Browse Topic: Tests and Testing
The added connectivity and transmission of personal and payment information in electric vehicle (EV) charging technology creates larger attack surfaces and incentives for malicious hackers to act. As EV charging stations are a major and direct user interface in the charging infrastructure, ensuring cybersecurity of the personal and private data transmitted to and from chargers is a key component to the overall security. Researchers at Southwest Research Institute® (SwRI®) evaluated the security of direct current fast charging (DCFC) EV supply equipment (EVSE). Identified vulnerabilities included values such as the MAC addresses of both the EV and EVSE, either sent in plaintext or encrypted with a known algorithm. These values allowed for reprogramming of non-volatile memory of power-line communication (PLC) devices as well as the EV’s parameter information block (PIB). Discovering these values allowed the researchers to access the IPv6 layer on the connection between the EV and EVSE
The half vehicle spindle-coupled multi-axial input durability test has been broadly used in the laboratory to evaluate the fatigue performance of the vehicle chassis systems by automotive suppliers and OEMs. In the lab, the front or rear axle assembly is usually held by fixtures at the interfaces where it originally connects to the vehicle body. The fixture stiffness is vital for the laboratory test to best replicate the durability test in the field at a full vehicle level especially when the subframe of the front or rear axle is hard mounted to the vehicle body. In this work, a multi-flexible body dynamics (MFBD) model in Adams/Car was utilized to simulate a full vehicle field test over various road events (rough road, braking, steering). The wheel center loads were then used as inputs for the spindle coupled simulations of the front axle with a non-isolated subframe. Three types of fixtures including trimmed vehicle body, a rigid fixture with softer connections and a rigid fixture
This paper reviews the current situation in the terms and definitions that influence the development of testing and prediction in automotive, aerospace and other areas of engineering. The accuracy of these terms and definitions is very important for correct simulation, testing and prediction. This paper aims to define accurate terms and definitions. It also includes the author’s recommendations for improving this situation and preparing new standards.
The electric vehicle market, vehicle ECU computing power, and connected electronic vehicle control systems continue to grow in the automotive industry. The results of these advanced and expanded vehicle technologies will provide customers with increased cost savings, safety, and ride quality benefits. One of these beneficial technologies is the tire wearing prediction. The improved prediction of tire wear will advise a customer the best time to change tires. It is expected that this prediction algorithms will be essential part for both the optimization of the chassis control systems and ADAS systems to respond to changed tire performance that varies with a tire’s wear condition. This trend is growing, with many automakers interested in developing advanced technologies to improve product quality and safety. This study is aimed at analyzing the handling and ride comfort characteristics of the tire according to the depth of tire pattern wear change. The handing and ride comfort
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