RESUMEN
Predicting the system efficiency of green energy and developing forward-looking power technologies are key points to accelerating the global energy transition. This research focuses on optimizing the parameters of proton exchange membrane fuel cells (PEMFCs) and photovoltaic (PV) cells using the honey badger algorithm (HBA), a swarm intelligence algorithm, to accurately present the performance characteristics and efficiency of the systems. Although the HBA has a fast search speed, it was found that the algorithm's search stability is relatively low. Therefore, this study also enhances the HBA's global search capability through the rapid iterative characteristics of spiral search. This method will effectively expand the algorithm's functional search range in a multidimensional and complex solution space. Additionally, the introduction of a sigmoid function will smoothen the algorithm's exploration and exploitation mechanisms. To test the robustness of the proposed methodology, an extensive test was conducted using the CEC'17 benchmark functions set and real-life applications of PEMFC and PV cells. The results of the aforementioned test proved that with regard to the optimization of PEMFC and PV cell parameters, the improved HBA is significantly advantageous to the original in terms of both solving capability and speed. The results of this research study not only make definite progress in the field of bio-inspired computing but, more importantly, provide a rapid and accurate method for predicting the maximum power point for fuel cells and photovoltaic cells, offering a more efficient and intelligent solution for green energy.
RESUMEN
A Wiegand sensor is composed of a strip of Wiegand wire and a pick-up coil. The research presented in this paper examines and characterizes the fast magnetization reversal in a Wiegand wire, which leads to changes in magnetic flux density in its pick-up coil to produce the so-called Wiegand pulse to be used as a reference mark in a linear positioning system. It was observed in this research that the magnitude and duration of the pulse voltage were independent of driving frequency, indicating that Wiegand effect sensors could be ideal for use as zero-speed transducers. The repeatability of the Wiegand pulse was found to vary with different magnetic flux intensities of external magnetic field, as well as the angle between the magnetic induction line and the Wiegand wire. Through calibrated experimental and numerical parametric studies, the mechanism for producing repeatable Wiegand pulses to be used as a reference mark for precision liner positioning systems was revealed, which represents the novelty of this research. On the basis of this mechanism, the optimal design combination of the Wiegand sensor's position with respect to the magnetization source can be obtained. Utilizing commercially available Wiegand sensors, it was demonstrated in this research that with a Wiegand pulse serving as a magnetic reference mark, positioning repeatability of 0.3 um could be achieved, which is on the same order as optical scales. The work presented in this research has engineering implications as well as offering scientific insights into magnetization mechanisms for generating enough magnetic remanence to produce a Barkhausen jump, resulting in repeatable Wiegand for use as a reference mark in a linear positioning system.
RESUMEN
Study design: Case series. Background: Robot-assisted rehabilitation mediated by exoskeletal devices is a popular topic of research. The biggest difficulty in the development of rehabilitation robots is the consideration of the clinical needs. This study investigated the usability of a novel cable-driven exoskeletal robot specifically designed for hand rehabilitation. Methods: The study consists of three steps, including prototype development, spasticity observation, and usability evaluation. First, we developed the prototype robot DexoHand to manipulate the patient's fingers based on the clinical needs and the cable-driven concept established in our previous work. Second, we applied DexoHand to patients with different levels of spasticity. Finally, we obtained the system usability scale (SUS) and assessed its usability. Results: Two healthy subjects were recruited in the pre-test, and 18 patients with stroke and four healthy subjects were recruited in the formal test for usability. The total SUS score obtained from the patients and healthy subjects was 94.77 ± 2.98 (n = 22), indicating an excellent level of usability. The satisfaction score was 4.74 ± 0.29 (n = 22), revealing high satisfaction with DexoHand. The tension profile measured by the cables showed the instantaneous force used to manipulate fingers among different muscle tone groups. Conclusions: DexoHand meets the clinical needs with excellent usability, satisfaction, and reliable tension force monitoring, yielding a feasible platform for robot-assisted hand rehabilitation.