Related Experiment Video
Updated: Jun 17, 2025
10:22
Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements
Published on: September 7, 2019
8.2K
An Application of Uncertainty Quantification to Efficiency Measurements and Validating Requirements through
Michael Leighton1, Uday Akasapu2
1AVL List GmbH, 8020 Graz, Austria.
Sensors (Basel, Switzerland)
|August 10, 2024
Summary
This study demonstrates uncertainty quantification for electric drive unit efficiency testing. It improves confidence in simulations and validates test results by analyzing measurement errors.
Area of Science:
- Engineering
- Metrology
- Automotive Engineering
Background:
- Product development relies heavily on validation to meet design goals and mitigate risks.
- Electric Drive Units (EDUs) are critical components in modern vehicles, requiring rigorous testing.
- Accurate efficiency testing is essential for EDU performance and reliability.
Purpose of the Study:
- To demonstrate uncertainty quantification (UQ) for Electric Drive Unit (EDU) efficiency testing.
- To enhance confidence in simulation results within the validation process.
- To assess requirement coverage and validate test outcomes by analyzing measurement uncertainties.
Main Methods:
- Utilized the framework from the Guide to the Expression of Uncertainty in Measurement (GUM) for UQ.
- Performed an analytical evaluation of the measurement chain for EDU efficiency testing.
- Derived elemental uncertainties and propagated them to the derived quantity of efficiency.
Main Results:
- Identified erroneous measurements within the sensor-based measurement chain.
- Quantified the uncertainty associated with EDU efficiency measurements.
- Provided a basis for assessing requirement coverage and validating test results.
Conclusions:
- UQ is crucial for reliable EDU efficiency validation.
- Analysis of measurement uncertainty highlights potential errors in the testing process.
- This methodology enhances the credibility of validation campaigns and informs design improvements.
Related Concept Videos
00:59Uncertainty: Overview
531
In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.
531
03:37Uncertainty in Measurement: Accuracy and Precision
73.6K
Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value.
73.6K
00:59Propagation of Uncertainty from Random Error
659
An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
659
02:46Uncertainty in Measurement: Reading Instruments
38.0K
Counting is the type of measurement that is free from uncertainty, provided the number of objects being counted does not change during the process. Such measurements result in exact numbers. By counting the eggs in a carton, for instance, one can determine exactly how many eggs are there in the carton. Similarly, the numbers of defined quantities are also exact. For example, 1 foot is exactly 12 inches, 1 inch is exactly 2.54 centimeters, and 1 gram is exactly 0.001 kilograms. Quantities...
38.0K
01:05Estimation of the Physical Quantities
4.2K
On many occasions, physicists, other scientists, and engineers need to make estimates of a particular quantity. These are sometimes referred to as guesstimates, order-of-magnitude approximations, back-of-the-envelope calculations, or Fermi calculations. The physicist Enrico Fermi was famous for his ability to estimate various kinds of data with surprising precision. Estimating does not mean guessing a number or a formula at random. Instead, estimation means using prior experience and sound...
4.2K
04:08The Uncertainty Principle
23.2K
Werner Heisenberg considered the limits of how accurately one can measure properties of an electron or other microscopic particles. He determined that there is a fundamental limit to how accurately one can measure both a particle’s position and its momentum simultaneously. The more accurate the measurement of the momentum of a particle is known, the less accurate the position at that time is known and vice versa. This is what is now called the Heisenberg uncertainty principle. He...
23.2K