoresini, FedericoBallo, FedericoLucà, FrancescantonioManzoni, StefanoGobbi, MassimilianoMastinu, Giampiero
Verifying training datasets in vision-based vehicle safety applications is crucial to understanding the potential limitations of detection capabilities that may result in a higher safety risk. Vision-based pedestrian safety applications with crash avoidance technologies rely on prompt detection to avoid a crash. This research aims to develop a verification process for vulnerable road user safety applications with vision-based detection functionalities. It consists of reviewing the application’s safety requirements, identifying the target objects of detection in the operational design domain and pre-crash scenarios, and evaluating the safety risks qualitatively by examining the training dataset based on the results of pre-crash scenarios classification. As a demonstration, the process is implemented using open-source pedestrian tracking software, and the pre-crash scenarios are classified based on the trajectories of pedestrians in an example training dataset used in a pedestrian
Hsu, Chung-Jen
The increased connectivity of vehicles expands the attack surface of in-vehicle networks, enabling attackers to infiltrate through external interfaces and inject malicious traffic. These malicious flows often contain anomalous semantic information, potentially leading to misleading control instructions or erroneous decisions. While most semantic-based anomaly detection methods for in-vehicle networks focus on extracting semantic context, they often overlook interactions and associations between multiple semantics, resulting in a high false positive rate (FPR). To address these challenges, the Adaptive Structure Graph Attention Network Model (AS-GAT) is proposed for in-vehicle network anomaly detection. Our approach combines a semantic extractor with a continuously updated graph structure learning method based on attention weight similarity constraints. The semantic extractor identifies semantic features within messages, while the graph structure learning module adaptively updates the
Luo, FengLuo, ChengWang, JiajiaLi, Zhihao
With the extensive production and widespread use of plastics, the issue of environmental pollution caused by plastic waste has become increasingly prominent. Consequently, researchers have been focusing on developing efficient methodologies for upcycling waste plastics and converting them into value-added materials. This hybrid review–conceptual article first provides an overview of strategies for upcycling waste plastic into carbon-capturing materials. It presents carbonization and activation as key steps in converting plastic waste into adsorbent materials and explores strategies for converting common waste plastics. Building upon this foundation, the article introduces and conceptualizes a novel upcycling approach with two manufacturing routes to convert plastic waste into carbon-capturing materials using supercritical fluid (ScF)-assisted injection molding process. It continues by investigating the potential of developing lightweight components made of such carbon-capturing
Pirani, MahdiMeiabadi, Mohammad SalehMoradi, MahmoudEnriquez, Lissette GarciaSreenivasan, Sreeprasad T.Farahani, Saeed
To address the issues of unreasonable collision avoidance path planning algorithms and inadequate safety in high-speed scenarios, a trajectory prediction-based collision avoidance path planning algorithm has been proposed. First, a trajectory prediction model is constructed using the long–short-term memory (LSTM) network, and the trajectory prediction model is trained and tested with the HighD dataset. Second, the future trajectory of the obstacle car is predicted, the future trajectory information of the two cars is combined to generate the lane-changing decision, and the three-times B-spline curves are used to generate the collision avoidance path clusters. The optimal collision avoidance paths are generated based on the multi-objective optimization function. Finally, build a MATLAB/CarSim simulation platform to verify the reasonableness and safety of the planned paths by taking the three scenarios of the continuous overtaking, preceding car pulling out, and the neighboring car
Liu, Xiao LongZhang, LeiLi, Peng KunXie, RuWang, QingLi, Ran Ran
As countries around the world attach more importance to carbon emissions and more stringent requirements are put forward for vehicle emissions, hybrid vehicles, which can significantly reduce emissions compared with traditional fuel vehicles, as well as low-viscosity lubricating oil, have become significant trends in the industry. In this article, a total of nine vehicles of 48 V mild-hybrid models and full-hybrid models are tested. Using three kinds of low-viscosity lubricating oil and driving a total of 120,000 km in environments with low temperature, high humidity, high temperature, or high altitude, the engines are then disassembled and scored. The effects of the four extreme environments on the engine starts–stops, ignition advance angle, engine power, state of charge (SOC), acceleration performance, and oil consumption characteristics of hybrid vehicles are studied; the oxidation characteristics and iron content change characteristics of low-viscosity lubricating oil are analyzed
