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This document summarizes types of heat sinks and considerations in relation to the general requirements of aircraft heat sources, and it provides information to achieve efficient utilization and management of these heat sinks. In this document, a heat sink is defined as a body or substance used for removal of the heat generated by thermodynamic processes. This document provides general data about airborne heat sources, heat sinks, and modes of heat transfer. The document also discusses approaches to control the use of heat sinks and techniques for analysis and verification of heat sink management. The heat sinks are for aircraft operating at subsonic and supersonic speeds.

This recommended practice provides guidance on vehicle Cybersecurity and was created based off of, and expanded on from, existing practices which are being implemented or reported in industry, government and conference papers. The best practices are intended to be flexible, pragmatic, and adaptable in their further application to the vehicle industry as well as to other cyber-physical vehicle systems (e.g., commercial and military vehicles, trucks, busses). Other proprietary Cybersecurity development processes and standards may have been established to support a specific manufacturer’s development processes, and may not be comprehensively represented in this document, however, information contained in this document may help refine existing in-house processes, methods, etc. This recommended practice establishes a set of high-level guiding principles for Cybersecurity as it relates to cyber-physical vehicle systems.

This document describes the megawatt-level DC charging system requirements for couplers/inlets, cables, cooling, communication and interoperability. The intended application is for commercial vehicles with larger battery packs requiring higher charging rates for moderate dwell time. A simplified analog safety signaling approach is used for connection-detection to guarantee de-energized state for unmated couplers with superimposed high speed data for EVSE-EV charging control and other value added services.

This SAE Aerospace Recommended Practice (ARP) specifies the methods, equipment, and materials to be used in the installation, mounting, and testing of receptacle connectors used in pressure differential applications requiring an effective connector seal.

Agricultural vehicles often drive along the same terrain day after day or year after year. Yet, they still must detect if a moveable object, such as another vehicle or an animal, happens to be on their path or if environmental conditions have caused muddy spots or washouts. Obstacle detection is one of the major missing pieces that can remove humans from highly automated agricultural machines today and enable the autonomous vehicles of the future. Unsettled Topics in Obstacle Detection for Autonomous Agricultural Vehicles examines the challenges of environmental object detection and collision prevention, including air obscurants, holes and soft spots, prior maps, vehicle geometry, standards, and close contact with large objects. Click here to access the full SAE EDGETM Research Report portfolio.

Information and communication technology is fundamentally changing the way we live and operate in cities, such as instant access to events, transportation, bookings, payments, and other services. At the same time, three “megatrends” in the automotive industry—self-driving, electrification, and advanced manufacturing technology—are enabling the design of innovative, application-specific vehicles that capitalize on city connectivity. Applications could countless; however, they also need to be safe and securely integrated into a city’s physical and digital infrastructure, and into the overall urban ecosystem. Unsettled Issues Concerning Automated Driving Services in the Smart City Infrastructure examines the current state of the industry, the developments in automated driving and robotics, and how these new urban, self-driving city applications are different. It also analyzes higher level challenges for urban applications.

On-road vehicles equipped with driving automation features—where a human might not be needed for operation on-board—are entering the mainstream public space. However, questions like “How safe is safe enough?” and “What to do if the system fails?” persist. This is where remote operation comes in, which is an additional layer to the automated driving system where a human remotely assists the so-called “driverless” vehicle in certain situations. Such remote-operation solutions introduce additional challenges and potential risks as the entire vehicle-network-human now needs to work together safely, effectively, and practically. Unsettled Issues in Remote Operation for On-road Driving Automation highlights technical questions (e.g., network latency, bandwidth, cyber security) and human aspects (e.g., workload, attentiveness, situational awareness) of remote operation and introduces evolving solutions.

