This specification establishes the requirements for the following types of self-locking nuts in thread diameter sizes 0.1380 through 0.6250 inch: a Wrenching Nuts: i.e., hexagon, double hexagon, and spline nuts. b Anchor Nuts: i.e., plate nuts, gang channel nuts, and shank nuts. The wrenching nuts, shank nuts, and nut elements of plate and gang channel nuts are made of a corrosion- and heat-resistant nickel-base alloy of the type identified under the Unified Numbering System as UNS N07001 and of 180000 psi axial tensile strength at room temperature, with maximum conditioning of parts at 1400 °F prior to room temperature testing.

E-25 General Standards for Aerospace and Propulsion Systems

Multi-Stage Registration and Feature Based Robust and Precise LiDAR SLAM

2025-01-7161

02/21/2025

In a complex and ever-changing environment, achieving stable and precise SLAM (Simultaneous Localization and Mapping) presents a significant challenge. The existing SLAM algorithms often exhibit limitations in design that restrict their performance to specific scenarios; they are prone to failure under conditions of perceptual degradation. SLAM systems should maintain high robustness and accurate state estimation across various environments while minimizing the impact of noise, measurement errors, and external disturbances. This paper proposes a three-stage method for registering LiDAR point cloud. First, the multi-sensor factor graph is combined with historical pose and IMU pre-integration to provide a priori pose estimation; then a new method for extracting planar features is used to describe and filter the local features of the point cloud. Second, the normal distribution transform (NDT) algorithm is used as coarse registration. Third, the feature to feature registration is used for

Li, Zhichao, Tong, Panpan, Shi, Weigang, Bi, Xin

Space-Time Evolution of Temperature of Asphalt Mixture during Transportation

2025-01-7171

02/21/2025

Temperature segregation significantly affects the compaction of asphalt mixtures and the durability of the asphalt pavement layer. Uneven cooling of the mixture during transportation is a key factor contributing to temperature segregation. This study uses finite element simulations to analyze the temporal and spatial temperature evolution during the transportation of asphalt mixtures. A temperature segregation evaluation index (TSIv) is proposed to assess the significance of various factors affecting segregation. Support vector regression (SVR), random forest regression (RFR), and extreme gradient boosting (XGBoost) models are employed to predict temperature changes during transportation and optimize the predictive models. The results indicate that the proportion of areas with a temperature difference of less than 10°C is consistently the highest, followed by areas with a temperature difference greater than 25°C, and then those with temperature differences in the ranges of 10-16°C and

Cheng, Hao, Ma, Tao, Tang, Fanlong, Fan, Jianwei

Evaluation Method for the Impacts of Truck Platoons Lateral Control on Pavement Performance

2025-01-7152

02/21/2025

The introduction of autonomous truck platoons is expected to result in drastic changes in operational characteristics of freight shipments, which may in turn have significant impacts on efficiency, energy consumption, and infrastructure durability. Since the lateral positions of autonomous trucks traveling consecutively within a lane are fixed and similar (channelized traffic), such platooning operations are likely to accelerate damage accumulation within pavement structures. To further advance the application of truck platooning technology in various pavement environments, this study develops a flexible evaluation method to evaluate the impact of lateral arrangement within autonomous truck platoons on asphalt pavement performance. This method simplifies the impact of intermittent axle load applications along the driving direction within a platoon, supporting platoon controllers in directly evaluating pavement damage for different platoon configurations. Specifically, a truck platoon

Wenlu, Yu, Ye, Qin, Chen, Daoxie, Min, Yitong, Chen, Leilei

A Traffic Conflict Risk Assessment Model for Highway Construction Zones Based on Trajectory Data

