Browse Topic: Calibration
This SAE Aerospace Recommended Practice (ARP) provides recommended practices for the calibration and acceptance of icing wind tunnels to be used in testing of aircraft components and systems and for the development of simulated ice shapes. This document is not directly applicable to air-breathing propulsion test facilities configured for the purposes of engine icing tests, which are covered in AIR6189. This document also does not provide recommended practices for creating Supercooled Large Drop (SLD) or ice crystal conditions, since information on these conditions is not sufficiently mature for a recommended practice document at the time of publication of ARP5905A. Use of facilities as part of an aircraft’s ice protection Certification Plan should be reviewed and accepted by the applicable regulatory agency prior to testing. Following acceptance of a test plan, data generated in these facilities may be submitted to regulatory agencies for use in the certification of aircraft ice
Calibrated Accelerated Life Testing (CALT) is a sequential and quantitative method for Accelerated Life Testing (ALT). Its design aims to optimize test efficiency by minimizing both test duration and sample size while estimating product life. In the CALT context, the focus is on testing samples under three or more distinct stresses or loads to estimate the life span/BX life, which is a crucial parameter in reliability estimation. Determining the first load in CALT typically involves exploratory testing on a limited number of specimens and relies heavily on engineering judgments such as analyzing Finite Element Analysis (FEA) outcomes, referencing test data from comparable designs and materials, and considering stiffness results etc. This often leads to challenges in accurately identifying the first load/stress. To address this issue, we propose a systematic step-stress test approach instead of exploratory testing. This approach aims to efficiently identify the first load in CALT. The
ABSTRACT In this context, a damage model is a mathematical algorithm that is used to predict if and when in a given loading history a structure will fail by ductile fracture. Increments in a damage parameter are related to strain increments and state of stress. The damage model would operate as part of a numerical simulation, or separately on an output file. A scale effect in ductile fracture is widely recognized from test data, where a large structure tends to fail at lower strain than a smaller structure that is geometrically similar and of the same material. Most damage models are not scale sensitive, and when they are calibrated to data from small laboratory specimens, they will tend to over-predict the performance (i.e., energy absorbing capability) of a larger structure. Another factor is scatter in test results even when specimens are made with care to be as identical as possible. Both of these factors are addressed in the proposed statistics-based damage model. Scale effects
ABSTRACT This paper will incorporate product development methodology from the FED program where AVL is responsible in collaboration with World Technical Services Inc., for delivering a fully developed hybrid propulsion system integrated into the demonstrator vehicle. Specifically, the paper will discuss via case study the unique methodology employed by AVL Powertrain to develop, validate, and integrate our hybrid propulsion system into the FED vehicle. Content will include traditional and virtual powertrain development methodologies that maximize product development efficiency, ensure a robust final design, and minimize development costs. Hybrid controls development, calibration techniques and vehicle design issues will also be discussed
ABSTRACT Due to the high complexity of modern internal combustion engines and powertrain systems, the proper calibration of the electronic control unit’s (ECU) parameters has a strong impact on project targets like fuel consumption, emissions and drivability, as well as development costs and project duration. Simulation methods representing the system behavior with a model can support the calibration process considerably. However, standard physics-based models are often not able to describe all effects with sufficient accuracy, or the effort to set up a detailed model is too high. Physics-based models can also have a high computational demand, so that their simulation is not real-time capable. More suited for ECU calibration are data-driven models, combined with Design of Experiment (DoE). The system to be calibrated is identified with few specific test bench or vehicle measurements. From these measurements, a mathematical regression model is built. This paper describes recently
ABSTRACT Modern electronic control units (ECUs) typically contain many physically based models represented by a complex structure of maps, curves and scalar parameters. The purpose of these models is to monitor or predict engine values that are normally measured by actual sensors. If the model structure is a good representation of the physical system and the parameters are well fitted, such a model can replace the sensor and serve as a virtual sensor to reduce the cost and complexity of the overall system. Virtual sensors are commonly used in the ECU for predicting engine torque, air pressure and flow, emissions, catalyst temperature, and exhaust gas temperatures. To ensure an optimal prediction quality of these models, their parameters need to be calibrated using real measurement data collected, e.g., in the vehicle or in the test cell. Due to the models’ complexity and the high number of parameters, a manual calibration is very time consuming or even impossible. Instead, iterative
Researchers at the National Institute of Standards and Technology (NIST) and colleagues have developed standards and calibrations for optical microscopes that allow quantum dots to be aligned with the center of a photonic component to within an error of 10 to 20 nanometers (about one-thousandth the thickness of a sheet of paper). Such alignment is critical for chip-scale devices that employ the radiation emitted by quantum dots to store and transmit quantum information
