Browse Topic: Measurements
The design and improvement of electric motor and inverter systems is crucial for numerous industrial applications in electrical engineering. Accurately quantifying the amount of power lost during operation is a substantial challenge, despite the flexibility and widespread usage of these systems. Although it is typically used to assess the system’s efficiency, this does not adequately explain how or why power outages occur within these systems. This paper presents a new way to study power losses without focusing on efficiency. The goal is to explore and analyze the complex reasons behind power losses in both inverters and electric motors. The goal of this methodology is to systematically analyze the effect of the switching frequency on current ripple under varying operating conditions (i.e., different combinations of current and speed) and subsequently identify the optimum switching frequency for each case. In the end, the paper creates a complete model for understanding power losses
With the rapid adoption of electric vehicles (EVs), ensuring the reliability, safety, and cost-effectiveness of power electronic subsystems such as onboard chargers, DC-DC converters, and vehicle control units (VCUs) has become a critical engineering focus. These components require thorough validation using precise calibration and communication protocols. This paper presents the development and implementation of an optimized software stack for the Universal Measurement and Calibration Protocol (XCP), aimed at real-time validation of VCUs using next-generation communication methods such as CAN, CAN-FD, and Ethernet. The stack facilitates read/write access to the ECU’s internal memory in runtime, enabling efficient diagnostics, calibration, and parameter tuning without hardware modifications. It is designed to be modular, platform-independent, and compatible with microcontrollers across different EV platforms. By utilizing the ASAM-compliant protocol architecture, the proposed system
In recent times, a standard driving cycle is an excellent way to measure the electric range of EVs. This process is standardized and repeatable; however, it has some drawbacks, such as low active functions being tested in a controlled environment. This sometimes causes huge variations in the range between driving cycles and actual on-road tests. This problem of variation can be solved by on-road testing and testing a vehicle for customer-based velocity cycles. On-road measurement may be high on active functions while testing, which may give an exact idea of real-world consumption, but the repeatability of these test procedures is low due to excessive randomness. The repeatability of these cycles is low due to external factors acting on the vehicle during on-road testing, such as ambient temperature, driver behavior, traffic, terrain, altitude, and load conditions. No two measurements can have the same consumption, even if they are done on the same road with the same vehicle, due to the
The effective measurement and verification of dimensional stability indicators for large size and highly stable structures in service environments is the key to the development of high-precision spacecraft technology. Spatial carrier speckle interferometry technology has been widely used for high-precision measurements in recent years due to its advantages of fast speed, high accuracy, and simple operation. However, the existing technical research only focuses on the measurement under normal temperature and pressure environments, and there is little research on the application under complex operating conditions in space. There is currently no relevant research on the impact of system ambient vibration and noise on measurement stability disturbances. In response to the above issues, a high-precision deformation measurement system suitable for complex environments of high and low temperatures in a vacuum was designed based on spatial carrier measurement technology. A system measurement
In vehicle development, occupant-centered design is crucial to ensuring customer satisfaction. Key factors such as visibility, access, interior roominess, driver ergonomics, interior storage and trunk space directly impact the daily experience of vehicle occupants. While automakers rely on engineering metrics to guide architectural decisions, however in some cases doesn’t exist a clear correlation between these quantitative parameters and the subjective satisfaction of end users. This study develops a methodology which addresses that gap by proposing the creation of quantitative satisfaction curves for critical engineering metrics, providing a robust tool to support decision-making during the early stages of vehicle design. Through a combination of clinics, research, and statistical analysis, this project outlines a step-by-step process for developing (dis)satisfaction curves, offering a clearer understanding of how dimensions like headroom, glove box volume, and A-pillar obscuration
Occupant comfort is a fundamental consideration during the early stages of vehicle development, with internal spaciousness serving as a key pillar in creating a pleasant in-cabin experience. Among the various factors that contribute to this perception, legroom plays a particularly significant role, especially for rear-seat passengers. This study investigates the relationship between second-row legroom and occupant satisfaction under real-world driving conditions, employing a combination of research, statistical data analysis, and dynamic clinics to assess perceptual comfort. The findings reveal that shin and leg heights are the primary drivers of satisfaction or discomfort, while gender and overall height exhibit only minor influences on perceived comfort. Additionally, the study highlights the importance of other interior dimensions, such as shoulder room, knee clearance, and chair height, in shaping overall comfort since if they were poorly chosen, they would have affected clinic
In recent decades, vehicles have evolved from mere means of individual transportation to something much more meaningful. They are no longer mere metal bodies housing combustion engines, but now play a complex role in people’s lives, encompassing emotional, aesthetic, and symbolic aspects. These factors influence consumers’ choice of a model, brand, or version. Based on a literature review of the global automotive sector, including brand literature, scientific articles, and current automotive news, this study aims to analyze the main design and positioning trends adopted by large multinationals in the market. Using the Jeep Renegade as a case study, three design proposals for the model are illustrated and presented as follows: a “facelift,” a “new generation,” and a “concept vehicle.” Next, these design trends are conceptualized, initially illustrating the respective sketches and drafts, which take into account market positioning and the different options for the models presented in
In the race toward practical quantum computers and networks, photons — fundamental particles of light — hold intriguing possibilities as fast carriers of information at room temperature. Photons are typically controlled and coaxed into quantum states via waveguides on extended microchips, or through bulky devices built from lenses, mirrors, and beam splitters. The photons become entangled — enabling them to encode and process quantum information in parallel — through complex networks of these optical components. But such systems are notoriously difficult to scale up due to the large numbers and imperfections of parts required to do any meaningful computation or networking.
