Abstract:

With the advance of science and technology, there has been increasing interest in robotic systems. Two of the most important requirements for monitoring such systems are sensor design technology and battery state of charge (SOC) estimation. This dissertation aims to develop an integrated monitoring system that can accurately monitor motion signals (including voltage, current, temperature, angular velocity, and SOC) in real-time and can be applied to a humanoid robot developed by our laboratory.

The dissertation discusses the development of this integrated system in two major parts. The first focuses on developing intelligent sensors, including the MEMS gyroscope, its sensing circuit, and the wireless temperature sensor. In MEMS gyroscope research, frequency matching is an important issue. The single-gimbaled decoupled gyroscope (SGDG) is presented first, and the proposed feedback frequency-matching algorithm (FFMA) is used to improve signal attenuation caused by frequency mismatch. The FFMA combined quadrature error cancellation algorithm (QEC) can also reduce quadrature error caused by imperfection in the mechanical structure. According to the simulation results, both FFMA and QEC can increase gyroscope performance. Secondly, an ultra linear and high sensitivity switched-capacitor sensing circuit, with parasitic-insensitive topology, can be realized at the same time. This circuit is very suitable for gyroscope measurement and can use signal processing to cancel the voltage offset. As for the wireless temperature sensor, in our previous design, based on the CMOS proportional-to-absolute temperature (PTAT) principle, the temperature sensor can only has the sensitivity of 2.3 mV/°C with linearity up to 95% for the temperature range from 20 °C to 120 °C. In order to improve the measurement range, linearity, and sensitivity of our previous design using the PTAT principle, a combined device based on the principle of CMOS double zero temperature coefficient (DZTC) points is first created at the chip level with two voltage references, one current reference, and one temperature sensor. The results show that the chip can achieve linearity up to 97% with a sensitivity of 9.55 mV/°C, in a wide temperature range from ?20 °C to 120 °C. The proposed temperature sensor has 4.15-times better sensitivity than the previous design. An 8-bit successive-approximation-register (SAR) ADC and a 433 MHz wireless transmitter are also integrated in this chip. In order to improve the efficiency of analog IC layout design, the automatic placement system (APS), which is expected to improve the layout design procedure for analog IC product development, is proposed to quickly provide a layout design placement.

The second part of the dissertation first proposes a method based on a genetic algorithm (GA) for optimization of the battery pack (OBP). The proposed method considers the cell balance of battery packs and thus avoids cell over-discharge and over-charge. Validation results indicate that the proposed method can greatly reduce temperature variation and power loss due to temperature effect, and can accurately estimate battery packs’ SOC and terminal voltage. Secondly, a new SOC estimation method, “Modified ECE + EKF,” is proposed, combining a modified ECE method with an EKF-based method. The modified ECE method considers self-discharge, influence of temperature, and SOC on coulombic efficiency, while the EKF-based method is used to make the approximate initial SOC value converge to its real value. The experimental results show that the proposed method is superior to several traditional techniques, giving a SOC estimation accuracy within 1% of the true value.