Browse Topic: Performance tests
The Vertical Lift Proprotor Noise Test (VLPNT) was a wind tunnel testing campaign in the NASA Langley Research Center's 14- by 22-Foot Subsonic Tunnel (14x22) aimed at measuring the aerodynamic performance and acoustic behavior of proprotors operating at conditions representative of vectored thrust UAM vehicles with articulating propulsors. This was a continuation of a proprotor performance test conducted previously in the same facility. A secondary objective of the VLPNT was to perform a scaling investigation on a subset of the tested proprotor geometries in an effort to identify low-Reynolds number impacts on performance and acoustics. It is hoped that the results of the VLPNT effort will provide modelers and vehicle developers with critical knowledge of the aerodynamic and acoustic behavior of proprotors during the transitional operating modes between vertical and axial forward flight.
As the utilization of lithium-ion batteries in electric vehicles expands, monitoring the usable cell capacity (UCC) is essential for ensuring accurate state-of-health (SOH) estimation. Battery performance degradation is influenced by temperature and constraints. Capacity tests in laboratory settings are typically conducted at low C-rates to approximate equilibrium conditions, whereas in real vehicle applications, charging currents are often much higher. This discrepancy in rates frequently results in deviations between laboratory characterization and on-board Battery Management Systems (BMS) capacity estimation. To investigate how C-rate of diagnostic Reference Performance Test (RPT) modulates aging effects under temperature and mechanical loading, we conducted long-term cycling tests on lithium iron phosphate/graphite pouch cells at 25°C and 45°C under different constrained conditions. The cycling protocol is a tiered multi-rate protocol. Cells were aged at Block1 under 1C, and UCC evolution was quantified after each block. The result shows battery aging can be divided into three stages: a decelerated, steady, and accelerated aging stage. The degradation of LFP cells is dominated by loss of lithium inventory (LLI), and elevated temperature accelerates the degradation. By combining differential voltage analysis (DVA), direct current internal resistance, electrochemical impedance spectroscopy, and ultrasonic testing, we found that under 45°C free condition, accelerated aging is consistent with intensified SEI growth and electrolyte decomposition, accompanied by increased LLI, gas-generation, and increased resistance. These signals emerge earlier than the apparent capacity divergence and may serve as early indicators for predicting the onset of rapid degradation. Appropriate constrain mitigates aging, and its influence becomes more pronounced when using higher-rate RPTs. At 25°C, high-rate RPTs exhibit an apparent capacity recovery. DVA analyses indicate the recovery originates from gradual activation of lithium. Overall, these findings illustrate and explain the degradation characteristics and capacity recovery phenomenon, providing a reference for connecting laboratory standard tests with on-board BMS capacity estimation.
This SAE Recommended Practice applies to mobile cranes when used in lifting crane service that are equipped with boom length indicating devices.
This paper describes the electromagnetic noise mitigation on the Maryland Tiltrotor Rig (MTR) and presents its first hover test results. The primary source of noise was found to be pulse width modulation associated with the motor controller. Due to this noise, testing was limited to unpowered, freewheeling cases. To solve the noise problem and allow powered testing, three hardware filters were integrated into the power and data systems. A complementary digital filter was also used. With the filtering solution in place, hover tests were carried out to high collectives of 30◦and blade loadings of 0.2. The test data was assessed using blade element-momentum theory predictions.
The integration of Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning (ML) has transformed various industries, offering substantial benefits. The application of these technologies in engine reliability testing has immense potential as they offer real-time monitoring and analysis of engine performance parameters. Engine reliability testing is vital for ensuring the safety, efficiency, and longevity of engines. Traditional methods are time consuming, expensive, and rely heavily on manual inspection and data analysis. This paper shows how IoT and ML technologies can enhance the efficiency of engine reliability testing. The paper includes the following case studies:
In 2023, Joby Aviation conducted a test of a prototype propeller for an electric vertical takeoff and landing (eVTOL) tilt-propeller aircraft in the 40- by 80-Foot Wind Tunnel at the National Full-Scale Aerodynamics Complex (NFAC). There were three objectives of the test: measuring 1) propeller performance, 2) dynamic blade loads, particularly in resonance, and 3) aeroacoustics. This paper is part of a trio and is focused on performance and blade loads measurements and validation; two companion papers cited in the text present an overview of the test and provide details on aeroacoustics analysis, respectively. Test measurements are compared to predictions generated by a CFD-trained model called AeroRef, the comprehensive analysis code RCAS with a finite state dynamic wake model, the Helios ROAM mid-fidelity blade loads solver coupled to RCAS, and OVERFLOW CFD coupled to RCAS. For performance, the AeroRef model and CFD were able to accurately predict thrust and rolling and pitching moments. RCAS was able to accurately predict structural dynamic modes and resonance crossings, but test measurements showed stronger modal responses than the dynamic inflow model was able to excite. Coupling RCAS with OVERFLOW resulted in excellent predictions of dynamic blade loads but at high computational cost; ROAM-RCAS coupling provided conservative predictions with a more efficient solver, demonstrating itself as a good option for eVTOL design studies.