Innovators at NASA Johnson Space Center have developed a technology that can isolate a single direction of tensile strain in biaxially woven material. This is accomplished using traditional digital image correlation (DIC) techniques in combination with custom red-green-blue (RGB) color filtering software. DIC is a software-based method used to measure and characterize surface deformation and strain of an object. This technology was originally developed to enable the extraction of circumferential and longitudinal webbing strain information from material comprising the primary restraint layer that encompasses inflatable space structures.
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.
The global electronics supply chain has always run in cycles — tight supply followed by sudden gluts — but in recent years, the pace and scale of disruption have accelerated. From semiconductor shortages to shifting trade policies and pandemic-driven bottlenecks, OEMs across every sector have been forced to rethink how they source and secure critical components.
Accurate defect quantification is crucial for ensuring the serviceability of aircraft engine parts. Traditional inspection methods, such as profile projectors and replicating compounds, suffer from inconsistencies, operator dependency, and ergonomic challenges. To address these limitations, the 4D InSpec® handheld 3D scanner was introduced as an advanced solution for defect measurement and analysis. This article evaluates the effectiveness of the 4D InSpec scanner through multiple statistical methods, including Gage Repeatability and Reproducibility (Gage R&R), Isoplot®, Youden plots, and Bland–Altman plots. A new concept of Probability of accurate Measurement (PoaM)© was introduced to capture the accuracy of the defect quantification based on their size. The results demonstrate a significant reduction in measurement variability, with Gage R&R improving from 39.9% (profile projector) to 8.5% (3D scanner), thus meeting the AS13100 Aerospace Quality Standard. Additionally, the 4D InSpec
In contemporary society, where Global Navigation Satellite Systems (GNSS) are utilised extensively, their inherent fragility gives rise to potential hazards with respect to the safety of ship navigation. In order to address this issue, the present study focuses on an ASM signal delay measurement system based on software defined radio peripherals. The system comprises two distinct components: a transmitting end and a receiving end. At the transmitting end, a signal generator, a first time-frequency synchronisation device, and a VHF transmitting antenna are employed to transmit ASM signals comprising dual Barker 13 code training sequences. At the receiving end, signals are received via software-defined radio equipment, a second time-frequency synchronisation device, a computing host, and a VHF receiving antenna. Utilising sliding correlation algorithms enables accurate time delay estimation. The present study leverages the high performance and low cost advantages of the universal
Large farms cultivating forage crops for the dairy and livestock sectors require high-quality, dense bales with substantial nutritional value. The storage of hay becomes essential during the colder winter months when grass growth and field conditions are unsuitable for animal grazing. Bale weight serves as a critical parameter for assessing field yields, managing inventory, and facilitating fair trade within the industry. The agricultural sector increasingly demands innovative solutions to enhance efficiency and productivity while minimizing the overhead costs associated with advanced systems. Recent weighing system solutions rely heavily on load cells mounted inside baling machines, adding extra costs, complexity and weight to the equipment. This paper addresses the need to mitigate these issues by implementing an advanced model-based weighing system that operates without the use of load cells, specifically designed for round baler machines. The weighing solution utilizes mathematical
The first step in designing or analyzing any structure is to understand “right” set of loads. Typically, off-road vehicles have many access doors for service or getting into cab etc. Design of these doors and their latches involve a knowledge of the loads arising when the door is shut which usually involves an impact of varying magnitudes. In scenarios of these impact events, where there is sudden change of velocity within few milliseconds, produces high magnitude of loads on structures. One common way of estimating these loads using hand calculations involves evaluating the rate-of-change-of-momentum. However, this calculation needs “duration of impact”, and it is seldom known/difficult to estimate. Failing to capture duration of impact event will change load magnitudes drastically, e.g. load gets doubled if time-of-impact gets reduced from 0.2 to 0.1 seconds and subsequently fatigue life of the components in “Door-closing-event” gets reduce by ~7 times. For these problems, structures
Measuring the volume of harvested material behind the machine can be beneficial for various agricultural operations, such as baling, dropping, material decomposition, cultivation, and seeding. This paper aims to investigate and determine the volume of material for use in various agricultural operations. This proposed methodology can help to predict the amount of residue available in the field, assess field readiness for the next production cycle, measure residue distribution, determine hay readiness for baling, and evaluate the quantity of hay present in the field, among other applications which would benefit the customer. Efficient post-harvest residue management is essential for sustainable agriculture. This paper presents an Automated Offboard System that leverages Remote Sensing, IoT, Image Processing, and Machine Learning/Deep Learning (ML/DL) to measure the volume of harvested material in real-time. The system integrates onboard cameras and satellite imagery to analyze the field
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