Your Selections

Real-time data
Show Only

Collections

File Formats

Content Types

Dates

Sectors

Topics

Authors

Publishers

Affiliations

Committees

Events

Magazine

   This content is not included in your SAE MOBILUS subscription, or you are not logged in.

Calibration of Electrochemical Models for Li-ion Battery Cells using Three-Electrode Testing

Ford Motor Company-Chulheung Bae, Jie Deng
SK Innovation-Heechan Park
  • Technical Paper
  • 2020-01-1184
To be published on 2020-04-14 by SAE International in United States
Electrochemical models of Lithium ion batteries are today a standard tool in the automotive industry for activities related to the computer-aided design, analysis, and optimization of energy storage systems for electrified vehicles. One of the challenges in the development or use of such models is the need of detailed information on the cell and electrode geometry or properties of the electrode and electrolyte materials, which are typically unavailable or difficult to retrieve by end-users. This forces engineers to resort to “hand-tuning” of many physical and geometrical parameters, using standard cell-level characterization tests. This paper proposes a method to provide information and data on individual electrode performance that can be used to simplify the calibration process for electrochemical models. The proposed approach consists in inserting a reference electrode in a commercial Li-ion cell to obtain real-time data of how the cathode and anode interact with one another during cell operation, rather than resorting to coin cell testing of individual electrode materials. The paper will illustrate the technique developed for the reference electrode insertion, then describe the…

The Role of Sensors in the Evolution of Robotics

  • Magazine Article
  • TBMG-35609
Published 2019-12-01 by Tech Briefs Media Group in United States

At one time, robotics was considered more science fiction than reality. That's changing. Today, robots are increasingly playing a role in our everyday lives. They're zooming around our homes to pick up dust, helping surgeons perform operations with even more precision, sniffing out suspicious packages for law enforcement, and on the factory floor, they're performing all kinds of tasks for automotive, electronics, and industrial manufacturing companies.

   This content is not included in your SAE MOBILUS subscription, or you are not logged in.

The Road to Automobility

Autonomous Vehicle Engineering: December 2019

Lawrence D. Burns
  • Magazine Article
  • 19AVEP11_03
Published 2019-11-01 by SAE International in United States

The era of electrified, self-driving vehicles is upon us. Engineers are key to the transformation - with much hard work still to be done.

In 1911, eight years after the Wright Brothers flew the first airplane, French general Ferdinand Foch dismissed the new technology. “Airplanes are interesting scientific toys,” he scoffed, “but they are of no military value.” World War I and the wave of aeronautical progress it triggered would prove Foch wrong. Today, automobility is the subject of a “hype or ripe” debate similar in spirit to what the airplane experienced in its nascent years.

Annotation ability available
   This content is not included in your SAE MOBILUS subscription, or you are not logged in.

Development of Data Acquisition and Analysis System: Telemetry in Automotive

Vellore Institute of Technology-Divyansh Rastogi, Gokul Kumar, Chooriyaparambil Damodaran Naiju
Published 2019-10-11 by SAE International in United States
Digital data extraction is the most important and advance informative system that are embedded in the modern world functioning machinery to acquire the most precise feedback about the real-time operational situation of the machine to the control centre of operation. This data that is acquired from the machinery can be used to increase the efficiency, operational timing, production-cost and the overall human effort that is required for the operation. This paper focuses on the development on the advanced telemetry system that is capable to acquire real-time data of the modern vehicle wirelessly during its motion. A mobile automotive telemetry system for installation on-board a vehicle, includes: diagnostic structure for monitoring operational functions of the vehicle and generating operational information; memory for storing the generated operational information; and a server, in communication with the diagnostic structure and the memory. The server includes: (a) structure to receive a request from a remote client for the generated operational information; (b) structure to retrieve the generated operational information from the memory; and (c) structure to transmit the generated operational…
Annotation ability available

Autonomous Multi-Sensor Maritime Awareness System

  • Magazine Article
  • TBMG-35364
Published 2019-10-01 by Tech Briefs Media Group in United States

BIRD Aerosystems Herzliya, Israel

Reimagining Innovation: Additive Manufacturing

  • Magazine Article
  • TBMG-34570
Published 2019-06-01 by Tech Briefs Media Group in United States

In the injectable drug-delivery industry, expectations for improved patient experiences with administration and at-home delivery of therapeutic regimens are evolving. Products that combine the drug, its primary packaging, and a delivery system — commonly called combination products — are on the rise. The inclusion and expansion of digital elements in a delivery system can help deliver medical, sensor, and diagnostic information in real-time data streams. Such data can help caregivers provide better overall care, while other digital elements may encourage adherence to therapeutic regimens. Given these trends, additive manufacturing (AM) provides the opening for expansive idea generation and development agility that can lead to improved quality and new opportunities to disrupt the drug-delivery space.

