Search Results

This course, designed for EV motor engineers and graduate participants, systematically introduces EV motor design analysis and test verification. Combined with engineering practice, it discusses typical EV motor design cases and practical issues related to EV motor technology, aiming to broaden the horizon of EV motor design engineers and improve their problem-solving skills.

This course examines ADAS and autonomous vehicle technologies that offer the potential to increase safety while attempting to optimize the cost of car ownership. LIDAR (light detection ranging) and Infrared camera sensing are seeing a rapid growth and adoption in the industry. However, the sensor requirements and system architecture options continue to evolve almost every six months. This course will provide the foundation to build on for these two technologies in automotive applications. It will include a demonstration model for LIDAR and Infrared camera.

Advanced Driver Assist System (ADAS) and autonomous vehicle technologies have disrupted the traditional automotive industry with potential to increase safety and optimize the cost of car ownership. Among the challenges are those of sensing the environment in and around the vehicle. Infrared camera sensing is seeing a rapid growth and adoption in the industry. The applications and illumination architecture options continue to evolve. This course will provide the foundation on which to build near infrared camera technologies for automotive applications.

Advanced Driver Assist System (ADAS) and autonomous vehicle technologies have disrupted the traditional automotive industry with potential to increase safety and optimize the cost of car ownership. Light detection and ranging (LIDAR) sensing, a sensing method that detects objects and maps their distances, is seeing rapid growth and adoption in the industry. However, the sensor requirements and system architecture options continue to evolve. This course will provide the foundation to build LIDAR technologies in automotive applications.

Vehicle cybersecurity vulnerabilities could impact a vehicle's safe operation. Therefore, engineers should ensure that systems are designed free of unreasonable risks to motor vehicle safety, including those that may result due to existence of potential cybersecurity vulnerabilities. The automotive industry is making vehicle cybersecurity an organizational priority.

Photographs and video recordings of vehicle crashes and accident sites are more prevalent than ever, with dash mounted cameras, surveillance footage, and personal cell phones now ubiquitous. The information contained in these pictures and videos provide critical information to understanding how crashes occurred, and  analyze physical evidence. This course teaches the theory and techniques for getting the most out of digital media, including correctly processing raw video and photographs, correcting for lens distortion, and using photogrammetric techniques to convert the information in digital media to usable scaled three-dimensional data.

Convolutional neural networks are the de facto method of processing camera, radar, and lidar data for use in perception in ADAS and L4 vehicles, yet their operation is a black box to many engineers. Unlike traditional rules-based approaches to coding intelligent systems, networks are trained and the internal structure created during the training process is too complex to be understood by humans, yet in operation networks are able to classify objects of interest at error rates better than rates achieved by humans viewing the same input data.

Many technical projects, most vehicle and component testing, and all accident reconstructions, product failure analyses, and other forensic investigations, require photographic documentation. Roadway evidence disappears, tested or wrecked vehicles are repaired, disassembled, or scrapped, and components can be tested for failure. Photographs are frequently the only evidence that remains of a wreck, or the only records of subjects before or during tests. Making consistently good images during any inspection is a critical part of the evaluation process. 

This specification covers premium quality bolts and screws made of 6Al - 4V titanium alloy.

ARINC 800 is the first industry standard intended for characterization of aviation-grade high-speed (Gbps) Ethernet links. The test methods are based on realistic representation of cabin networks. The notional cabling architecture is based on IFE seat distribution using multiple intermediate disconnects. Sequential testing is supported by building up number of connectors in the link. Test guidelines for mixed intermediate cable lengths are provided.

This document defines general practices for testing the physical layer of a fiber optic cable system. It is the intention of this document to outline proven practices for engineers and technicians engaged in testing and supporting fiber optic cable systems in aircraft. This document defines general practices for testing the physical layer of a fiber optic cable system. It is the intention of this document to outline proven practices for engineers and technicians engaged in testing and supporting fiber optic cable systems in aircraft.

When vehicles share certain information wirelessly via Dedicated Short Range Communications (DSRC), they enable a new layer of electronic vehicle safety that, when needed, can generate warnings to drivers and even initiate automatic preventive actions. Vehicle location and velocity provided by Global Navigation Systems (GNSS), including GPS, are key in allowing vehicle path estimation. GNSS is effective in accurately determining a vehicle's location coordinates in most driving environments, but its performance suffers from obstructions in dense urban environments. To combat this, augmentations to GNSS are being contemplated and tested. This testing has been typically done using a reference GNSS system complimented by expensive military-grade inertial sensors, which can still fail to provide adequate reference performance in certain environments.

Research in plug in vehicles (PHEV and BEV) has of course been ongoing for decades, however now that these vehicles are finally being produced for a mass market an intense focus over the last few years has been given to proper evaluation techniques and standard information to effectively convey efficiency information to potential consumers. The first challenge is the development of suitable test procedures. Thanks to many contributions from SAE members, these test procedures have been developed for PHEVs (SAE J1711 now available) and are under development for BEVs (SAE J1634 available later this year). A bigger challenge, however, is taking the outputs of these test results and dealing with the issue of off-board electrical energy consumption in the context of decades-long consumer understanding of MPG as the chief figure of merit for vehicle efficiency.

Optical fiber has begun replacing copper in avionic networks. So far, however, it has been mainly restricted to non-critical applications (video transmission to the flight deck, IFE?). In order to take advantage of the high-bandwidth, low weight, no EMI properties of optical fibers in all data transmission networks, it will be necessary to improve the testing. One part of the puzzle, which is still missing, is the self-test button: the possibility to check the network and detect potential failures before they occur. The typical testing tool of a technician involved in optical fiber cables is the ?light source ? optical power meter? pair. With this tool, one can measure the insertion loss of the fiber link. A second important parameter, the return loss at each optical connector, is not analysed. In addition, this is only a global measurement, which does not allow the detection of possible weak points.

Plug-In Hybrid and Extended Range Electric Vehicle's have quickly become the focus of many OEM's and suppliers. Existing regulations and test procedures did not anticipate this rapid adoption of this new technology, resulting in many product development challenges. The lack of clear requirements is further complicated by CARBs consideration of CO2 inclusion in their next light duty OBD regulation. This presentation provides an overview of the regulatory requirements for OBD systems on hybrid vehicles that intend to certify in California. Near term challenges for EREV?s and PHEV?s are discussed, including concerns with the existing denominator and warm-up cycle calculations. Some proposals are made to address these concerns. Presenter Andrew Zettel, General Motors Company