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Journal Articles
Publisher: ASME
Article Type: Research Papers
J. Electrochem. En. Conv. Stor. August 2025, 22(3): 031008.
Paper No: JEECS-24-1044
Published Online: October 7, 2024
Image
in A Fault Diagnosis Method for Electric Vehicle Lithium Power Batteries Based on Dual-Feature Extraction From the Time and Frequency Domains
> Journal of Electrochemical Energy Conversion and Storage
Published Online: October 7, 2024
Fig. 1 ( a ) Three-layer wavelet packet decomposition process and ( b ) examples of subband sequences More about this image found in ( a ) Three-layer wavelet packet decomposition process and ( b ) examples o...
Image
in A Fault Diagnosis Method for Electric Vehicle Lithium Power Batteries Based on Dual-Feature Extraction From the Time and Frequency Domains
> Journal of Electrochemical Energy Conversion and Storage
Published Online: October 7, 2024
Fig. 2 Overall flowchart of time-domain feature extraction based on FGAE More about this image found in Overall flowchart of time-domain feature extraction based on FGAE
Image
in A Fault Diagnosis Method for Electric Vehicle Lithium Power Batteries Based on Dual-Feature Extraction From the Time and Frequency Domains
> Journal of Electrochemical Energy Conversion and Storage
Published Online: October 7, 2024
Fig. 3 ( a ) FGAE refactoring effect demonstration, ( b ) AE reconstruction effect demonstration, and ( c ) extract fault feature results and compare More about this image found in ( a ) FGAE refactoring effect demonstration, ( b ) AE reconstruction effect...
Image
in A Fault Diagnosis Method for Electric Vehicle Lithium Power Batteries Based on Dual-Feature Extraction From the Time and Frequency Domains
> Journal of Electrochemical Energy Conversion and Storage
Published Online: October 7, 2024
Fig. 4 Euclidean distance, correlation coefficient, and cosine similarity obtained feature results More about this image found in Euclidean distance, correlation coefficient, and cosine similarity obtained...
Image
in A Fault Diagnosis Method for Electric Vehicle Lithium Power Batteries Based on Dual-Feature Extraction From the Time and Frequency Domains
> Journal of Electrochemical Energy Conversion and Storage
Published Online: October 7, 2024
Fig. 5 Frequency domain feature extraction flowchart based on wavelet packet energy spectrum More about this image found in Frequency domain feature extraction flowchart based on wavelet packet energ...
Image
in A Fault Diagnosis Method for Electric Vehicle Lithium Power Batteries Based on Dual-Feature Extraction From the Time and Frequency Domains
> Journal of Electrochemical Energy Conversion and Storage
Published Online: October 7, 2024
Fig. 6 The frequency domain features proposed in this article, spectral entropy and spectral flatness proposed characterization results More about this image found in The frequency domain features proposed in this article, spectral entropy an...
Image
in A Fault Diagnosis Method for Electric Vehicle Lithium Power Batteries Based on Dual-Feature Extraction From the Time and Frequency Domains
> Journal of Electrochemical Energy Conversion and Storage
Published Online: October 7, 2024
Fig. 7 Flowchart of fault diagnosis More about this image found in Flowchart of fault diagnosis
Image
in A Fault Diagnosis Method for Electric Vehicle Lithium Power Batteries Based on Dual-Feature Extraction From the Time and Frequency Domains
> Journal of Electrochemical Energy Conversion and Storage
Published Online: October 7, 2024
Fig. 8 Original data curve More about this image found in Original data curve
Image
in A Fault Diagnosis Method for Electric Vehicle Lithium Power Batteries Based on Dual-Feature Extraction From the Time and Frequency Domains
> Journal of Electrochemical Energy Conversion and Storage
Published Online: October 7, 2024
Fig. 9 Reconstructed voltage curves using different wavelet functions for a three-level wavelet packet decomposition: ( a ) original data, ( b ) Symlets, ( c ) Biorthogonal, ( d ) Haar, ( e ) Daubechies, and ( f ) Meyer More about this image found in Reconstructed voltage curves using different wavelet functions for a three-...
