During the wireless power transmission of an electric vehicle (EV), due to the influence of the compensation circuit’s manufacturing process, the driver’s operating technique, and other factors, the wireless power transfer (WPT) efficiency features strong uncertainty. The article chooses the coil group’s spatial parameters as well as the compensation circuit’s parameters as input variables, and then builds the deep learning network as the framework of uncertainty quantification, so as to obtain the relevant statistical characteristic parameters of WPT efficiency, through comparing with the calculation results of classical Monte Carlo (MC), it can be verified that the uncertainty quantification based on deep learning has almost the same solution accuracy and higher computational efficiency. At the same time, the article adopts tent chaotic mapping and adaptive inertia weight strategy to improve the traditional Aquila Optimization (AO) algorithm, then uses the improved multiobjective AO algorithm to accomplish the optimization of the WPT system’s structure. Through the comparison of improved AO and other optimization algorithms, it can be concluded that the improved AO can search out the optimal design parameter group with faster speed and higher accuracy, which provides effective guidance for the actual optimized design of the EVs WPT system. 

Design of Electric Vehicle’s Wireless Power Transfer System Based on Deep Learning Combined With Multi-Objective Optimization

With the progress of science and technology and the rapid development of Industry 4.0, the number of transmission lines (TLs) in various electrical and electronic equipment or large-scale systems has increased significantly, and crosstalk between TLs has become a problem that cannot be ignored that affects the normal operation of Industrial Cyber-Physical Systems (ICPS). Considering that the uncertainty of TL manufacturing and practical application will propagate to crosstalk, and it is difficult to obtain uncertain distribution types in practical engineering applications, this article adopts a data-driven method based on the polynomial chaos expansion (PCE) to establish a PCE metamodel that conforms to any distribution. The coefficients of the PCE terms are calculated by orthogonal matching pursuit based on the compressive sensing, and the extension of probability driven to arbitrary distribution is in line with the category of artificial intelligence and more in line with practical engineering applications. Combined with the Sobol, the influence of each input variable on the multiconductor TL (MTLs) crosstalk is quantified so as to provide reasonable suggestions for the rectification and optimization of the MTLs crosstalk in the future. 

Uncertainty Quantification of Crosstalk for MTLs in the Context of Industry 4.0 Based on Data-Driven Polynomial Chaos Expansion

Accurate Modeling Approach and Uncertainty Quantification for TEM Weak-Coupling Coil: A Case Study on Bucking Coil

In this paper, in view of the uncertainty of geometric parameters of braided-shielded cable and structural parameters of the shield in practical problems, polynomial chaos expansions (PCE) is used to explore the uncertainty quantification of a crosstalk calculation model of braided-shielded cable. First, the model based on multi-conductor transmission line theory is expanded by PCE. Second, the truncation degrees of polynomials and sample size of PCE are determined by the leave-one-out method, and the statistical characteristic parameters of crosstalk are obtained by combining coefficients of polynomials. Compared with the calculation results of the Monte Carlo method, the mean value, standard deviation and probability density function obtained by the two methods are basically consistent, but the PCE method has obvious advantages in calculation efficiency. Finally, the influence of input variable parameters in the crosstalk calculation model of braided-shielded cable are calculated by combining the PCE and the Sobol’s global sensitivity analysis method, which provides theoretical guidance for the electromagnetic compatibility design of electrical and electronic equipment using braided-shielded cable.

/pdf/uncertainty-quantification-method-of-crosstalk-involving-3arbh1p4.pdf

Uncertainty Quantification Method of Crosstalk Involving Braided-Shielded Cable

In view of the electromagnetic interference (EMI) of the signal shielded cable in the rail weighbridge, the interference source is analyzed on the basis of the field measurement and investigation, and methods of suppressing the crosstalk voltage of the shielded cable are proposed. First, the capacitive coupling model between the power line and the shielded cable is established, and the coupling model between the shielded layer and the core is developed. Later, the distribution parameters of the multi-conductor transmission line system are extracted by the commercial software ANSYS based on the finite element method. Then the coupling voltages of the shielded layer and the core can be calculated; compared with the measured results, the accuracy and effectiveness of the proposed method are verified. Finally, the EMI suppression methods are proposed and its effectiveness is verified. The EMI of the shielded cable is very common in engineering, and this method has a good reference value for solving the similar problems.

Study on the Electromagnetic Interference of Shielded Cable in Rail Weighbridge

The degree adaptive stochastic response surface method is applied to analyze statistically the crosstalk in multiconductor transmission lines (MTLs). The coefficient of polynomial chaos expansion (PCE) is obtained based on the least angle regression. The truncation degree of PCE is iterated using the degree adaptive truncation algorithm, and the optimal proxy model of the crosstalk of the original MTLs that satisfies the actual error requirements is calculated. The statistical properties of crosstalk in MTLs (such as mean, standard deviation, skewness, kurtosis, and probability density distribution) are obtained. The failure probability of the electromagnetic compatibility in the MTLs system is considered. The global sensitivity indices of crosstalkrelated factors are analyzed. Finally, the proposed method is proved to be effective compared with the conventional Monte Carlo method. The uncertainty quantification of crosstalk in MTLs can be calculated efficiently and accurately.

Uncertainty Quantification of the Crosstalk in Multiconductor Transmission Lines via Degree Adaptive Stochastic Response Surface Method

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Uncertainty Quantification of the Crosstalk in Multiconductor Transmission Lines via Degree Adaptive Stochastic Response Surface Method