This paper presents an adaptive talkative power (TP) framework that enables simultaneous high-efficiency power transfer and reliable data communication under time-varying load conditions. A high-frequency TP-based bidirectional boost converter employing a SiC-based zero voltage switching–quasi square wave (ZVS-QSW) topology is proposed, incorporating closed-loop online efficiency optimization. Data transmission is realized through adaptive switching-frequency modulation at the transmitter, allowing information encoding while preserving optimal power transfer efficiency. To support reliable data detection under unknown and non-constant load conditions, an adaptive receiver architecture is developed that extracts information from output voltage ripple variations induced by frequency modulation. Owing to the nonlinear and complex nature of the ripple characteristics, a supervised machine-learning-based classification approach is employed for data detection, eliminating the need for prior knowledge of converter parameters and overcoming the limitations of conventional maximum-likelihood detection methods. The proposed system is validated through real-time simulations using a dSPACE MicroLabBox system in conjunction with MATLAB/Simulink R2025b. Simulation results demonstrate power transfer efficiencies approaching 98% while enabling reliable and efficient data transmission across a wide range of operating conditions, including varying conversion ratios and dynamic load variations, thereby confirming the effectiveness and robustness of the proposed TP-based power and data transmission scheme.
Mousavi et al. (Tue,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: