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In order to improve the system efficiency and operational economy of hybrid energy storage (HES) tramway under cycle conditions, this paper presents an energy management method based on equivalent loss instantaneous optimization (ELIO) for lithium battery/supercapacitor hybrid energy storage system (HESS) with dual DC/DC topology. The online convex programming method is used to solve the problem, and the optimal dynamic mixing degree at each moment of the system is obtained. This proposed method properly allocates the power flow between lithium battery and supercapacitor to minimum the system equivalent loss in the unit control period. According to the equivalent loss theory, the ELIO problem is converted to the optimal output power solution of the HESS. Under various operating conditions, the multi-index performance is tested and analyzed by a HESS test platform, which consists of lithium battery, supercapacitor, bidirectional DC/DC converter and energy management system. The experimental results show that compared with the power following strategy, this proposed ELIO method can effectively improve more than system efficiency, operational economy and driving mileage, and improved the service life of HESS by smoothing battery operating pressure.

The accuracy of Global Positioning System (GPS) is often combined with the reliability of Inertial Navigation System (INS) to accomplish navigation. This paper proposes an innovative way to filter and fuse the GPS and INS information. UKF is employed to simulate the information convergence of the dynamic model which maintains better performance in nonlinear system. So we can obtain a fair precise filtering result when both are online. At the same time, the INS data is trained with the result as training target when it is the unique input. This paper raises the idea that Support Vector Machine (SVM) is adopted to train the INS data during GPS outage and the simulated annealing is applied to realize the optimization of the parameters of kernel function and the penalty function in the SVM algorithm. Therefore, the integration navigation could retain almost as precise as the GPS when the GPS is off-line.

The proposed algorithm provides fast and accurate auto-exposure capability for digital still cameras. For normal lighting conditions, the number of preview frames and the exposure error are within 3.5 frames and 3.92%. For high contrast lighting conditions, the number of preview frames and the exposure error are within 8.8 frames and 6.56%. Furthermore, it offers accurate detection for both back lit and excessive front lit conditions at the same time and make proper exposure to the main object.

A 2.4 G single-chip radio-frequency (RF) transceiver front-end for IEEE 802.11b is integrated in 0.18 mum CMOS technology. The direct conversion architecture is adopted for both transmitter & receiver to minimize the on-chip and off-chip components required, which ensures low cost and low power consumption. The VCO oscillates at two times the carrier frequency to minimize PA pulling effect, which also facilitates the generation of quadrature LOs by using a divide-by-two circuit. It is also promising that further integration of multi-mode transceiver can be facilitated because this architecture maximizes reuse of building blocks in transmitter, receiver and PLL. Primary test results show that the transmit peak error vector magnitude (peak EVM) is less than 16% (rms value about 8.6%) with the spectrum mask requirements met and show that at 4.4 GHz, PLL phase noise is about -119 dBc/Hz at 3 MHz offset.