Multi-directional plasmonic splitter and polarization analyzer based on the catenary metasurface

Owing to the unique properties of strongly confined and enhanced electric fields, surface plasmon polaritons (SPPs) provide a new platform for the realization of ultracompact plasmonic circuits. However, there are challenges in coupling light into SPPs efficiently and subsequently routing SPPs. Here, we propose a multi-directional SPPs splitter and polarization analyzer based on the catenary metasurface. Based on the abundant electromagnetic modes and geometric phase modulation principle of catenary structure, the device has realized high efficiency beam splitting for four different polarization states ( x -polarization, y -polarization, LCP and RCP). The central wavelength of the device is 632 nm and the operation bandwidth can reach 70 nm (585-655 nm). Based on the phenomenon of SPPs beam splitting, we present a prototype of a polarization analyzer, which can detect the polarization state of incident light by adding photodetector with light intensity logic threshold in four directions. Moreover, by combining this device with dynamic polarization modulation techniques, it is possible to be served as a router or switch in integrated photonic circuits.

Optimized switch-level soft error detection based on advanced switch-level models

Due to the reduction of transistor size, modern circuits are becoming more sensitive to soft errors. The development of new techniques and algorithms targeting soft error detection are important as they allow designers to evaluate the weaknesses of the circuits at an early stage of the design. The project presents an optimized implementation of soft error detection simulator targeting combinational circuits. The developed simulator uses advanced switch level models allowing the injection of soft errors caused by single event-transient pulses with magnitudes lesser than the logic threshold. The ISCAS'85 benchmark circuits are used for the simulations. The transients can be injected at drain, gate, or inputs of logic gate. This gives clear indication of the importance of transient injection location on the fault coverage. Furthermore, an algorithm is designed and implemented in this work to increase the performance of the simulator. This optimized version of the simulator achieved an average speed-up of 310 compared to the non-algorithm based version of the simulator.

Optimized switch-level soft error detection based on advanced switch-level models

Due to the reduction of transistor size, modern circuits are becoming more sensitive to soft errors. The development of new techniques and algorithms targeting soft error detection are important as they allow designers to evaluate the weaknesses of the circuits at an early stage of the design. The project presents an optimized implementation of soft error detection simulator targeting combinational circuits. The developed simulator uses advanced switch level models allowing the injection of soft errors caused by single event-transient pulses with magnitudes lesser than the logic threshold. The ISCAS'85 benchmark circuits are used for the simulations. The transients can be injected at drain, gate, or inputs of logic gate. This gives clear indication of the importance of transient injection location on the fault coverage. Furthermore, an algorithm is designed and implemented in this work to increase the performance of the simulator. This optimized version of the simulator achieved an average speed-up of 310 compared to the non-algorithm based version of the simulator.

Fuzzy control of dual storage system of an electric drive vehicle considering battery degradation

In this manuscript, fuzzy logic energy management strategy for dual storage system inclu\-ding supercapacitors and battery is proposed in order to prolong battery lifespan and enhance the range of electric drive vehicle (EDV). First an EDV model and three drive cycles (NEDC, UDDS, and NREL) are established in Matlab/Simulink. Then a fuzzy inference system is designed considering three inputs: power demand, state of charge (SOC) of battery and SOC of supercapacitors. An output, which refers to split ratio between supercapacitors and battery power, is determined. Fuzzy rules are constituted in order to decrease not only high level battery current but also number of charge/discharge cycle of battery which are the main factors of battery deterioration. For a performance verification of the proposed method, three drive cycles with different characteristics are considered. Obtained results are compared to two other strategies; one of them is battery only system and the other one is dual storage system managed by logic threshold method. It is shown that the proposed method delivers better and robust performance to prolong battery lifespan.

Parameter optimization of rule-based control strategy for multi-mode hybrid electric vehicle

Multi-mode hybrid electric vehicle is considered as the best hybrid power solution because it has many operational modes and can achieve a wider and more efficient transmission range. But at the same time, it also brings some problems, such as the choice of operational mode. At present, the most commonly used mode-switching strategy is rule-based control strategy, but it needs to determine the logical threshold value of each control variable in advance. Usually these values are determined by experience, but cannot guarantee that the value obtained is the optimal solution. This paper combines the improved NSGA_II algorithm with the rule-based control strategy and optimizes the logic threshold value by using the improved NSGA_II algorithm to get the optimal logic threshold value. Combining the optimized rule-based control strategy with the minimum equivalent fuel consumption strategy, a real-time control strategy for multi-mode hybrid electric vehicle is proposed. The advantages of the proposed control strategy are proved by an example.

Two-layer mass-adaptive hill start assist control method for commercial vehicles

This study aims to develop a two-layer mass-adaptive control framework to improve the hill start assist performance of commercial vehicles equipped with an electronic parking brake system. In the first layer, the desired pressure of the hill start assist control is proposed, then a logic threshold control method is employed to track the time-varying desired pressure. Due to the frequently changing load of the commercial vehicles, the second layer is utilized to estimate the vehicle mass online. The proposed mass-adaptive control method is evaluated via a co-simulation platform involving MATLAB/Simulink, TruckSim and AMESim, and is compared with a one-layer scheme without mass estimation. Finally, we further demonstrate the feasibility and robustness of the two-layer mass-adaptive hill start assist framework in vehicle experiments.