Browse Topic: Test equipment and instrumentation
This paper presents the design of a cost-effective fuel injector driver designed for accelerated testing of injectors. The driver simulates injection patterns across a wide range of vehicle operating conditions and can be programmed with injection maps for different engines, test cycles based on drawing specifications, pre-defined engine running profiles, and manual control, where the user defines PWM frequency and duty cycle. It also enables remote operation through a Wi Fi access point. An injector driver-based test setup was developed to study wear and evaluate leakage tendency in an injector design. To simulate extended field usage in a short timeframe, an accelerated operating cycle was derived using telematics data. Injector samples were tested with periodic leak rate measurements. Conducting such tests at vehicle level or on engine test bench would involve significant time and cost. This setup is an effective tool for rapid comparative analysis across supplier design, enabling
The increasing adoption of electric vehicles (EVs) has intensified the demand for advanced elastomeric materials capable of meeting stringent noise, vibration and harshness (NVH) requirements. Unlike internal combustion engine (ICE) vehicles, EVs lack traditional masking noise generated by the powertrain. In the automotive industry, the dynamic stiffness of elastomers in internal combustion engines has traditionally been determined using hydraulic test rigs, with test frequencies limited to a maximum of 1,000 Hz. Measurements above this frequency range have not been possible and are conducted only through computerized FE or CAE calculation models. Electric drive systems, however, generate distinct tonal noise components in the high-frequency range up to 10,000 Hz, which are clearly perceptible even at low sound pressure levels. Consequently, the dynamic stiffness characteristics of elastomers up to 3,000 Hz are critical for optimizing NVH performance in EVs. This study focuses on high
The activation of the fuel injector affects both engine performance and pollutant emissions. However, the automotive industry restricts access to information regarding the circuits and control strategies used in its vehicles. One way to optimize fuel injections is using piezoelectric injectors. These injectors utilize crystals that expand or contract when subjected to an electric current, moving the injector needle. They offer a response time up to four times faster than solenoid-type injectors and allow for multiple injections per combustion cycle. These characteristics result in higher combustion efficiency, reduced emissions, and lower noise levels, making piezoelectric injectors widely used in next-generation engines, where stricter emission and efficiency standards are required. This study aims to design a drive circuit for piezoelectric injectors in a common rail system, intended for use in a diesel injector test bench. Experimental measurement of voltage was obtained from an
The European Space Agency (ESA) has added a micro-vibration test instrument, developed by the National Physical Laboratory (NPL), to its satellite testing facilities. NPL is the United Kingdom’s National Measurement Institute, developing and maintaining the national primary measurement standards. The instrument measures vibrations generated by satellite subsystems, to quantify their effects on images and measurements made from space. This facility is the result of five years of collaboration between NPL and ESA.
In the next years, the global hydrogen vehicle market is expected to grow at a very high rate. Consequently, it is necessary for scholars and professionals to study and test specific components in order to rise motor efficiency leveraging the new features of connectivity available in smart roads. In particular, our research is focused on the developement of an engine control module driven by evaluation of usage characteristics (e.g., driving style) and "connected-to-x" scenarios using the standard engine control approach. Moreover, the module proposed enables the implementation of "fast running" models to improve the response of vehicles and make the best possible use of H2-powered engine characteristics. That said, in this paper is proposed a new approach to implement the control module, using Support Vector Machine (SVM) as the machine learning algorithm to detect driving style, and consequently modify the parameters of the engine. We choose SVM because i) it is less prone to
This document establishes training guidelines applicable to fiber optic safety training, technical training and fiber awareness for individuals involved in the manufacturing, installation, support, integration and testing of fiber optic systems. Applicable personnel include: Managers Engineers Technicians Logisticians Trainers/Instructors Third Party Maintenance Agencies Quality Assurance Shipping Receiving Production Purchasing
This document provides user information on best practice methods and processes for the in-service inspection, evaluation, and cleaning of expanded beam (EB) fiber optic interconnect components (termini, alignment sleeves, and connectors), test equipment, and test leads based on the information provided in AIR6031 and ARP6283. This document provides the user with a decision-making tool to determine if the fiber optic components are acceptable for operation with EB fiber optic termini.
This paper presents a model-based systems engineering (MBSE) and digital twin approach for a military 6T battery tester. A digital twin architecture (encompassing product, process, and equipment twins) is integrated with AI-driven analytics to enhance battery defect detection, provide predictive diagnostics, and improve testing efficiency. The 6T battery tester’s MBSE design employs comprehensive SysML models to ensure traceability and robust system integration. Initial key contributions include early identification of battery faults via impedance-based sensing and machine learning, real-time state-of-health tracking through a synchronized virtual battery model, and streamlined test automation. Results indicate the proposed MBSE/digital twin solution can detect degradation indicators (e.g. capacity fade, rising internal impedance) earlier than traditional methods, enabling proactive maintenance and improved operational readiness. This approach offers a reliable, efficient testing
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