The article presents a multiple residual power prediction system to be applied in mobile robots or automation fields. The system contains multiple power detection units to measure multiple online power values. Each po...
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The article presents a multiple residual power prediction system to be applied in mobile robots or automation fields. The system contains multiple power detection units to measure multiple online power values. Each power detection unit uses four current sensors to measure the current variety, and uses weighted average method and redundant management method to calculate the exact current value, and isolates faulty measurement values. We use the proposed algorithms to be applied in voltage detection of each power detection unit. Then we can calculate the real-time power values according to the current and voltage measurement values. The control core of the power detection unit is HOLTEK microchip, and communicates with the data integration unit via wire I2C interface. The power detection units transmit the measurement values of current and voltage to the controller of the system. The main controller of the power detection system is PC-based system, and communicates with the data integration unit via wire RS232 interface. The main controller of the system can controls each power output ratio of the power sources, and predicts the power loading and the residual power for each power detection unit using auto-regression algorithm, and computes the residual time of mobile robots to work in the free space, and arrange the residual power of the enough power source to the weakness power sources using sequential single-item auction algorithm. In experiment result, the residual power prediction system can adjusts the power sources to increase the working time.
The article presents a power detection and prediction system (PDPS) using fusion algorithms to be applied in the on-line power monitoring of the target device. The system contains multiple power detection units, a dat...
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ISBN:
(纸本)9783037856512
The article presents a power detection and prediction system (PDPS) using fusion algorithms to be applied in the on-line power monitoring of the target device. The system contains multiple power detection units, a data integration unit, a target device, a power source and a main controller. Each power detection unit measures the assigned power source on real-time, and uses four current sensors to measure the current variety. We use fusion algorithms to be applied in current and voltage detection. We can calculate the real-time power values according to the estimated values of current and voltage measurement values. The main controller predicts the power loading for each power detection unit using auto-regression algorithm, and calculates the error value between the prediction value and the measurement value for each detection value, and compares the relation value on various condition.
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