2025-01-7217

02/21/2025

Highway construction zones present substantial safety challenges due to their dynamic and unpredictable traffic conditions. With the rising number of highway projects, limited accident data during brief construction phases underscores the need for alternative safety evaluation methods, such as traffic conflict analysis. This study addresses vehicular safety issues within the Kunshan section of the Shanghai-Nanjing Expressway, focusing on conflict risk assessment through a spatio-temporal analysis of a construction zone. Using drone-captured video, vehicle trajectories were extracted to derive key operational indicators, including speed and acceleration, providing a spatio-temporal foundation for analyzing traffic flow and conflict dynamics. A novel **Comprehensive Collision Risk Index (CCRI)** was introduced, integrating Time-to-Distance-to-Collision (TDTC) and Enhanced Time-to-Collision (ETTC) metrics to enable a multidimensional assessment of conflict risk. The CCRI captures both

Zhang, Yuwen, Guo, Xiucheng, Ma, Yuheng

Regulatory and Policy Framework for Urban Drone Logistics Systems

2025-01-7144

02/21/2025

The swift and relentless progression of drone technology has ushered in novel opportunities within the realm of urban logistics, especially for the potential of drones to modify last-mile delivery and improve customer fulfillment through mobile application integration, offering the potential for delivery systems that are both efficient and environmentally sustainable. This development is not just a technological leap but a transformative shift in how goods are moved within urban spaces, potentially reducing traffic congestion and emissions from traditional vehicles. Nevertheless, the safety issues of drone flights in cities are becoming increasingly serious, and the accountability related to drone accidents is not clear, raising concerns in society regarding the use and safety of drones. Therefore, to fully utilize the potential of drones in urban logistics, the incorporation of drones into the urban airspace environment necessitates the establishment of a strong regulatory and policy

Ma, Jie, Yang, Junjie, Diao, Weile, Du, Yiling, Chen, Weiqi

Study on the Minimum Diversion Decision Distance of Autonomous Vehicle on Freeway Based on Lane-Changing Trajectory Modelling

2025-01-7170

02/21/2025

Most autonomous vehicles employ a relatively conservative lane-changing strategy in freeway system. In the diversion areas, autonomous vehicles typically initiate lane-changing to curb lanes at lower speeds at a considerable distance from the diversion point, resulting in a decrease in the overall traffic efficiency within the diversion areas. However, lane-changing decision points excessively close to exit ramps can exacerbate the urgency of the lane-changing process, prompting irrationally forced lane-changing and increasing the collision risk. To provide decision-making references for the safe and rapid diverging of autonomous vehicles in freeway diversion areas, this study proposes a minimum diversion decision distance (MDDD) model for autonomous vehicles through microscopic lane-changing trajectory data. Specifically, the lane-changing process was divided into waiting for the acceptable gap stage and executing the lane-changing stage in this model. Subsequently, UAV aerial

Li, ZhenFa, Luo, BaoGuo, Yang, Qi, Chen, Xu, Pan, BingHong

Semantic Segmentation of Lane Lines for Pix2Pix Network Introducing Ghost Module

2025-01-7208

02/21/2025

Technology for lane line semantic segmentation is crucial for ensuring the safe operation of intelligent cars. Intelligent cars can now comprehend the distribution and meaning of scenes in an image more precisely thanks to semantic segmentation, which calls for a certain degree of accuracy and real-time network performance. A lightweight module is selected, and two previous models are improved and fused to create the lane line detection model. Finally, experiments are conducted to confirm the model's efficacy. This paper proposes a lightweight replacement program with the aim of addressing the issue of large parameterization in the generative adversarial network (GAN) model and difficult training convergence. The overall network structure is selected from the Pix2Pix network in the conditional generative adversarial network, and the U-net network of the generator is cut and replaced by the Ghost Module, which consists of a modified downsampling module that enhances the global fusion

Yang, Kun, Wang, Jian

Fleet Sizing and Relocation Strategies for Shared Autonomous Vehicles under Uncertainty: A Two-Stage Robust Optimization Approach