Enhanced License for Data Dictionary for Quantities Used in Cyber Physical Systems (AS6969B) allowing for greater usage as outlined in the terms of the Enhanced License. Terms can be reviewed prior to purchase once item is added to the cart. Data Dictionary for Quantities Used in Cyber Physical Systems (AS6969B) This data dictionary provides definitions for quantities commonly used in the command and control of cyber physical systems. It defines mathematical and logical terms, quantities, measurement units, reference systems, measurands, and measurements. It also defines common quantity modalities. The dictionary is structured to be convenient to data modelers. It is also extendable so that users can create their own quantity domains.

Unique Helmholtz induction feeds 2023 Corvette Z06

Aiming at the hassle of intent time window selection and intent characteristic parameters determination in driving intention recognition, two distinctive intention time window division strategies are proposed. The experiment was carried out in the driving simulator, and 160 units of valid sets of using samples were selected from the driving samples collected from 15 subjects, and the driving intentions were categorized into three categories: lane keeping (LK), lane changing left (LCL), and lane changing right (LCR). Pearson correlation analysis was performed on the intention characteristic parameters by comparing the differences in the intention samples and considering the correlation between the parameters. Thereafter six driving intention feature parameters were identified.

Aiming at the system multi-source uncertainty problem during the path tracking control of intelligent vehicle in complex curved road environments, the model predictive control algorithm based on the extended state observer is proposed. Firstly, based on the vehicle dynamics theory, intelligent vehicle path tracking error model is established that takes into account the uncertainty of vehicle parameters and the uncertainty of road curvature, road attachment conditions and other random interference factors, and an online random disturbance estimation method based on the extended state observer is proposed. At the same time, the whale optimization algorithm is used to optimize the relevant parameters of the expanded state observer. Then combined with interference estimation to establish intelligent vehicle path tracking accuracy and driving stability index functions and constraints, and design a path tracking model predictive control method based on the extended state observer.

In this paper, a closed loop path planning and tracking control approach of collision avoidance for autonomous vehicle is proposed. The two-level model predictive control (MPC) is proposed for the path planning and tracking. The upper-level MPC is designed based on the simple vehicle kinematic model to calculate the collision-free trajectory and the potential field method is adopted to evaluate the collision risk and generate the cost function of the optimization problem. The lower-level MPC is the trajectory-tracking controller based on the vehicle dynamics model that calculates the desired control inputs. Finally the control inputs are distributed to steering wheel angle and motor torque via optimal control vectoring algorithm. Test cases are established on the Simulink/CarSim platform to evaluate the performance of the controller.

With the continuous development of the electrical vehicles (EVs), the electric power network and transportation network are interconnected by EVs which require a coordinated operation of the two networks. In view of these coupled networks, this paper proposes a charging navigation strategy for EVs based on charging power adjustment, which can not only provide the navigation path with the shortest total operational time for EVs from the origin node to the completion of charging, but also effectively reduce load fluctuations in the electric power system. In the electric power system, an innovative optimization strategy for adjusting the EV charging power distribution is proposed, which can adjust the charging power in a timely and effective manner according to the response of EV charging. The multi-objective particle swarm optimization (MOPSO) algorithm and the improved Dijkstra algorithm are used for solving the obtained the EV charging power adjustment plan and charging paths.

In order to improve the path tracking accuracy of driverless vehicles at different speed, a fuzzy adaptive model prediction control method was proposed to adjust constant predictive horizon of MPC. Based on the MPC method of 3-DOF vehicle dynamics model, prediction horizon and weight coefficient of the MPC controller could be varied in real time according to the speed and road curvature. With the desired path as the target, the front wheel angle was changed to achieve path tracking. Simulation analysis was performed under the CarSim/Simulink co-simulation environment. Simulation results show that under the condition of satisfying ride comfort and stability of vehicle, the tracking error of the proposed method in the path tracking control is reduced by 30.0%, 29.9% and 14.6% at 36km/h, 72km/h and 108km/h, respectively, which are helpful to path tracking control.

This specification covers a corrosion-resistant steel in the form of seamless or welded tubing.