Study on Evaluation Method of Drivability of Hybrid Electric Vehicle Based on Ensemble Empirical Mode Decomposition Noise Reduction Method

2023-01-5083

11/22/2023

Features
Event
Automotive Technical Papers
Authors Abstract
Content
During the drivability test process, a large amount of noise generated by a series of internal and external factors of the vehicle reduces the accuracy of the drivability evaluation. To solve this problem, this paper introduces the EEMD denoising method and compares the denoising effects of the EMD denoising method and EEMD denoising method on the original signal using the entropy weight evaluation index. In addition, the optimal parameter setting is obtained by comparing the denoising results of different parameter settings in the EEMD denoising method. The results show that when the white noise is integrated 3000 times and the standard deviation of white noise is 0.1, the EEMD noise reduction method is the best, and the comprehensive score of noise reduction is 0.732 points higher than that of EMD. The research results indicate that the EEMD noise reduction method has a good noise reduction effect, which can ensure the accuracy of subsequent calculation of subsequent drivability indexes. It can be applied to the processing process of driving acceleration signals in hybrid vehicle acceleration conditions.
Meta TagsDetails
DOI
https://doi.org/10.4271/2023-01-5083
Pages
6
Citation
Cai, Q., Ou, Z., and Mo, M., "Study on Evaluation Method of Drivability of Hybrid Electric Vehicle Based on Ensemble Empirical Mode Decomposition Noise Reduction Method," SAE Technical Paper 2023-01-5083, 2023, https://doi.org/10.4271/2023-01-5083.
Additional Details
Publisher
Published
Nov 22, 2023
Product Code
2023-01-5083
Content Type
Technical Paper
Language
English