2025-01-7192

02/21/2025

Shared autonomous vehicles systems (SAVS) are regarded as a promising mode of carsharing service with the potential for realization in the near future. However, the uncertainty in user demand complicates the system optimization decisions for SAVS, potentially interfering with the achievement of desired performance or objectives, and may even render decisions derived from deterministic solutions infeasible. Therefore, considering the uncertainty in demand, this study proposes a two-stage robust optimization approach to jointly optimize the fleet sizing and relocation strategies in a one-way SAVS. We use the budget polyhedral uncertainty set to describe the volatility, uncertainty, and correlation characteristics of user demand, and construct a two-stage robust optimization model to identify a compromise between the level of robustness and the economic viability of the solution. In the first stage, tactical decisions are made to determine autonomous vehicle (AV) fleet sizing and the

Li, Kangjiao, Cao, Yichi, Zhou, Bojian, Wang, Shuaiqi, Yu, Yaofeng

VMD-CNN-BiGRU Model for Vehicle Fuel Consumption Prediction Considering Spatial-Functional Road Characteristics

2025-01-7211

02/21/2025

To accurately predict the fuel consumption of vehicles, this study proposes a vehicle fuel consumption prediction model based on the VMD-CNN-BiGRU algorithm by considering six road spatial features such as road grades, one-way road attributes and intersection attributes. First, the VMD algorithm is employed to reduce the nonlinearity and nonsmoothness of the raw data by determining the optimal number of VMD decomposition modes. Then, the CNN-BiGRU algorithm is used to predict each modal component after decomposition, and the obtained prediction results are compared and analyzed with the prediction results of existing CNN-BiGRU, EMD-CNN-BiGRU and EEMD-CNN-BiGRU models. The results show that the VMD-CNN-BiGRU model significantly outperforms other models in terms of prediction performance and can accurately capture the trend of vehicle fuel consumption, thus effectively verifying the superiority and feasibility of the model. In addition, this study provides an in-depth analysis of the

Gao, Yating, Yan, Lixin, Deng, Guangyang, Chen, Siyuan

SAE TOMORROW TODAY: Optimizing Energy Data for the Cold Supply Chain

1350102/10/2025

The growing complexity of fleet electrification has highlighted the importance of understanding how energy is used and where you can reduce waste. To optimize energy intensity at industrial facilities, one company is leveraging integrated data and AI-powered intelligence to reduce both cost and fleet-related emissions, particularly when it comes to cold storage supply chains. Ndustrial helps companies lower energy intensity, decrease costs, and increase sustainable industrial operations with solutions like the Nsight Energy Intensity Platform, a data analytics and monitoring solution central to the management of electric transport refrigeration unit (eTRU) power systems. To learn more, we sat down with Manuel Aguirre VP of Supply Chain Electrification, to discuss Ndustrial's energy optimization solutions and the importance of efficient refrigeration management throughout the cold storage supply chain. We'd love to hear from you. Share your comments, questions and ideas for future

Hineman, Marcie

Contact, Wire Barrel, Crimp Type

AS5261A (Current)

02/08/2025

This specification provides dimensional standards for crimp type contact wire barrel design and is a replacement for MS3190. Some wire barrel designs may exist in AS39029 but are not considered approved for future use, therefore, will not appear in this specification. The crimp barrel sizes listed in this document have been standardized in AS39029 and AS22520 specifications, tools and contacts are available to support these listed sizes. These crimp barrel requirements shall be used for any contact, regardless of whether it is a standard or non-standard contact configuration. The specification lists details for three types of wire barrels: A, B, and C. Wire barrel type A is not recommended for new design. Table 4 lists each AS39029 detail sheet wire barrel type.

