Search Results

Honda’s eGX electric racing kart and CR-V Hybrid racer concept give a glimpse into the future of electrified racing tech.

This AIR documents qualification of Percon 28, an Extra-High Strength copper alloy, to AS29606 according to AS6324.

SAE J2461 specifies the recommended practices of a Vehicle Electronics Programming Stations (VEPS) architecture.in a Win32® environment. This system specification, SAE J2461, was a revision of the requirements for Vehicle Electronics Programming Stations (VEPS) set forth in SAE J2214, Vehicle Electronics Programming Stations (VEPS) System Specification for Programming Components at OEM Assembly Plants (Cancelled Jun 2004). The J2214 standard has been cancelled indicating that it is no longer needed or relevant.

Abstract The use of straight vegetable oil in diesel engines leads to undesirable consequences due to the peculiar physicochemical properties of vegetable oils. In this regard, the use of pure and unmodified vegetable oils requires their obligatory dilution with petroleum fuels, usually diesel fuel. However, blends of diesel fuel with vegetable oil have a significantly higher density and viscosity than pure diesel fuels. Therefore, in this article, it was proposed to use blends of vegetable oil with aviation kerosene since kerosene has lower density and viscosity compared to diesel fuel. In addition, kerosene is less prone to coking of injectors, has a higher calorific value, and has a lighter hydrocarbon composition, which makes starting the engine easier. Within the framework of the study, engine tests of a full-size four-cylinder diesel engine, MMZ D-245.12.C, were carried out at maximum load in the range of crankshaft speeds from minimum (1000 min−1) to nominal (2400 min−1).

Thin plates buckle after applying load and return to normal position after the load is released, this process is called oil canning. Waviness in thin panels can be seen on various plates of metals. Oil canning is a major issue if panels are too thin and these panels create vibration and noise in the vehicle body panel. If the panels are wider, then there are more chances of oil canning issues. Different digital simulations and physical techniques are currently available to check the canning performance, but they required geometrical data and physical setup. In this paper machine learning (ML) approach to predict the oil canning performance is presented. This approach adds a new process to the existing process of vehicle door design, but it helps avoid the number of simulations and unwanted structural modifications at the early design stage, making it a handy and powerful tool for the designer.

Abstract Measuring the dynamic parameters of liquid fragments generated in the near-field of atomizing sprays poses a significant challenge due to the random nature of the fragments, the instability of the spray, and the limitations of current measuring technology. Precise determination of these parameters can aid in improving the control of the atomization process, which is necessary for providing suitable spray structures with appropriate flow rates and droplet size distributions for various applications such as those used in heat engines. In piston and gas turbine engines, controlling spray characteristics such as penetration, cone angle, particle size, and droplet size distribution is crucial to improve combustion efficiency and decrease exhaust emissions. This can be accomplished by adjusting the structural and/or operating parameters of the fuel supply system.

This document is intended to supplement the SAE J1939 documents by offering the SAE J1939 information in a form that can be sorted and search for easier use.

Abstract The tailpipe zero-emission legislation has pushed the automotive industry toward more electrification. Regenerative braking is the capability of electric machines to provide brake torque. So far, the regenerative braking feature is primarily considered due to its effect on energy efficiency. However, using individual e-machines for each wheel makes it possible to apply the antilock braking function due to the fast torque-tracking characteristics of permanent magnet synchronous motors (PMSM). Due to its considerable cost reduction, in this article, a feasibility study is carried out to investigate if the ABS function can be done purely through regenerative braking using a mid-fidelity model-based approach. An uni-tire model of the vehicle with a surface-mount PMSM (SPMSM) model is used to verify the idea. The proposed ABS control system has a hierarchical structure containing a high-level longitudinal slip controller and a low-level SPMSM torque controller.

Historical materials, task force mission statement, task force organizational documents, discussion documents, comparison tables, spreadsheets, government interpretations and announcements, standards organization correspondence, industry interpretations, international standards, task force proposals, material references, trade association statements, equipment manufacturer reviews, and other task force developed documents that were inspected, reviewed, referenced or used in development of the SAE J3097TM/ANSI Z26.1 2019-05 Standard

This SAE Recommended Practice documents nomenclature in common use for various types of radiator and radiator core construction, as well as for various radiator-related accessories.

Abstract Numerous researchers are committed to finding solutions to the path planning problem of intelligence-based vehicles. How to select the appropriate algorithm for path planning has always been the topic of scholars. To analyze the advantages of existing path planning algorithms, the intelligence-based vehicle path planning algorithms are classified into conventional path planning methods, intelligent path planning methods, and reinforcement learning (RL) path planning methods. The currently popular RL path planning techniques are classified into two categories: model based and model free, which are more suitable for complex unknown environments. Model-based learning contains a policy iterative method and value iterative method. Model-free learning contains a time-difference algorithm, Q-learning algorithm, state-action-reward-state-action (SARSA) algorithm, and Monte Carlo (MC) algorithm.

Abstract Precise vehicle state and the surrounding traffic information are essential for decision-making and dynamic control of intelligent connected vehicles. Tremendous research efforts have been devoted to developing state estimation techniques. This work investigates the research progress in this field over recent years. To be able to describe the state of multiple traffic elements uniformly, the concept of a vehicle neighborhood system is proposed to describe the system composed of vehicles and their surrounding traffic elements and to distinguish it from the traditional macroscopic traffic research field. In this work, the vehicle neighborhood system consists of three main traffic elements: the host vehicle, the preceding vehicle, and the road. Therefore, a review of state estimation methods for the vehicle neighborhood system is presented around the three traffic objects mentioned earlier.

Abstract Previous volunteer studies focused on low-speed frontal events have demonstrated that muscle activation (specifically pre-impact bracing) can significantly affect occupant response. However, these tests do not always include a sufficient number of small female volunteers to compare their unique responses to the typically studied midsize male population. The purposes of this study were to quantify the occupant kinetics and muscle responses of relaxed and braced small female and midsize male volunteers during low-speed frontal sled tests and to compare between muscle states and demographic groups. Small female and midsize male volunteers experienced multiple low-speed frontal sled tests consisting of two pulse severities (1 g and 2.5 g) and two muscle states (relaxed and braced) per pulse severity. The muscle activity of 30 muscles (15 bilaterally) and reaction forces at the volunteer-test buck interfaces and seat belt were measured before and during each sled test.

This paper develops a co-simulation framework based on the use of the package LiveLinkTMfor Matlab to perform parameters optimization of dynamical systems implemented in COMSOL Multiphysics. The identification problem is recast as an optimization problem which is solved in Matlab. Code for the key steps of the approach is described in detail, and an implementation based on the particle swarm optimization (PSO) algorithm is proposed. The effectiveness and general applicability of the framework are shown for two energy systems: lithium-ion battery (LIB) and gasoline particulate filter (GPF). Matlab codes and COMSOL models for both case studies are made publicly available and can be used as a starting point to solve parameter identification problems for systems beyond the case studies presented here.