Temperature estimation of induction machines based on wireless sensor networks

Abstract

Abstract. In this paper, a fourth-order Kalman filter (KF) algorithm is implemented in the wireless sensor node to estimate the temperatures of the stator winding, the rotor cage and the stator core in the induction machine. Three separate wireless sensor nodes are used as the data acquisition systems for different input signals. Six Hall sensors are used to acquire the three-phase stator currents and voltages of the induction machine. All of them are processed to root mean square (rms) in ampere and volt. A rotary encoder is mounted for the rotor speed and Pt-1000 is used for the temperature of the coolant air. The processed signals in the physical unit are transmitted wirelessly to the host wireless sensor node, where the KF is implemented with fixed-point arithmetic in Contiki OS. Time-division multiple access (TDMA) is used to make the wireless transmission more stable. Compared to the floating-point implementation, the fixed-point implementation has the same estimation accuracy at only about one-fifth of the computation time. The temperature estimation system can work under any work condition as long as there are currents through the machine. It can also be rebooted for estimation even when wireless transmission has collapsed or packages are missing.