AE-8C1 Connectors Committee

PACKING, PREFORMED - MS28775 O-RING

AS28775A (Current)

02/08/2025

A-6C2 Seals Committee

Influence of Fibre Weight Fraction on the Mechanical Characteristics of the Caryota Urens Fiber Reinforced Polyester Composite

2025-28-0114

02/07/2025

The present study aims to assess the tensile properties of Caryota urens fibre reinforced polyester composites. Composites were fabricated with different fiber weight fractions starting from 5% to 35% with 5% increment. The mechanical testing of composite material was conducted using ASTM standards. The results indicated that the tensile, impact, and flexural properties of composite material were increased up to 25% fiber weight fraction; after that, they have been reduced due to some factors, like fiber distribution, which may not be uniform, and adhesion between fiber and matrix may be reduced. The optimal weight fraction of caryota urens fiber found from this study is 25%. The maximum tensile, impact, and flexural strength obtained for the composites were 36.22 MPa, 62.21 MPa, and 0.224 N/m, respectively. Water absorption characteristics show the increase of water intake behavior of composites due to their hydrophobic nature.

Santhanam, K, Raja, K., Naveen, M, Saranbala, M, M, Naveenkumar

Overview of Blockchain-Based Digital Authorized Release Certificate

AIR7123 (Current)

01/21/2025

The scope of this document is to provide an overview, process, and implementation guidance on use of blockchain technology for a secure, immutable, and traceable digital authorized release certificate. This document does not standardize the process nor is it meant for authorities to recognize the standard as an acceptable means of recording data collected through the required authorized release certificate (ARC) tags.

G-31 Digital Transactions for Aerospace

SAE TOMORROW TODAY - Matching Buyers & Sellers to Advance SDV Development

1349701/16/2025

From evolving consumer expectations to changing business models to updates to the car itself, there is no doubt that software is radically transforming the automotive industry--and companies must adapt now or risk being left behind. The rise of smartphones has permanently altered consumer expectations, and software-defined vehicles (SDVs) are expected to provide experiences akin to those found on mobile devices. Preferences for infotainment and safety features through advanced driver-assistance systems (ADAS) are also increasingly central to purchase decisions. In an effort to meet these demands and accelerate the development of SDVs, SDVerse was developed as a B2B sales marketplace for buyers and sellers of automotive software. The matchmaking platform is available to all OEMs, suppliers, and other companies with relevant software offerings and tools. To learn more, we sat down with Prashant Gulati, Chief Executive Officer, to discuss the role of SDVerse in the automotive industry's

Hineman, Marcie

Episode 253 - Building a Better EV Battery Supply Chain

WC-0177601/07/2025

Challenges in Cost Reduction for Automotive Parts: A Comprehensive Analysis

2024-36-0174

12/20/2024

The automotive industry is facing unprecedented pressure to reduce costs without compromising on quality and performance, particularly in the design and manufacturing. This paper provides a technical review of the multifaceted challenges involved in achieving cost efficiency while maintaining financial viability, functional integrity, and market competitiveness. Financial viability stands as a primary obstacle in cost reduction projects. The demand for innovative products needs to be balanced with the need for affordable materials while maintaining structural integrity. Suppliers’ cost structures, raw material fluctuations, and production volumes must be considered on the way to obtain optimal costs. Functional aspects lead to another layer of complexity, once changes in design or materials should not compromise safety, durability, or performance. Rigorous testing and simulation tools are indispensable to validate changes in the manufacturing process. Marketing considerations are also

Oliveira Neto, Raimundo Arrais, Souza, Camila Gomes Peçanha, Brito, Luis Roberto Bonfim, Guimarães, Georges Louis Nogueira

Recycling and Resynthesis of Cathode Materials from Lithium-Ion Batteries for EVs

2024-36-0110

12/20/2024

The cost of electric vehicles (EVs) is significantly influenced by lithium-ion batteries, which typically account for about 40% of the total price, primarily due to the critical minerals content. Notably, minerals for cathode production are prone to scarcity and market price fluctuations. Moreover, the extraction of these minerals through mining activities poses substantial environmental challenges, including carbon emissions and resource depletion. In response to these concerns, recycling emerges as strategic to ensure the sustainability of electrification and secure the mineral supply chain. This paper presents findings from a study on recycling EV batteries using hydrometallurgical processes, encompassing the resynthesis of cathode materials utilizing recycled resources. The hydrometallurgical method exhibited an extraction efficiency surpassing 90%, with no direct CO2 emissions. Validation of the resynthesis phase involved the fabrication of cells with resynthesized cathodes

