A Wireless Power Transfer System for Mining Locomotives Based on the Stochastic Collocation Method

This study focuses on optimizing a wireless charging system for mining electric locomotives in explosive environments, utilizing the Stochastic Collocation Method (SCM) to enhance safety and efficiency. By employing inductive and magnetic resonance coupling, the system achieves a transfer efficiency exceeding 90% across distances ranging from 50 to 200 mm. SCM effectively addresses the complexities of variable underground conditions, thereby minimizing design uncertainties and enhancing system reliability. This methodology incorporates polynomial chaos expansions to model uncertainties and optimize parameters, achieving up to a 50% reduction in simulation time while maintaining accuracy. Experimental validations corroborate the simulation results, confirming strong compliance with explosion safety standards and demonstrating high system efficiency. The findings underscore significant advancements in operational safety and energy management, establishing a scalable model for deploying advanced wireless charging technologies in hazardous industrial settings.

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Publication Details

Published
2024-11-22
DOI
https://doi.org/10.1109/sgee64306.2024.10865956
Primary Topic
Energy Harvesting in Wireless Networks
Type
article
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article

A Wireless Power Transfer System for Mining Locomotives Based on the Stochastic Collocation Method

Han Zeng, Yanjin Zhu
Energy Harvesting in Wireless Networks
article

A Wireless Power Transfer System for Mining Locomotives Based on the Stochastic Collocation Method

Han Zeng, Yanjin Zhu
article en

Abstract

This study focuses on optimizing a wireless charging system for mining electric locomotives in explosive environments, utilizing the Stochastic Collocation Method (SCM) to enhance safety and efficiency. By employing inductive and magnetic resonance coupling, the system achieves a transfer efficiency exceeding 90% across distances ranging from 50 to 200 mm. SCM effectively addresses the complexities of variable underground conditions, thereby minimizing design uncertainties and enhancing system reliability. This methodology incorporates polynomial chaos expansions to model uncertainties and optimize parameters, achieving up to a 50% reduction in simulation time while maintaining accuracy. Experimental validations corroborate the simulation results, confirming strong compliance with explosion safety standards and demonstrating high system efficiency. The findings underscore significant advancements in operational safety and energy management, establishing a scalable model for deploying advanced wireless charging technologies in hazardous industrial settings.

East China Jiaotong University (CN), CRRC (China) (CN)
Affordable and clean energy
Openalex Percentile: Top 75%
Energy Harvesting in Wireless Networks
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