Zhu, GezhengtingHu, HuaPan, JinchongLuo, YitaoHua, LunJiao, YanJiang, JiandiShao, HengXu, ZhengxinYan, JingfengWei, GuangyuanZhang, Heng
Due to manufacturing, assembly, and actuator wear, slight deviations between the actual and logical positions of various gears in a transmission system may accumulate, affecting shift quality, reducing shift accuracy, and causing operational anomalies. To address this issue, a self-learning method based on the top dead center (TDC) and lower dead center (LDC) was proposed, specifically for the hybrid gearbox of an electric torque converter (eTC) module and a double-input shaft gearbox (DIG). The linear active disturbance rejection control (LADRC) method was employed to estimate and manage the nonlinear resistance during the motion of the shifting motor. To simplify the controller parameter problem, the nutcracker optimization algorithm (NOA) was utilized to tune the LADRC parameters, thereby optimizing the position self-learning process. The control strategy was modeled using MATLAB/SIMULINK, and its reasonableness was verified through hardware-in-the-loop (HIL) tests. Based on these
Hong, HanchiQuan, Kangningd’Apolito, LuigiXu, Li
From biology, to genetics, and paleontology, these fields share the DNA as a common and time-proven tool. In science, pressure may be such a tool, shared by thermodynamics, material science, and astrophysics, but not by aerodynamics. Pressure is a shorthand for a force acting perpendicular to a surface. When this surface is reduced to zero, so should the pressure. The wing area of an aircraft acts as a reference area to calculate its parasite drag coefficient. In this scenario, the parasite drag acts as a force over the wing area. If the wing area is reduced to zero, its parasite drag does not, as the fuselage is still generating parasite drag. The ratio of the parasite drag and wing area is an example of a pressure construct that uses a physically irrelevant reference area and has no absolute zero. Pressure constructs, more frequently used than pressures in aerodynamics, are a math-based parameter that preserve dimensional propriety according to the Buckingham Pi theorem but lacks a
Burgers, Phillip
Accurate and responsive trajectory tracking is a critical challenge in intelligent vehicle control system. To improve the adaptability and real-time performance of intelligent vehicle trajectory tracking controllers, we propose a genetic algorithm adaptive preview (GAAP) scheme that offline optimizes the preview distance based on vehicle speed and reference path curvature. The goal is to obtain the optimal preview distance that balances tracking accuracy, stability, and real-time performance. By establishing a relationship between optimal preview distance, speed, and curvature, we enhance real-time performance through online table checking during trajectory tracking. Our trajectory tracking error model takes into account not only position errors but also heading errors. A feedback–feedforward trajectory tracking controller is then designed to achieve rapid responses without compromising robustness. Simulation tests conducted under straight circular arc condition and double lane change
Cheng, KehanZhang, HuanhuanHu, ShengliNing, Qianjia
In order to deploy renewable energy sources for balanced power generation and consumption, batteries are crucial. The large weight and significant drain on the energy efficiency of conventional batteries urge the development of structural batteries storing electrical energy in load-bearing structural components. With the current shift to a green economy and growing demand for batteries, it is increasingly important to find sustainable solutions for structural batteries as well. Sustainable structural batteries (SSBs) have strong attraction due to their lightweight, design flexibility, high energy efficiency, and reduced impact on the environment. Along with sustainability, these structural batteries increase volumetric energy density, resulting in a 20% increase in efficiency and incorporate energy storage capabilities with structural components, realizing the concept of massless energy storage. However, the significant problems in commercializing SSBs are associated with their
Kusekar, Sambhaji KashinathPirani, MahdiBirajdar, Vyankatesh DhanrajBorkar, TusharFarahani, Saeed
