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- Title
Uncertainty Quantification and Optimal Design of EV-WPT System Efficiency based on Adaptive Gaussian Process Regression.
- Authors
Xinlei Shang; Linlin Xu; Quanyi Yu; Bo Li; Gang Lv; Yaodan Chi; Tianhao Wang
- Abstract
Wireless power transfer (WPT) is a safe, convenient, and intelligent charging solution for electric vehicles. To address the problem of the susceptibility of transmission efficiency to large uncertainties owing to differences in coil and circuit element processing and actual driving levels, this study proposes the use of adaptive Gaussian process regression (aGPR) for the uncertainty quantification of efficiency. A WPT system efficiency aGPR surrogate model is constructed with a set of selected small-sample data, and the confidence interval and probability density function of the transmission efficiency are predicted. Finally, the reptile search algorithm is used to optimize the structure of the WPT system to improve efficiency.
- Subjects
KRIGING; WIRELESS power transmission; PROBABILITY density function; ELECTRIC charge; CIRCUIT elements; RADAR in aeronautics
- Publication
Applied Computational Electromagnetics Society Journal, 2023, Vol 38, Issue 12, p929
- ISSN
1054-4887
- Publication type
Article
- DOI
10.13052/2023.ACES.J.381202