   This content is not included in your SAE MOBILUS subscription, or you are not logged in.

Flight Control Actuators - Dynamic Seals, Collection of Duty Cycle Data

A-6A3 Flight Control and Vehicle Management Systems Cmt
  • Aerospace Standard
  • ARP4895B
  • Current
Published 2019-05-16 by SAE International in United States
This SAE Aerospace Recommended Practice (ARP) provides an algorithm aimed to analyze flight control surface actuator movements with the objective to generate duty cycle data applicable to hydraulic actuator dynamic seals.
Annotation ability available
   This content is not included in your SAE MOBILUS subscription, or you are not logged in.

Evaluation of a Robust Haptic Interface for Semi-Autonomous Vehicles

SAE International Journal of Connected and Automated Vehicles

Clemson University, USA-Chengshi Wang, Yue Wang, John R. Wagner
  • Journal Article
  • 12-02-02-0007
Published 2019-05-15 by SAE International in United States
The advent of steer-by-wire technologies has changed the driving paradigm for drivers and vehicle autonomy. Such technologies integrate electric motors to actuate the tire-road plus human-machine interfaces. Steer-by-wire vehicles can benefit from haptic concepts through the provision of tunable force feedback, coupled with nonlinear control, to introduce lane keeping and pathway following technologies that minimize and possibly eliminate driver actions. In this article, two vehicle haptic interfaces, including a robotic grip and a joystick, both of which are accompanied by nonlinear sliding mode control, have been developed and studied on a steer-by-wire platform integrated with a virtual reality driving environment. An operator-in-the-loop evaluation that included 30 human test subjects investigated these haptic steering interfaces over a prescribed series of driving maneuvers through real-time data logging and post-test questionnaires. A conventional steering wheel with the robust sliding mode controller was used for all the driving events for comparison. Subjective and objective results from the tests demonstrate that the driver’s experience can be enhanced by up to 76.3% with a robotic grip steering input when compared to…
This content contains downloadable datasets
Annotation ability available
   This content is not included in your SAE MOBILUS subscription, or you are not logged in.

Autonomous “Wingman” Vehicles

Aerospace & Defense Technology: May 2019

  • Magazine Article
  • 19AERP05_01
Published 2019-05-01 by SAE International in United States

The Future of Military Unmanned Vehicle Technology

The US Army's Futures Command is the most important administrative reorganization of the modern Army. Responding to the world's changing priorities-especially the “near peer” threat of ascendant Russia and China-the Army is no longer modernizing, but re-inventing its ground vehicle fleet against new realities. Just like the U.S. Air Force stopped inventing better jets and pilot aids and moved to unmanned aerial vehicles (UAV) for “dull, dirty and dangerous” missions, the Army envisions multiple autonomous vehicle concepts. Instead of a heavier Abrams main battle tank, or a replacement to the aging M113 APC, autonomous “wingman” vehicles may replace some of the human-heavy tasks on the future battlefield.

Annotation ability available
   This content is not included in your SAE MOBILUS subscription, or you are not logged in.

“Fitting Data”: A Case Study on Effective Driver Distraction State Classification

American Optimal Decisions, Inc.-Alexey Zrazhevsky
DENSO International America Inc.-Yu Zhang
Published 2019-04-02 by SAE International in United States
The goal of this project was to investigate how to make driver distraction state classification more efficient by applying selected machine learning techniques to existing datasets. The data set used in this project included both overt driver behavior measures (e.g., lane keeping and headway measures) and indices of internal cognitive processes (e.g., driver situation awareness responses) collected under four distraction conditions, including no-distraction, visual-manual distraction only, cognitive distraction only, and dual distraction conditions. The baseline classification method that we employed was a support vector machine (SVM) to first identify driver states of visual-manual distraction and then to identify any cognitive-related distraction among the visual-manual distraction cases and other non-visual manual distraction cases. The new aspect of this research is optimization of the classification effort, which involved cardinality constraints on 16 overt driver behavior measures. A spline transformation was also implemented to achieve better classification performance. In addition to testing our optimization approach with the SVM, we also explored logistic regression. Results revealed the spline-transformed variables to produce a good “out-of-sample” performance for both the SVM…
This content contains downloadable datasets
Annotation ability available