This paper proposes a practical non-linear energy harvesting (EH) model and a corresponding resource allocation algorithm for simultaneous wireless information and power transfer (SWIPT) systems. The non-linear EH model accounts for the non-linear characteristics of EH circuits, which are often overlooked in traditional linear models. The proposed model is based on a logistic function and captures the dynamics of RF energy conversion efficiency for different input power levels. The resource allocation algorithm is formulated as a non-convex optimization problem to maximize the total harvested power at energy harvesting receivers (ERs), subject to minimum required signal-to-interference-plus-noise ratios (SINRs) at information receivers (IRs). The non-convex objective function is transformed into an equivalent subtractive form, enabling the derivation of an efficient iterative resource allocation algorithm. In each iteration, a rank-constrained semidefinite program (SDP) is solved optimally via SDP relaxation. Numerical results show that the proposed non-linear EH model significantly improves the total harvested power compared to the traditional linear model. The simulation results demonstrate that the proposed algorithm outperforms the baseline scheme based on the linear model, especially when the number of ERs increases. The paper also provides a proof of the tightness of the SDP relaxation under certain channel conditions. The results highlight the importance of using a practical non-linear EH model for resource allocation in SWIPT systems to avoid mismatches caused by the non-linear nature of EH circuits.This paper proposes a practical non-linear energy harvesting (EH) model and a corresponding resource allocation algorithm for simultaneous wireless information and power transfer (SWIPT) systems. The non-linear EH model accounts for the non-linear characteristics of EH circuits, which are often overlooked in traditional linear models. The proposed model is based on a logistic function and captures the dynamics of RF energy conversion efficiency for different input power levels. The resource allocation algorithm is formulated as a non-convex optimization problem to maximize the total harvested power at energy harvesting receivers (ERs), subject to minimum required signal-to-interference-plus-noise ratios (SINRs) at information receivers (IRs). The non-convex objective function is transformed into an equivalent subtractive form, enabling the derivation of an efficient iterative resource allocation algorithm. In each iteration, a rank-constrained semidefinite program (SDP) is solved optimally via SDP relaxation. Numerical results show that the proposed non-linear EH model significantly improves the total harvested power compared to the traditional linear model. The simulation results demonstrate that the proposed algorithm outperforms the baseline scheme based on the linear model, especially when the number of ERs increases. The paper also provides a proof of the tightness of the SDP relaxation under certain channel conditions. The results highlight the importance of using a practical non-linear EH model for resource allocation in SWIPT systems to avoid mismatches caused by the non-linear nature of EH circuits.