Affiliations: [a] Department of Mechanical Engineering, National Chiao
Tung University, Hsinchu, Taiwan | [b] Department of Mechatronic, Energy and Aerospace
Engineering, Chung Cheng Institute of Technology, National Defense University,
Tauyuan, Taiwan
Correspondence:
[*]
Corresponding author: Ya-Wei Lee, Department of Mechatronic,
Energy and Aerospace Engineering, Chung Cheng Institute of Technology, National
Defense University No.75, Shiyuan Rd., Daxi Township, Tauyuan County 33551,
Taiwan. Tel.: +886 3 380 112 6; Fax: +886 3 380 064 7; E-mail: [email protected]
Abstract: 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.
Keywords: Electromagnetically controlled, magnetic nanofluid (MNF), radial basis function neural network (RBF NN), generalized frequency response functions (GFRFs)
