Technology And Device Development Of Thermal Management Of Giant Magnetostrictive Material Smart Component

Giant magnetostrictive material (GMM) is one kind of smart material which elongates in magnetic field. For this characteristic, it can be made into Giant magnetostrictive material smart component, which can be widely applied in micro-driving fields such as ultra-precise machine tools, precise instruments and so on.However, when GMM smart component works, it will generate heat, such as Joule heat, which will cause a significant temperature rise of the smart component. This will results in thermal deformation and the nonlinearity of the GMM. As a result, the output performance of the smart component will be badly influenced. Therefore, thermal management must be applied to reduce or eliminate the influence from the temperature rise to the smart component so that the output accuracy of the smart component can be ensured. Unfortunately, because the smart component has a large lag coefficient, it is difficult to realize the closed-loop control of the temperature. therefore, in the previous research, only half-closed-loop temperature control systems have been achieved, which have a low temperature control accuracy.In order to solve these problems, this dissertation has carried out in-depth research on the thermal structure design of the smart component. Based on literature search, the dissertation summarized the characteristics and application of GMM, and analyzed the research status of the thermal management, thermal structure design of the driving coil, system identification and control strategies of the GMM smart component. Based on the forgoing analysis, the dissertation presents a new type of GMM smart component, which is driven by AC/DC separated coils, and a new type of water cooling temperature control system using cascade control strategy.Given the parameters of the magnetic field and thermal field, the AC/DC separated coils was designed and simulated to verify the validity of the scheme. After that, water cooling temperature control scheme was designed and the overall structure of the smart component was presented. After that, the FSI model of the smart component was built and simulated to analyze its performance of temperature control. Then the dynamical model of the smart component was built based on system identification. The control parameters were optimized by genetic algorithm so that the optimal temperature control of the smart component can be achieved. Finally, combined tests were carried out to verify the validity, precision and reliability of the smart component and temperature control system.