Rotor skewing is a commonly used technique to mitigate noise and vibration challenges of permanent magnet synchronous motor. The intention of rotor skewing is to minimize targeted electromagnetic forces, thereby enhancing motor NVH performance. However, achieving improved NVH performance may be attainable by merely altering the rotor skew pattern while keeping the summation of radial and tangential electromagnetic forces the same. This research investigates the impact of different rotor skewing patterns on the NVH performance of permanent magnet synchronous motor. With summation of radial and tangential electromagnetic forces remaining the same, four different skew patterns are applied to generate electromagnetic forces across each motor slice. Multi-slice method is used for different skew patterns when applying electromagnetic forces on the motor model. Noise and vibration level will be compared to identify the best skew pattern for proposed motor.
A test and signal processing strategy was developed to allow a tire manufacturer to predict vehicle-level interior response based on component-level testing of a single tire. The approach leveraged time-domain Source-Path-Contribution (SPC) techniques to build an experimental model of an existing single tire tested on a dynamometer and substitute into a simulator vehicle to predict vehicle-level performance. The component-level single tire was characterized by its acoustic source strength and structural forces estimated by means of virtual point transformation and a matrix inversion approach. These source strengths and forces were then inserted into a simulator vehicle model to predict the acoustic signature, in time-domain, at the passenger’s ears. This approach was validated by comparing the vehicle-level prediction to vehicle-level measured response. The experimental model building procedure can then be adopted as a standard procedure to aid in vehicle development programs.
The Science and Technology Directorate's (S&T) National Urban Security Technology Laboratory (NUSTL) recently brought together emergency responders from across the nation to test unmanned aircraft systems (UAS) from the Blue UAS Cleared List. By providing an aerial vantage point, and creating standoff distance between responders and potential threats, UAS can significantly mitigate safety risks to responders by allowing them to assess and monitor incidents remotely. U.S. Department of Homeland Security, Washington, D.C. In November 2024, the U.S. Department of Homeland Security's (DHS) National Urban Security Technology Laboratory (NUSTL) teamed up with Mississippi State University's (MSU) Raspet Flight Research Laboratory, and DAGER Technology LLC, to conduct an assessment on selected models of cybersecure “Blue UAS.” The drones, including models from Ascent AeroSystems, Freefly Systems, Parrot Drones, Skydio, and Teal Drones, are cybersecure and commercially available to assist emergency responders with their public safety operations. These evaluations were a continuation of previous tests held in rural Texas last June. The overall goal was to assess various capabilities (e.g., camera visual acuity, latency, and command and control link quality) in different geographic settings and terrain.
Battery cell aging and loss of capacity are some of the many challenges facing the widespread implementation of electrification in mobility. One of the factors contributing to cell aging is the dissimilarities of individual cells connected in a module. This paper reports the results of several aging experiments using a mini-module consisting of seven 5 Ah 21700 lithium-ion battery cells connected in parallel. The aging cycle comprised a constant current-constant voltage charge cycle at a 0.7C C-rate, followed by a 0.2C constant current discharge, spanning the useful voltage range from minimum to maximum according to the cell manufacturer. Charge and discharge events were separated by one-hour rest periods and were repeated for four weeks. Weekly reference performance tests were executed to measure static capacity, pulse power capability and resistance at different states of charge. All diagnostics were normalized with respect to their starting numbers to achieve a percentage change over time. Both electrical and thermal dissimilarities were considered by initial cell selection or adjusting the thermal boundary conditions, respectively. The latter was achieved by contrasting air cooling with direct liquid immersion cooling which prevented temperature spikes and ensured more uniform temperature distribution between the cells. For well-clustered cells, the use of immersion cooling reduced the capacity fade noticeably when compared to air cooling. However, when cells are not well clustered, the impact of electrical dissimilarities overshadowed the thermal benefits. Poor cell clustering resulted in a lower discharge resistance increase which itself reflected as smaller changes of the pulse power fade. The results highlighted the importance of cell selection and clustering during research and when building packs for final application and reinforced the benefits of good thermal management. The work did not fully explore the benefits of immersion cooling due to the moderate C-rates used.
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