Obara, Rafael Brisolla, Erthal, Leopoldo, Souza, Cleiton Oliveira, Roggerio, Leonardo, Freitas, Heverson Renan, Lima, Ana Luiza Lorenzen, Bassani, Jean Carlos

Multi Criteria Analysis Selection of Cylindrical Spur Gears

2024-36-0117

12/20/2024

Organizations need to maintain their processes at high levels of efficiency to be competitive, asset management and industrial maintenance are extremely important to obtain positive results in optimizing operating costs, saving energy resources, reduction of environmental impacts among other characteristics that are considered differential for organizations. In this scenario, methods are increasingly being sought to assist managers in decision-making processes that contain several alternatives and selection criteria involved. The AHP and TOPSIS methods have been widely associated with prioritization studies, cost evaluation, resource selection, suppliers, among others. Thus, the selection of equipment and industrial elements can be evaluated by means of multicriteria decision methods where the criteria considered important by specialists in the area are inserted into the model. The objective of this article was to present a selection process for spur gears based on stress analysis and

de Oliveira, Geraldo Cesar Rosario, de Oliveira, Vania Aparecida Rosario, Silva, Carlos Alexis Alvarado, Guidi, Erick Siqueira, Salomon, Valério Antonio Pamplona, Rosado, Victor Orlando Gamarra, de Azevedo Silva, Fernando

Integrating Agenda 2030 with Lean practices and Industry 4.0 Technologies: Case Study in an Automotive Industry

2024-36-0043

12/20/2024

Competitive companies constantly seek continuous increases in productivity, quality and services level. Lean Thinking (LT) is an efficient management model recognized in organizations and academia, with an effective management approach, well consolidated theoretically and empirically proven Within Industry 4.0 (I4.0) development concept, manufacturers are confident in the advantages of new technologies and system integration. The combination of Lean and I4.0 practices emerges from the existence of a positive interaction for the evolutionary step to achieve a higher operational performance level (exploitation of finances, workload, materials, machines/devices). In this scenario where Lean Thinking is an excellent starting point to implement such changes with a method and focus on results; that I4.0 offers powerful technologies to increase productivity and flexibility in production processes; but people need to be more considered in processes, in a context aligned with the Industry 5.0

Braggio, Luis, Marinho, Osmar, Soares, Luis, Lino, Alan, Rabelo, Fábio, Muniz, Jorge

Advanced Design Validation Planning Techniques for Commercial Vehicle E-Axles

02-17-04-0024

12/16/2024

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, Michael, Tuschkan, Alwin, Playfoot , Ben

Energy Management Strategy Based on Fast Dynamic Programming for Extender Range Electric Logistics Vehicle

2024-01-7039

12/13/2024

The computational efficiency of dynamic programming (DP) energy management strategies is enhanced through the discretization of state variables in this study. The upper and lower bounds of SOC (State of Charge) and the SOC variation at each moment are calculated using the maximum and minimum power of the range extender, which eliminates invalid state combinations and significantly reduces the size of the feasible state set. To investigate the impact of different sampling intervals on SOC during various phases, intervals at 1s, 2s, 4s, 5s, and 10s are set for both charge retention and consumption phases. It is revealed that in the consumption phase, different sampling intervals minimally affect SOC, with trajectories closely matching. However, in the charge retention phase, the impact of different sampling intervals on SOC is significant, resulting in considerable differences in SOC trajectories. Additionally, in the charging-discharging (CD) phase, fuel consumption significantly varies

Wei, Changyin, Wei, Yiyu, Yang, Dinghao, Wang, Yichen, Liu, Dezheng

A Fuzz Testing Method Based on DDPM for Intelligent Connected Vehicles CAN Communication

