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The technique for simulating the process of developing thermoelectromotive force by the inhomogeneous thermocouple during the change of the temperature field along its legs is proposed in this paper. This allows determining the instantaneous error of the thermocouple during their operation without the use of working standards. There were revealed new relationships between the maximum and instantaneous errors due to drift and inhomogeneity. The sum of absolute values of these errors is constant, and this relationship holds in any temperature field.

The fixed switching frequency method in space vector pulse width modulation strategy has been widely used in the motor speed control system. The three-phase current of the motor under this control method will generate harmonics with higher amplitude at integer multiples of the switching frequency. It is the main source of electromagnetic noise generated by the motor. Therefore, in order to suppress the current harmonics of the driver output and improve the current waveform quality, first of all, the three-phase current ripple generation mechanism based on the common topology of the three-phase motor driver is deduced theoretically and the current ripple prediction model is obtained. The results of the prediction model are then used to specifically modify the switching frequency of motor driver to reduce the amount of current harmonics during motor rotation. The experimental results show that the harmonic suppression control method based on ripple prediction model is more effective than the traditional fixed switching frequency method in reducing the motor current harmonics and improving current quality. The method in this paper has been applied in an underwater propulsion system.

The positioning accuracy of Wireless Sensor Networks [1] (WSNs) determines the performance of this network. In order to improve the accuracy of mobile node ranging in Wireless Sensor Networks, this paper proposed a Trilateration algorithm based on Minimum Generalization Error. The method using signal strength data of the anchor node which was measured by the RSSI[2] (Received Signal Strength Indicator, RSSI) for modeling, and the Minimum Generalization Error to optimize the Trilateration Positioning algorithm to target node ranging. Compared with the traditional Trilateration positioning algorithm [3]–[4], this method is higher in accuracy and stronger in adaptability.