The comfort of seats increasingly becomes a crucial factor in the overall driving experience, particularly as vehicles become increasingly integrated into people’s daily lives. Passengers often maintain a relatively fixed posture and have close contact with the seat for extended periods of time, leading to issues such as heat, humidity, and stickiness. In order to enhance the thermal comfort experienced by occupants, manufacturers are no longer satisfied with ensuring the thermal comfort performance of vehicles only through the HVAC system in the cabin, but also developed a microclimate control seat that adjusts the temperature through ventilation between the contact surface of the seat and the human body, trying to improve the thermal comfort of passengers more effectively. However, the ventilation ducts of these seats are commonly designed based on empirical or autonomous standards, and their effectiveness is subsequently assessed through test or simulation, typically under unloaded
Zhang, TianmingRen, JindongZhang, Haonan
Letter from the Guest Editors
Farahani, SaeedVargas-Silva, GustavoKazan, HakanMoradi, MahmoudMedina, Carlos
2023–2024 Reviewers
Pilla, Srikanth
Cooperation lies at the core of multiagent systems (MAS) and multiagent reinforcement learning (MARL), where agents must navigate between individual interests and collective benefits. Advanced driver assistance systems (ADAS), like collision avoidance systems and adaptive cruise control, exemplify agents striving to optimize personal and collective outcomes in multiagent environments. The study focuses on strategies aimed at fostering cooperation with the aid of game-theoretic scenarios, particularly the iterated prisoner’s dilemma, where agents aim to optimize personal and group outcomes. Existing cooperative strategies, such as tit-for-tat and win-stay lose-shift, while effective in certain contexts, often struggle with scalability and adaptability in dynamic, large-scale environments. The research investigates these limitations and proposes modifications to align individual gains with collective rewards, addressing real-world dilemmas in distributed systems. By analyzing existing
Nidamanuri, JaswanthSathi, VaigaraiShaik, Sabahat
Letter from the Focus Issue Editors
Lakhlani, HardikKumar, VivekWenbin, YuBagga, KalyanGundlapally, SanthoshDi Blasio, GabrieleSplitter, DerekRajendran, Silambarasan
Aerospace engineering programmes typically cover airworthiness philosophies, principles, structures, processes, and procedures. The industry has recently recognized the need to enhance the graduate engineers’ skills around airworthiness. This has led to introduction of standards acting as guides for developing curricula and content for university airworthiness courses. Concept maps, a visual mapping of concepts in a hierarchical way, enjoy wide use in engineering education (teaching and assessment). Airworthiness courses are both technical and legalistic, presenting challenges to students when it comes to understanding complex and intertwined regulations. Schematic representations of concepts can foster the cognitive processes of learning. Concept maps can assess efficiently and comprehensively a multitude of airworthiness topics. This study examines the feasibility of applying concept maps in airworthiness education. Fill-in-a-map concept maps were developed as assessment tools for an
Kourousis, KyriakosChatzi, Anna
2023–2024 Reviewers
Ryan, Tom
The flow structure and unsteadiness of shock wave–boundary layer interaction (SWBLI) has been studied using rainbow schlieren deflectometry (RSD), ensemble averaging, fast Fourier transform (FFT), and snapshot proper orthogonal decomposition (POD) techniques. Shockwaves were generated in a test section by subjecting a Mach = 3.1 free-stream flow to a 12° isosceles triangular prism. The RSD pictures captured with a high-speed camera at 5000 frames/s rate were used to determine the transverse ray deflections at each pixel of the pictures. The interaction region structure is described statistically with the ensemble average and root mean square deflections. The FFT technique was used to determine the frequency content of the flow field. Results indicate that dominant frequencies were in the range of 400 Hz–900 Hz. The Strouhal numbers calculated using the RSD data were in the range of 0.025–0.07. The snapshot POD technique was employed to analyze flow structures and their associated
Datta, NarendraOlcmen, SemihKolhe, Pankaj
2023–2024 Reviewers
Sandu, Corina
The twin challenges of the automotive industry namely petroleum dependence and environmental pollution paved way for the development of an environmentally friendly and feasible substitute for diesel, possessing power characteristics equivalent to those of a diesel engine. Biofuel has potential as a renewable energy source, offering a more sustainable alternative to traditional fossil fuels. However, it does come with some challenges, such as varying quality and combustion properties. To enhance its performance, engines can be fine-tuned by adjusting fuel injection parameters, such as timing, pressure, and duration. Accordingly, this research article focuses on optimizing the fuel injection parameters for a CRDi engine powered by D+LPO (20% lemon peel oil and 80% diesel) biofuel, with the goal of improving both performance and emission characteristics. The experimental design matrix was generated using Design Expert-13 software, employing the I-optimal technique. Utilizing response
Saiteja, PajarlaAshok, B.
