A Comparative Analysis of Wireless Power Transfer Technologies Using Grey Relational Analysis

This study evaluates five prominent Wireless Power Transfer (WPT) technologies Inductive Coupling, Resonant Inductive Coupling, Radio Frequency (RF) Transfer, Magnetic Resonance Coupling, and Laser Power Transfer based on multiple performance criteria using the Grey Relational Analysis (GRA) method. The technologies were assessed on four key parameters: efficiency, range, safety, and cost-effectiveness. Through normalization, deviation sequence, and the calculation of Grey Relational Coefficients (GRC), we established a Grey Relational Grade (GRG) for each technology, ranking them based on their overall performance. The results show that Laser Power Transfer ranks highest among the WPT methods, achieving the best balance of range, safety, and cost-effectiveness, with a GRG of 0.8571. This technology is optimal for applications requiring long-range power transfer, although it has moderate efficiency. Inductive Coupling, with the second-highest GRG (0.5238), excels in efficiency but is limited by its short range, making it ideal for close-contact applications, such as charging pads. RF Transfer ranks third, offering a moderate balance of range and cost-effectiveness, suited for remote, low-power applications where efficiency is less critical. Magnetic Resonance and Resonant Inductive Coupling rank fourth and fifth, respectively, showing moderate performance across all criteria without excelling in any specific aspect. The use of GRA enables a structured and quantitative assessment of each technology’s suitability for various applications, highlighting their strengths and limitations relative to an ideal performance profile. This research provides valuable insights for selecting WPT technologies based on specific operational requirements, supporting decision-making in fields such as consumer electronics, medical devices, and industrial automation. Future work may involve exploring other criteria, such as environmental impact and scalability, to further refine the selection process.