Severe problem of aerodynamic heating and drag force are inherent with any hypersonic space vehicle like space shuttle, missiles etc. For proper design of vehicle, the drag force measurement become very crucial. Ground based test facilities are employed for these estimates along with any suitable force balance as well as sensors. There are many sensors (Accelerometer, Strain gauge and Piezofilm) reported in the literature that is used for evaluating the actual aerodynamic forces over test model in high speed flow. As per previous study, the piezofilm also become an alternative sensor over the strain gauges due to its simple instrumentation. For current investigation, the piezofilm and strain gauge sensors have mounted on same stress force balance to evaluate the response time as well as accuracy of predicted force at the same instant. However, these force balance need to be calibrated for inverse prediction of the force from recorded responses. A reliable multi point calibration
This SAE Aerospace Recommended Practice (ARP) addresses the general procedure for the best practices for minimizing uncertainty when calibrating thermal conductivity and cold cathode vacuum gauges, which includes the vacuum sensor(s) and accompanying electronics necessary for a pressure measurement to be made. It also includes the best practices for an in-process verification where limitations make it impossible to follow the best practices for minimizing uncertainty. Verifying the accuracy and operation of vacuum gauges is critical to ensure the maintenance of processes while under vacuum
This study presents the constructed electromechanical model and the analysis of the obtained nonlinear systems. An algorithm for compensating the nonlinear drift of a gyroscope in a microelectromechanical system is proposed. Tests were carried out on a precision rotating base, with the angular velocity changing as per the program. Bench testing the gyroscope confirmed the results, which were also supported by the parameter calibration. The analytical method was further validated through experimental results, and a correction algorithm for the mathematical model was developed based on the test results. After calibration and adjusting the gyroscope’s systematic flaws, the disparity in calculating the precession angle was within 1/100th of an angular second over an interval of approximately 1000 s. Currently, research is underway on the new nonlinear dynamic characteristics of electrostatically controlled microstructures. The results of the integrated navigation system of small satellites
This paper gives insights in the theoretical measurement uncertainty of E-Drive rotor position dependent results, like Id and Iq calculations, done by a modern propulsion power analyzer (PA). The calculation of Id and Iqis fundamental to perform control optimization and application tasks for an E-Drive system. To optimize the E-Drive system application towards e.g., best efficiency, best performance, or improved NVH the importance of the testing toolchain is described: a power analyzer delivering the required results, an automation system, and a Design of Experiment tool to set improved target values. Consequently, inverters applications featuring field-oriented control (FOC) with permanent magnet synchronous machines (PMSM) are updated with a chosen control strategy. For achieving a certain behavior of an E-Drive, different degrees of freedom in the Inverter Control Unit are available; Lookup tables Id and Iq represent two fundamental application labels to be considered. Since the
The automobile industry is going through one of the most challenging times, with increased competition in the market which is enforcing competitive prices of the products along with meeting the stringent emission norms. One such requirement for BS6 phase 2 emission norms is monitoring for partial failure of the component if the tailpipe emissions are higher than the OBD limits. Recently PM (soot) sensor is employed for partial failure monitoring of DPF in diesel passenger cars.. PM sensor detects soot leakage in case of DPF substrate failure. There is a cost factor along with extensive calibration efforts which are needed to ensure sensor works flawlessly. This paper deals with the development of an algorithm with which robust detection of DPF substrate failure is achieved without addition of any sensor in the aftertreatment system. In order to achieve this, a thermodynamic model of DPF substate was created using empirical relations between parameters like exhaust flow rate, exhaust
This paper introduces a novel approach to automate PID calibration for closed-loop control systems and the creep control function in an electric vehicle. Through a comprehensive literature survey, it is found that this method is the first of its kind to be applied in the field of automated electric vehicle calibration for Creep function. The proposed approach utilizes a systematic methodology that automatically tunes the PID parameters based on predefined performance criteria, including energy consumption and jerk. To implement this methodology, the ETAS INCA FLOW software, which provides guided calibration methods for in-vehicle testing & calibration, is employed. The calibration process is performed on a real-time electric vehicle platform to validate the effectiveness of the proposed approach. The results of this study showcases the advantages of automated PID calibration for closed-loop control systems and creep control function in small commercial electric vehicle. The proposed
This Aerospace Recommended Practice (ARP) describes a standard method and means for measuring or calibrating the "Spectrum Amplitude" output of an impulse generator
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