Thoracic injuries, most frequently rib fractures, commonly occur in motor vehicle crashes. With an increased reliance on human body models (HBMs) for injury prediction in various crash scenarios, all thoracic tissues and structures require more comprehensive evaluation for improvement of HBMs. The objective of this study was to quantify the contribution of costal cartilage to whole rib bending properties in physical experiments. Fifteen bilateral pairs of 5th human ribs were included in this study. One rib within each pair was tested without costal cartilage while the other rib was tested with costal cartilage. All ribs were subjected to simplified A-P loading at 2 m/s until failure to simulate a frontal thoracic impact. Results indicated a statistically significant difference in force, structural stiffness, and yield strain between ribs with and without costal cartilage. On average, ribs with costal cartilage experienced a lower force but greater displacement with a longer time to
Schaffer, RoseKang, Yun-SeokMarcallini, AngeloPipkorn, BengtBolte, John HAgnew, Amanda M
Traditional pedestrian detection methods have poor robustness. Deep learning-based methods have shown high performance in recent years but rely on substantial computational resources. Developing a lightweight, deep learning-based pedestrian detection algorithm is essential for applying deep learning-based algorithms in resource-limited scenarios, such as driverless and advanced driver assistance systems. In this article, an improved model based on YOLOv3 called “YOLOPD” (You Only Look Once—Pedestrian Detection), is proposed. It is obtained by constructing a self-attentive module, introducing a CIOU (Complete Intersection over Union) loss function and a depth separated convolutional layer. Experimental results show that on the INRIA (National Institute for Research in Computer Science and Automation), Caltech, and CityPerson pedestrian dataset, the MR (miss rate) of the model YOLOPD is better than that of the original YOLOv3 model, and the number of parameters is reduced by about 1/3
Li, ShanglinWang, Qi FengLi, Ren FaXiao, Juan
Throughout the vehicles industry and electrification, vehicle ride comfort, road holding, and fuel/charge economy have always been important considerations for the design and development of shock absorbers. Vehicle suspension is one of the oscillating power dissipation sources in which the undesired mechanical energy is dissipated into heat waste. Therefore, in this study a regenerative MacPherson strut is modeled and validated to investigate the vehicle vertical dynamics performance as well as the harvestable power that can be used to charge batteries or power vehicle electrical loads. The optimal design parameters of the regenerative MacPherson strut (RE.M.S) is obtained by using multi-object genetic algorithm (MOGA) optimization for a better trade-off between regenerated power, ride comfort, and road holding. The results showed that RE.M.S can function as a semi-active shock absorber as change of duty cycle of charging circuit. Furthermore, the optimal selection of the design
Hegazy, Ahmed H.A.Kaldas, Mina M.Soliman, Aref M.A.Huzayyin, A.S.
Design validation plays a crucial role in the overall cost and time allocation for product development. This is especially evident in high-value manufacturing sectors like commercial vehicle electric drive systems or e-axles, where the expenses related to sample procurement, testing complexity, and diverse requirements are significant. Validation methodologies are continuously evolving to encompass new technologies, yet they must be rigorously evaluated to identify potential efficiencies and enhance the overall value of validation tests. Simulation tools have made substantial advancements and are now widely utilized in the development phase. The integration of simulation-based or simulation-supported validation processes can streamline testing timelines and sample quantities, all the while upholding quality standards and minimizing risks when compared to traditional methods. This study examines various scenarios where the implementation of advanced techniques has led to a reduction in
Leighton, MichaelTuschkan, AlwinPlayfoot , Ben
2023–2024 Reviewers
Hardy, Warren
Items per page:
1 – 50 of 11326