Enhancing Alignment Accuracy in Laser Wireless Power Transmission Systems Using Integrated Target Detection and Perturbation-Observation Method

This paper introduces a high-precision alignment method for laser wireless power transmission (LWPT) systems, integrating neural network-based target detection with a perturbation-observation technique. The objective is to enhance the alignment accuracy between the laser spot and the photovoltaic array, thereby improving energy transfer efficiency. The method’s key feature is its ability to achieve these results without requiring additional optical components, simplifying system design. Continual assessment and adjustment based on real-time output power data ensure optimal alignment, maximizing the photovoltaic array power output. Experimental results demonstrated that the proposed method achieved an initial alignment precision with pixel errors below 3%, translating to a physical error of approximately 7 mm. Fine-tuning through the perturbation-observation method further optimized the alignment, resulting in a photovoltaic array power output of 98.70% of its maximum potential. This hybrid approach provides a reliable solution for boosting the performance of LWPT systems, offering significant potential for practical applications.

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Publication Details

Journal
Photonics
Published
2024-11-20
DOI
https://doi.org/10.3390/photonics11111094
Citations
4
Primary Topic
Energy Harvesting in Wireless Networks
Type
article
Field-Weighted Citation Impact
0.83
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article

Enhancing Alignment Accuracy in Laser Wireless Power Transmission Systems Using Integrated Target Detection and Perturbation-Observation Method

Yunfeng Bai, Liangrong Sun, Jinsong Kang, Yanping Zhou
4 citations
Photonics
Energy Harvesting in Wireless Networks
0.83
article

Enhancing Alignment Accuracy in Laser Wireless Power Transmission Systems Using Integrated Target Detection and Perturbation-Observation Method

Yunfeng Bai, Liangrong Sun, Jinsong Kang, Yanping Zhou
article en
4 citations

Abstract

This paper introduces a high-precision alignment method for laser wireless power transmission (LWPT) systems, integrating neural network-based target detection with a perturbation-observation technique. The objective is to enhance the alignment accuracy between the laser spot and the photovoltaic array, thereby improving energy transfer efficiency. The method’s key feature is its ability to achieve these results without requiring additional optical components, simplifying system design. Continual assessment and adjustment based on real-time output power data ensure optimal alignment, maximizing the photovoltaic array power output. Experimental results demonstrated that the proposed method achieved an initial alignment precision with pixel errors below 3%, translating to a physical error of approximately 7 mm. Fine-tuning through the perturbation-observation method further optimized the alignment, resulting in a photovoltaic array power output of 98.70% of its maximum potential. This hybrid approach provides a reliable solution for boosting the performance of LWPT systems, offering significant potential for practical applications.

PhotonicsVol. 11(11)
Tongji University (CN), Shanghai Aerospace Automobile Electromechanical (China) (CN)
Affordable and clean energy
Openalex Percentile: Top 26%
Energy Harvesting in Wireless Networks
0.83
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