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Browse AllThe electronic mechanical brake (EMB) system is a critical actuator for achieving brake-by-wire control. This review categorizes and summarizes the literature related to EMB into three sections: actuator, mathematical modeling, and control strategies. In the actuator aspect, this article compares and analyzes motors, motion conversion mechanisms, and self-reinforcing mechanisms. For mathematical modeling, this article reviews modeling methods for EMB systems concerning motors, transmission mechanisms, friction, contact collisions, nonlinear stiffness, and hysteresis characteristics. Regarding control strategies, this article consolidates methods for clamp force control, clamp force estimation, and gap management. Finally, the article discusses potential future research directions in EMB from both hardware structure and software algorithm perspectives
This specification covers a corrosion-resistant steel product in the solution and precipitation heat-treated (H950) condition, 12 inches (305 mm) and under in nominal diameter, thickness, or, for hexagons, least distance between parallel sides
This specification covers a corrosion-resistant steel product in the solution and precipitation heat-treated (H1150) condition, 12 inches (305 mm) and under in nominal diameter, thickness, or, for hexagons, least distance between parallel sides
This specification covers a corrosion-resistant steel product in the solution and precipitation heat-treated (H1100) condition, 12 inches (305 mm) and under in nominal diameter, thickness, or, for hexagons, least distance between parallel sides. The aged product may be supplied directly by a producer or by another entity performing the functions of a producer as defined in AS6279. The latter can be accomplished by precipitation heat treatment of solution treated material previously certified to AMS5934. The entity assuming responsibility for the aging operation is designated the producer of AMS5934/H1100
This specification covers a corrosion-resistant steel product in the solution and precipitation heat-treated (H1025) condition, 12 inches (305 mm) and under in nominal diameter, thickness, or, for hexagons, least distance between parallel sides
ML approaches to solving some of the key perception and decision challenges in automated vehicle functions are maturing at an incredible rate. However, the setbacks experienced during initial attempts at widespread deployment have highlighted the need for a careful consideration of safety during the development and deployment of these functions. To better control the risk associated with this storm of complex functionality, open operating environments, and cutting-edge technology, there is a need for industry consensus on best practices for achieving an acceptable level of safety. Navigating the Evolving Landscape of Safety Standards for Machine Learning-based Road Vehicle Functions provides an overview of standards relevant to the safety of ML-based vehicle functions and serves as guidance for technology providers—including those new to the automotive sector—on how to interpret the evolving standardization landscape. The report also contains practical guidance, along with an example
While weaponizing automated vehicles (AVs) seems unlikely, cybersecurity breaches may disrupt automated driving systems’ navigation, operation, and safety—especially with the proliferation of vehicle-to-everything (V2X) technologies. The design, maintenance, and management of digital infrastructure, including cloud computing, V2X, and communications, can make the difference in whether AVs can operate and gain consumer and regulator confidence more broadly. Effective cybersecurity standards, physical and digital security practices, and well-thought-out design can provide a layered approach to avoiding and mitigating cyber breaches for advanced driver assistance systems and AVs alike. Addressing cybersecurity may be key to unlocking benefits in safety, reduced emissions, operations, and navigation that rely on external communication with the vehicle. Automated Vehicles and Infrastructure Enablers: Cybersecurity focuses on considerations regarding cybersecurity and AVs from the
With the influx of artificial intelligence (AI) models aiding the development of autonomous driving (AD), it has become increasingly important to analyze and categorize aspects of their operation. In conjunction with the high predictive power innate to AI solutions, due to the safety requirements inherent to automotive systems and the demands for transparency imposed by legislature, there is a natural demand for explainable and predictable models. In this work, we explore the various strategies that reveal the inner workings of these models at various component levels, focusing on those adapted at the modeling stage. Specifically, we highlight and review the use of explainability in state-of-the-art AI-based scenario understanding and motion prediction methods, which represent an integral part of any AD system. We break the discussion down across three key axes that are inherent to any AI solution: the data, the model architecture, and the loss optimization. For each of the axes, we
This SAE Recommended Practice describes how to position and posture the H-point design tool (HPD) described in Appendix B, and how to establish the seating reference point (SgRP), design H-point travel path, and other key reference points that are used in the design and specification of both driver and passenger seat positions. This practice also provides a method for determining the length of the seat track for a driver seat that adjusts fore/aft. The seat track length is based on a desired level of driver accommodation, assuming a U.S. population containing an equal number of male and female drivers. The procedure can be used to establish driver seat track accommodation for new vehicle designs or to evaluate accommodation in existing vehicles. A general method for determining driver seat track length for any driver population (male and female stature distribution) at any selected accommodation percentile and gender mix is given in Appendix A. Application of this document is limited
Accurate estimation of vehicle energy consumption plays an important role in developing advanced energy-saving connected automated vehicle technologies such as Eco Approach and Departure, PHEV mode blending, and Eco-route planning. The present study developed a reduced-order energy model with second-order response surfaces and torque estimation to estimate the energy consumption while just relying on the drive cycle information. The model is developed for fully electric Chevrolet Bolt using chassis dynamometer data. The dyno test data encompasses the various EPA test cycles, real-world, and aggressive maneuvers to capture most powertrain operating conditions. The developed model predicts energy consumption using vehicle speed and road-grade inputs for a drive cycle. The accuracy of the model is validated by comparing the prediction results against track and road test data. The developed model was able to accurately predict the energy consumption for track drive cycles within the error
The advent of neck braces for the helmeted motorcycle rider has introduced a pertinent research question: To what extent do they reduce measures related to the major mechanism of neck injury in unrestrained torso accidents, i.e., compression flexion (CF)? This question requires a suitable method of testing and evaluating the measures for a load case resulting in the required mechanism. This study proposes a weighted swinging anvil striking the helmeted head of a supine HIII ATD by means of a near vertex impact with a low degree of anterior head impact eccentricity to induce CF of the neck. The applied impact was chosen for the baseline (no neck brace) so that the upper and lower neck axial forces approached injury assessment reference values (IARV). The head impact point evaluated represents those typically associated with high-energy burst fractures occurring within the first 20 ms, with possible secondary disruption of posterior ligaments. The proposed test can be used to evaluate
With the development of automotive intelligence and networking, the communication architecture of automotive network is evolving toward Ethernet. To improve the real-time performance and reliability of data transmission in traditional Ethernet, time-sensitive network (TSN) has become the development direction of next-generation of automotive networks. The real-time advantage of TSN is based on accurate time synchronization. Therefore, a reliable time synchronization mechanism has become one of the key technologies for the application of automotive Ethernet technology. The protocol used to achieve accurate time synchronization in TSN is IEEE 802.1AS. This protocol defines a time synchronization mechanism suitable for automotive Ethernet. Through the master clock selection algorithm, peer link delay measurement, and clock synchronization and calibration mechanism, the time of each node in the vehicle network is synchronized to a reference master clock. In addition, the protocol clearly
This specification covers a corrosion-resistant steel product in the solution and precipitation heat treated (H1000) condition, 12 inches (305 mm) and under in nominal diameter, thickness, or, for hexagons, least distance between parallel sides