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Browse AllThis specification covers a corrosion-resistant steel in the form of investment castings homogenized and solution and precipitation heat treated to 180 ksi (1241 MPa) tensile strength.
The US trucking industry heavily relies on the diesel powertrain, and the transition towards zero-emission vehicles, such as battery electric vehicles (BEV) and fuel cell electric vehicles (FCEV), is happening at a slow pace. This makes it difficult for truck manufacturers to meet the Phase 3 Greenhouse Gas standards, which mandate substantial emissions reductions across commercial vehicle classes beginning of 2027. This challenging situation compels manufacturers to further optimize the powertrain to meet stringent emissions requirements, which might not account for customer application specifics may not translate to a better total cost of ownership (TCO) for the customer. This study uses a simulation-based approach to connect customer applications and regulatory categories across various sectors. The goal is to develop a methodology that helps identify the overlap between optimizing for customer applications vs optimizing to meet regulations. To use a data-driven approach, a real
In-vehicle communication among different vehicle electronic controller units (ECU) to run several applications (I.e. to propel the vehicle or In-vehicle Infotainment), CAN (Controller Area Network) is most frequently used. Given the proprietary nature and lack of standardization in CAN configurations, which are often not disclosed by manufacturers, the process of CAN reverse engineering becomes highly complex and cumbersome. Additionally, the scarcity of publicly accessible data on electric vehicles, coupled with the rapid technological advancements in this domain, has resulted in the absence of a standardized and automated methodology for reverse engineering the CAN. This process is further complicated by the diverse CAN configurations implemented by various Original Equipment Manufacturers (OEMs). This paper presents a manual approach to reverse engineer the series CAN configuration of an electric vehicle, considering no vehicle information is available to testing engineers. To
Accidents during lane changes are increasingly becoming a problem due to various human based and environment-based factors. Reckless driving, fatigue, bad weather are just some of these factors. This research introduces an innovative algorithm for estimating crash risk during lane changes, including the Extended Lane Change Risk Index (ELCRI). Unlike existing studies and algorithms that mainly address rear-end collisions, this algorithm incorporates exposure time risk and anticipated crash severity risk using fault tree analysis (FTA). The risks are merged to find the ELCRI and used in real time applications for lane change assist to predict if lane change is safe or not. The algorithm defines zones of interest within the current and target lanes, monitored by sensors attached to the vehicle. These sensors dynamically detect relevant objects based on their trajectories, continuously and dynamically calculating the ELCRI to assess collision risk during lane changes. Additionally
Severe rear-impact collisions can cause significant intrusion into the occupant compartment when the structural integrity of the rear survival space is insufficient. Intrusion patterns are influenced by impact configuration—underride, in-line, or override—with underride collisions channeling forces below the beltline through the rear wheels as a primary load path. This force concentration rapidly propels the rear seat-pan forward, contacting the rearward-rotating front seatback. The resulting bottoming-out phenomenon produces a forward impulse that amplifies loading on the front occupant’s upper torso, increasing the risk of thoracic injury even when the head is properly supported by the head restraint. This study analyzes a real-world rear-impact collision that resulted in fatal thoracic injuries to the driver, attributed to the interaction between the driver’s seatback and the forward-moving rear seat pan. A vehicle-to-vehicle crash test was conducted to replicate similar intrusion