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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 271 records · Page 15

Optimization of Air-Gap Profile in Interior Permanent-Magnet Synchronous Motors for Torque Ripple Mitigation

Interior permanent magnet synchronous motors (IPMSMs) have been widely used due to their high efficiency and high power density. Minimization of torque pulsation resulting in vibration and acoustic noise is one of the important design considerations for IPMSMs. In this paper, a grid on/off search method for the rotor profile is proposed to mitigate torque pulsation. Selection of the rotor profile is due to the fact that air-gap is the most sensitive parameter in electric machines wherein changes in flux densities can cause substantial differences in the distribution of forces. A layer comprised of 20 partitions with a 0.1 mm thickness and 3 degrees wide grids have been introduced to the rotor surface for each pole and the possible geometries have been analyzed using finite element method (FEM) in ANSYS Maxwell. An optimal design was found that has the lowest torque ripple with a higher average torque compared to the original design. Genetic algorithm (GA) has also been applied to the method to automate the coupling between Maxwell and Matlab thereby saving the simulation time. Finally, complete structural analysis has been done for both of the original and optimal designs to verify the superiority and feasibility of the proposed design.

42 ENGINEERING↗

Asymmetrical Magnet Shape Optimization Based on S-C Mapping for Torque Profile Mitigation in Unidirectional Application of SPMS Machine

Surface-mounted Permanent Magnet Synchronous (SPMS) machines are widely used in applications that require low torque ripple, reduced vibration and acoustic noise. For those applications of SPMSM in which only unidirectional operation is needed, asymmetric design optimization show to have significant advantages over symmetric designs. In this paper, an analytical method based on Schwarz -Christoffel mapping is presented for asymmetrical magnet shape optimization in SPMS machine. In this method, permanent magnet is divided into finite cells so that each cell can be assigned with either air (OFF) or magnet (ON). The Optimization problem is solved using Genetic Algorithms (GAs). In order to remove non-manufacturable shapes, the cluster of materials and cleaning method is used and applied into magnet cells. The analytical method can significantly reduce the computation time used by optimization process as compared with methods based on Finite Element Analysis (FEA). This method is applied to a 12-pole SPMS machine. Validation of the S-C mapping method and final results are carried out using 2D and 3D finite element analysis. Here, the results obtained demonstrate that asymmetrical magnet shape improves cogging torque and torque ripple performance of SPMS machine by a significant margin.

42 ENGINEERING↗

Source identification in acoustics and structural mechanics using Sierra/SD.

In this report we derive both time and frequency-domain methods for inverse identification of sources in elastodynamics and acoustics. The inverse/design problem is cast in a PDE-constrained optimization framework with efficient computation of gradients using the adjoint method. The implementation of source inversion in Sierra/SD is described, and results from both time and frequency domain source inversion are compared to actual experimental data for a weapon store used in captive carry on a military aircraft. The inverse methodology is advantageous in that it provides a method for creating ground based acoustic and vibration tests that can reduce the actual number of flight tests, and thus, saving costs and time for the program.

Walsh, Timothy Francis↗

Condition monitoring of wind turbine drivetrains: state-of-the-art technologies, recent trends, and future outlook

As global wind capacity expands, reducing operations and maintenance costs is critical to lowering the levelized cost of energy. This paper explores the state of the art in condition monitoring and prognostic strategies for wind turbine drivetrains, which are among the most failure-prone and maintenance-intensive subsystems. Current diagnostic methodologies are evaluated, covering supervisory control and data acquisition (SCADA) data, high-frequency vibration and acoustic analysis, machine learning and digital twin frameworks. Finally, practical challenges are identified that limit wide-scale industrial adoption, in order to guide future research and industrial efforts.

17 WIND ENERGY↗

Single sideband FM telemetry.

Single-sideband FM for data transmission on vibration and acoustic measurements, noting SNR PERFORMANCE, transmission link, etc

FREQUENCY MODULATION↗