RESUMO
In weak-coupling wireless power transmission, increasing operating frequency, and incorporating metamaterials, resonance structures or ferrite cores have been explored as effective solutions to enhance power efficiency. However, these solutions present significant challenges that need to be addressed. The increased operating frequency boosts ferrite core losses when it exceeds the working frequency range of the material. Existing metamaterial-based solutions present challenges in terms of requiring additional space for slab installation, resulting in increased overall size. In addition, limitations are faced in using Snell's law for explaining the effects of metamaterial-based solutions outside the transmission path, where the magnetic field can not be reflected or refracted. To address these issues, in this work, the concept of a negative equivalent magnetic reluctance structure is proposed and the metamaterial theory is extended with the proposed magnetic reluctance modelling method. Especially, the negative equivalent magnetic reluctance structure is effectively employed in the weak-coupling wireless power transfer system. The proposed negative equivalent magnetic reluctance structure is verified by the stacked negative equivalent magnetic reluctance structure-based transformer experiments and two-coil mutual inductance experiments. Besides, the transmission gain, power experiments and loss analysis experiments verify the effectiveness of the proposed structure in the weak-coupling wireless power transfer system.
RESUMO
Foreign object detection (FOD) is crucial to preventing wireless electric vehicle charging (WEVC) systems from thermal risk caused by intruded metals in the charging area. In practice, the spatial misalignment between EV and ground-assembled power transmitter is evitable. Unfortunately, according to our quantitative analysis based on conventional voltage-difference-based method, a misalignment of merely tens of mm has been enough to severely deteriorate the FOD accuracy. To combat this misalignment effect, a FOD strategy based on passive sensing coils utilizing voltage vector decomposition (VVD) is proposed in this paper. The proposed strategy can be invariant to misalignment in an automatic manner, during the whole charging process, and regardless of the resonance state of charging circuit. To facilitate VVD implementation, a method called inductance-misalignment mapping (IMM) is devised to obtain the spatial misalignment of EV in real time, and it can be executed by reusing the sensing coils without introducing extra cost. The effectiveness of optimized sensing coils with the proposed FOD method is validated successfully using a commercialized 3-kW prototype working from light load to rated load.
RESUMO
The efficacy of deep brain stimulation (DBS) for Parkinson's disease (PD) depends in part on the post-operative programming of stimulation parameters. Closed-loop stimulation is one method to realize the frequent adjustment of stimulation parameters. This paper introduced the nonlinear predictive control method into the online adjustment of DBS amplitude and frequency. This approach was tested in a computational model of basal ganglia-thalamic network. The autoregressive Volterra model was used to identify the process model based on physiological data. Simulation results illustrated the efficiency of closed-loop stimulation methods (amplitude adjustment and frequency adjustment) in improving the relay reliability of thalamic neurons compared with the PD state. Besides, compared with the 130Hz constant DBS the closed-loop stimulation methods can significantly reduce the energy consumption. Through the analysis of inter-spike-intervals (ISIs) distribution of basal ganglia neurons, the evoked network activity by the closed-loop frequency adjustment stimulation was closer to the normal state.