Image
in A Fault Diagnosis Method for Electric Vehicle Lithium Power Batteries Based on Dual-Feature Extraction From the Time and Frequency Domains
> Journal of Electrochemical Energy Conversion and Storage
Published Online: October 7, 2024
Fig. 10 Reconstructed voltage curves using wavelet packet decomposition at different levels: ( a ) 2-level decomposition, ( b ) 3-level decomposition, and ( c ) 4-level decomposition More about this image found in Reconstructed voltage curves using wavelet packet decomposition at differen...
Image
in A Fault Diagnosis Method for Electric Vehicle Lithium Power Batteries Based on Dual-Feature Extraction From the Time and Frequency Domains
> Journal of Electrochemical Energy Conversion and Storage
Published Online: October 7, 2024
Fig. 11 ( a ) Feature maps obtained for signals processed without noise reduction, ( b ) feature extraction results in time domain, ( c ) feature extraction results in frequency domain, and ( d ) isolated forest outlier detection results More about this image found in ( a ) Feature maps obtained for signals processed without noise reduction, ...
Image
in A Fault Diagnosis Method for Electric Vehicle Lithium Power Batteries Based on Dual-Feature Extraction From the Time and Frequency Domains
> Journal of Electrochemical Energy Conversion and Storage
Published Online: October 7, 2024
Fig. 12 Fault diagnosis results for ( a ) LOF, ( b ) DBSCAN, and ( c ) isolated forest More about this image found in Fault diagnosis results for ( a ) LOF, ( b ) DBSCAN, and ( c ) isolated for...
Image
in A Fault Diagnosis Method for Electric Vehicle Lithium Power Batteries Based on Dual-Feature Extraction From the Time and Frequency Domains
> Journal of Electrochemical Energy Conversion and Storage
Published Online: October 7, 2024
Fig. 13 Vehicle 2 raw data More about this image found in Vehicle 2 raw data
Image
in A Fault Diagnosis Method for Electric Vehicle Lithium Power Batteries Based on Dual-Feature Extraction From the Time and Frequency Domains
> Journal of Electrochemical Energy Conversion and Storage
Published Online: October 7, 2024
Fig. 14 ( a ) Vehicle 2 time-domain fault feature extraction results, ( b ) fault feature extraction results in frequency domain, and ( c ) outlier detection results More about this image found in ( a ) Vehicle 2 time-domain fault feature extraction results, ( b ) fault f...
Image
in A Fault Diagnosis Method for Electric Vehicle Lithium Power Batteries Based on Dual-Feature Extraction From the Time and Frequency Domains
> Journal of Electrochemical Energy Conversion and Storage
Published Online: October 7, 2024
Fig. 15 Detection results of unidimensional outliers in time domain and frequency domain for two vehicles: ( a ) time-domain characteristics of vehicle 1, ( b ) vehicle 1 frequency domain characteristics, ( c ) time-domain characteristics of vehicle 2, and ( d ) vehicle 2 frequency domain characte... More about this image found in Detection results of unidimensional outliers in time domain and frequency d...
Journal Articles
Publisher: ASME
Article Type: Research Papers
J. Electrochem. En. Conv. Stor. August 2025, 22(3): 031007.
Paper No: JEECS-24-1077
Published Online: September 30, 2024
Journal Articles
Accepted Manuscript
Publisher: ASME
Article Type: Research Papers
J. Electrochem. En. Conv. Stor.
Paper No: JEECS-24-1106
Published Online: September 30, 2024
Journal Articles
Accepted Manuscript
Publisher: ASME
Article Type: Research Papers
J. Electrochem. En. Conv. Stor.
Paper No: JEECS-24-1121
Published Online: September 30, 2024
Image
in Effects of Sintering Temperature on the Electrical Performance of Ce 0.8 Sm 0.2 O 1.9 –Pr 2 NiO 4 Composite Electrolyte for SOFCs
> Journal of Electrochemical Energy Conversion and Storage
Published Online: September 30, 2024
Fig. 1 XRD patterns of SDC, PNO, and SDC–PNO composites at different sintering temperatures More about this image found in XRD patterns of SDC, PNO, and SDC–PNO composites at different sintering tem...
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