Thermal analysis and temperature control strategy for FOG-Based SINS

The temperature-induced drift or scale factor error poses a great challenge for Fiber Optic Gyro(FOG)-Based Strap-down Inertial Navigation System (SINS). The accuracy of FOG is restrained because of the drift and scale factor varying with ambient temperature. Multi-levels temperature controllers or full-scale temperature compensation methods have been widely applied to correct the temperature-induced drift or scale errors. These temperature control strategies are developed with hypothesis of lumped parameter system (LPS). However, a single node is inadequate for resolving spatial inhomogeneity. Thus, the conventional temperature control strategies are insufficient to solve temperature-induced drift problems caused by its occupied spatially different temperature value or gradient related to heat transfer. In order to effectively control temperature environment of FOG-Based SINS with reduced energy consumption, a new thermal control method with reduced-order modeling (ROM) is proposed based on the distributed temperature parameter system (DTPS) obtained by computational fluid dynamic (CFD) simulations. Furthermore, the temperature adaptability under poor ambient environment as well as the location of actuators (heated or cooled)/sensors (temperature measurement) are analyzed in this paper. Our contribution consists of three parts. Firstly, airflows and thermal environment inside SINS, such as transient fluid flow and heat transfer between fluid-solid, are analyzed. The Boussinesq equations are used to model highly nonlinear and coupled physics of airflows and thermal energy inside SINS, especially around FOG. The Boussinesq equations along with corresponding boundary conditions are solved by using a commercial ANSYS solver based on the Finite Volume Method (FVM). Secondly, a low-dimensional model is developed to approximate the full high-dimensional Boussinesq equations by Proper Orthogonal Decomposition (POD)-Galerkin methodology. Thirdly, Linear Quadratic Regulator (LQR) addresses the low-dimensional model control to guarantee the constant and assigned temperature for the space around FOG. Through CFD simulation, it is demonstrated that optimal actuators/sensors spatial distribution and LQR control system based on reduced-order model are capable of control thermal environment inside SINS with reduced energy consumption to a large extent, which assures better temperature performance of FOG-Based SINS.