Browse Topic: Commercial vehicles
SAE JA6097 (“Using a System Reliability Model to Optimize Maintenance”) shows how to determine which maintenance to perform on a system when that system requires corrective maintenance to achieve the lowest long-term operating cost. While this document may focus on applications to Jet Engines and Aircraft, this methodology could be applied to nearly any type of system. However, it would be most effective for systems that are tightly integrated, where a failure in any part of the system causes the entire system to go off-line, and the process of accessing a failed component can require additional maintenance on other unrelated components.
This document applies to off-road forestry work machines defined in SAE J1116 or ISO 6814.
This document describes a rigorous engineering test procedure that utilizes industry-accepted data collection and statistical analysis methods to determine the road load and to estimate the aerodynamic drag area of trucks and buses weighing more than 10000 pounds. The test procedure may be conducted on a test track or on a public road under controlled conditions and supported by extensive data collection and data analysis constraints. The estimated aerodynamic-drag-area result represents a single-speed and single-yaw-angle condition. Test results that do not rigorously follow the method described herein shall not be represented as an SAE J2978 result.
This SAE Standard is intended to describe the basic types of felling heads, including those with bunching capabilities, that are attachments to a self-propelled machine. Only the major components that are necessary to describe the functions of the felling head, and to apply the principles of the standard are included. Illustrations used are not intended to include all existing felling heads or to describe any particular manufacturer’s variation.
This SAE Standard applies to machines as defined in Appendix A. Some of these machines can travel on-highway but function primarily off-highway.
This paper builds on last year’s paper presenting DevOps automation in the context of model-based development. Following that paper, we interviewed Simulink users in passenger automotive, motorsports, commercial vehicles, aviation, rocketry, and industrial automation. We discovered that much of the benefit of DevOps platforms to reduce product development cycle time relies on their interactive features. We prototyped new tools to bridge interactive DevOps Git-based platforms with model-based development workflows, and then gathered reactions from another round of interviews. Here we present these interactive DevOps workflows with the feedback from these interviews to contextualize how engineering teams could adopt them to accelerate their own model-based workflows.
Why precision engineering is defining confidence in next-generation internal combustion engines. In 2026, the global transport industry, and particularly the automotive industry, finds itself under competing pressures. Regulators are tightening emissions standards, with new regulations such as the EU's Euro 7 being proposed to reduce air pollution in line with net-zero ambitions. Fleet operators are managing ever-aging vehicle populations in uncertain economic conditions, and policymakers are accelerating mandates for sustainable fuels, with countries like the UK moving forward with a Zero Emission Vehicle mandate by 2035. Across passenger vehicles, commercial transport, and off-highway machinery, engineers are now tasked with delivering measurable carbon reduction using a combination of electrification, advanced internal combustion engines (ICE) and fuel innovation without compromising safety, durability or performance.
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