Analysis of detailed electric vehicle data in electrical engineering education
There is a large quantity of data available on the CAN bus of the Chevrolet Volt that can be obtained through the OBD2 connectors on both the passenger and driver side of the vehicle. Although much of this is not available on the console of the vehicle to passengers, it can be logged and collected to analyse various vehicle performance measures and behaviours as well as charging characteristics. A set of pertinent data has been collected simultaneously for approximately 40 vehicle parameters for numerous trips and charging events for the 2012 Chevrolet Volt. Some of the key parameters are battery voltage, battery current, motor currents, state of charge, engine rpm, vehicle speed, longitude, latitude, altitude, battery power, motor power, etc. This data has been used as a learning tool in the electrical engineering classroom for senior students in both advanced machine courses and in sustainable energy courses. Through analysis the students develop a better understanding of general electric vehicle operation principles and energy useage and management. They also develop problem solving skills and experience with analysing large data sets (certain trips have over 15 million data points) and using appropriate tools to perform large but repetitive tasks.
An EV-simulator for Electric Vehicle Education
This paper presents an Electric Vehicle simulator to aid in Electric Vehicle Education. There has been an exponential surge in demand for developing new generation of vehicles using electric-technology. That has caused rapid shift in design paradigm from mechanical to electrical. Such a paradigm shift requires developing new technology educational programs in electric vehicles. The EV-simulator presented in this paper will be helpful for such programs. The simulator is written in Visual C++/MS Visual Studio .NET 2007. It is called LAMAR-EVSim1 after Lamar's first Electric Vehicle Lamar-EV1. The tool is primarily tailored for educational use. Input data to the simulator is presented through a set of input data files including specifications of: the vehicle, the electric-elements, and the environment. The simulator estimates output parameters hierarchically from the tire, gear-box, motor, battery-pack, and finally at vehicle-level. The estimated output parameters include: various drag forces, torques, currents, voltages, RPMs, powers, top speeds, and mileages. Unlike other ev-simulators, this simulator embeds dynamic equations & algorithms context-sensitively so that the output simulation trace are self-instructive.
Relationship between level of internet addiction and time management skills among nursing students.
PURPOSE
This study investigated nursing students' levels of internet addiction (IA) and time management (TM) skills.


DESIGN AND METHODS
This cross-sectional descriptive study was conducted with 400 nursing students of a university in Turkey. The data were collected using the Personal Information Form, IA Scale, and TM Inventory.


FINDINGS
The IA scale and TM inventory mean scores were 40.83 ± 14.81 and 81.34 ± 11.91, respectively. A significantly negative relationship between students' level of IA and TM skills was found (p <0.05).


PRACTICE IMPLICATIONS
The concept of effective time management should be used in interventions for promoting students' conscious internet use.