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[IEEE 2018 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization (NEMO) - Reykjavik, Iceland (2018.8.8-2018.8.10)] 2018 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization (NEMO) - Low-Cost Simulation-Driven Design of Broadband Rectifiers for Ambient RF Energy Harvesting
摘要： A steady growth of ambient RF energy density associated with a rapid increase of the number of broadcasting devices stimulates the research on broadband harvesting circuits. Such circuits can be used as energy sources for low-power sensors or Internet-of-Things devices. On the other hand, dedicated design techniques for rectifiers are lacking which results in poor performance of existing circuits. Also, their design cost is high because it involves hybrid electromagnetic (EM) and harmonic balance (HB) simulations. In this work, we propose a novel design procedure for low-cost design of broadband rectifiers. The core component of the approach is a novel equivalent-circuit-based low-fidelity model which does not involve harmonic balance (HB) simulations. The model consists of a matching circuit loaded with the RF-to-DC converter block represented using the S-parameter matrix. The latter is obtained from a single HB simulation of the converter circuit. Inaccuracy of the model is reduced using appropriate correction techniques. At the first stage of the design process, the proposed model is optimized for minimization of the in-band reflection. At the second stage, a hybrid HB-EM-based tuning oriented towards maximization of the structure efficiency is carried out. The proposed approach is demonstrated using a novel broadband rectifier operating within 0.5 GHz to 3.5 GHz band. Numerical cost of the method is 80% lower compared to direct EM-HB- based optimization of the rectifier circuit.
关键词： broadband rectifiers,constrained optimization,simulation-driven design,surrogate-based optimization,equivalent circuit model
更新于2025-09-23 15:21:21
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[Institution of Engineering and Technology 12th European Conference on Antennas and Propagation (EuCAP 2018) - London, UK (9-13 April 2018)] 12th European Conference on Antennas and Propagation (EuCAP 2018) - Low-Cost Multi-Objective Optimization of Antennas By Means Of Generalized Pareto Ranking Bisection Algorithm
摘要： This paper introduces a generalized Pareto ranking bisection algorithm for low-cost multi-objective design optimization of antenna structures. The algorithm allows for identifying a set of Pareto optimal sets of parameters (that represent the best trade-offs between considered objectives) by iterative partitioning of the intervals connecting previously found designs and executing a Pareto-ranking-based poll search. The initial approximation of the Pareto front found using the bisection procedure is subsequently refined to the level of the high-fidelity EM model of the antenna at hand using local optimization. A serious limitation of the original bisection algorithm was that only two objectives could be considered. The generalized version proposed here allows for handling any number of design goals. An improved poll search procedure has also been developed and incorporated. Our algorithm has been demonstrated using an example of a UWB monopole antenna with three figures of interest taken into account: structure size, reflection response, and gain variability.
关键词： Antenna design,simulation-driven design,variable-fidelity simulations,generalized bisection algorithm,multi-objective optimization,Pareto ranking
更新于2025-09-04 15:30:14