In this study, an electromagnetically controlled cooling device (ECCD) is proposed, employing magnetic nanofluid (MNF) and electromagnetohydrodynamics to ameliorate the waste-heat dissipation of mechatronic systems. The MNF was charged in a condenser chamber as an auxiliary coolant, and was prepared from fine ferromagnetic particles of iron ferrite by using a chemical coprecipitation technique. A radial basis function neural network-based training model was employed for examining the electromagnetic resonance of the ECCD at a wide heating range. Satisfactory agreement between the experimental and predicted results indicated the accuracy of the model in capturing the ECCD dynamics. The nonlinearity of ECCD dynamics were also identified as a feature of frequency resonance by mapping a discrete-time model into generalized frequency response functions (GFRFs). Accordingly, the effect of electromagnetic induction relating to ECCD performance can be further confirmed.
|Number of pages||13|
|Journal||International Journal of Applied Electromagnetics and Mechanics|
|State||Published - 1 Jan 2015|
- Electromagnetically controlled
- generalized frequency response functions (GFRFs)
- magnetic nanofluid (MNF)
- radial basis function neural network (RBF NN)