2024-01-7044

12/13/2024

Modern vehicles are increasingly integrating electronic control units (ECUs), enhancing their intelligence but also amplifying potential security threats. Vehicle network security testing is crucial for ensuring the safety of passengers and vehicles. ECUs communicate via the in-vehicle network, adhering to the Controller Area Network (CAN) bus protocol. Due to its exposed interfaces, lack of data encryption, and absence of identity authentication, the CAN network is susceptible to exploitation by attackers. Fuzz testing is a critical technique for uncovering vulnerabilities in CAN network. However, existing fuzz testing methods primarily generate message randomly, lacking learning from the data, which results in numerous ineffective test cases, affecting the efficiency of fuzz testing. To improve the effectiveness and specificity of testing, understanding of the CAN message format is essential. However, the communication matrix of CAN messages is proprietary to the Original Equipment

Shen, Lin, Xiu, Jiapeng, Zhang, Zhuopeng, Yang, Zhengqiu

Unsettled Issues Regarding Electric Vehicle Battery Recycling

EPR2024030

12/12/2024

In today's world, the electric vehicle (EV) industry is experiencing a remarkable boom with increasing global demand. With it, comes the surging and unprecedented need for EV batteries. Recycling these batteries has become of crucial importance, as it not only plays a vital role in ensuring the security of the battery supply chain but also serves as a key measure for reducing greenhouse gas emissions. However, there are still several issues that remain unresolved in this domain. Unsettled Issues Regarding Electric Vehicle Battery Recycling delves deep into these issues, thoroughly exploring the current state of the industry and potential solutions to drive sustainable EV battery recycling. By addressing these challenges, we can strive towards a more sustainable future in the EV sector. Click here to access the full SAE EDGETM Research Report portfolio.

Lin, Xiao, Saputra Lase, Irdanto

SAE TOMORROW TODAY: The Future of Hydrogen Fuel: A Distribution Revolution

1349112/11/2024

Jules Verne was ahead of his time--and so is a company inspired by his name that recognizes hydrogen's immense potential as a clean energy solution. Verne develops and commercializes a novel technology to store and distribute hydrogen in its densest form, cryo-compressed. This approach maximizes hydrogen density, addressing the limitations of compressed gas and reducing the cost of dense storage -- which is a game-changer for boosting hydrogen adoption. To learn more, we sat down with Ted McKlveen, Co-founder & CEO, Verne, to discuss the company's breakthrough solution to addressing hydrogen storage and transportation and how it can unlock the widespread adoption of hydrogen energy, particularly in sectors like Class 8 trucking. We'd love to hear from you. Share your comments, questions and ideas for future topics and guests to podcast@sae.org. Don't forget to take a moment to follow SAE Tomorrow Today--a podcast where we discuss emerging technology and trends in mobility with the

Hineman, Marcie

Autonomous Mobile Robot for Gas Leak Localization

2024-01-5226

12/10/2024

LIDAR-based autonomous mobile robots (AMRs) are gradually being used for gas detection in industries. They detect tiny changes in the composition of the environment in indoor areas that is too risky for humans, making it ideal for the detection of gases. This current work focusses on the basic aspect of gas detection and avoiding unwanted accidents in industrial sectors by using an AMR with LIDAR sensor capable of autonomous navigation and MQ2 a gas detection sensor for identifying the leakages including toxic and explosive gases, and can alert the necessary personnel in real-time by using simultaneous localization and mapping (SLAM) algorithm and gas distribution mapping (GDM). GDM in accordance with SLAM algorithm directs the robot towards the leakage point immediately thereby avoiding accidents. Raspberry Pi 4 is used for efficient data processing and hardware part accomplished with PGM45775 DC motor for movements with 2D LIDAR allowing 360° mapping. The adoption of LIDAR-based AMRs

Feroz Ali, L., Madhankumar, S., Hariush, V.C., Jahath Pranav, R., Jayadeep, J., Jeffrey, S.

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