環境における稲のモミラクトンA、モミラクトンB, 及びファイトケミカルの環境相互作用活性並びに生物的活性に関する研究

広島大学(Hiroshima University)博士(農学)Doctor of Agriculturedoctora

Optimal control and real-time simulation of hybrid marine power plants

With significantly increasing concerns about greenhouse effects and sustainable economy, the marine industry presents great potential for reducing its environmental impact. Recent developments in power electronics and hybridisation technologies create new opportunities for innovative marine power plants which utilize both traditional diesel generators and energy storage like batteries and/or supercapacitors as the power sources. However, power management of such complex systems in order to achieve the best efficiency becomes one of the major challenges. Acknowledging this importance, this research aims to develop an optimal control strategy (OCS) for hybrid marine power plants. First, architecture of the researched marine power plant is briefly discussed and a simple plant model is presented. The generator can be used to charge the batteries when the ship works with low power demands. Conversely, this battery energy can be used as an additional power source to drive the propulsion or assist the generators when necessary. In addition, energy losses through braking can be recuperated and stored in the battery for later use. Second, the OCS is developed based on equivalent fuel consumption minimisation (EFCM) approach to manage efficiently the power flow between the power sources. This helps the generators to work at the optimal operating conditions, conserving fuel and lowering emissions. In principle, the EFCM is based on the simple concept that discharging the battery at present is equivalent to a fuel burn in the future and vice-versa and, is suitable for real-time implementation. However, instantaneously regulating the power sources’ demands could affect the system stability as well as the lifetime of the components. To overcome this drawback and to achieve smooth energy management, the OCS is designed with a number of penalty factors by considering carefully the system states, such as generators’ fuel consumption and dynamics (stop/start and cranking behaviour), battery state of charge and power demands. Moreover, adaptive energy conversion factors are designed using artificial intelligence and integrated in the OCS design to improve the management performance. The system therefore is capable of operating in the highest fuel economy zone and without sacrificing the overall performance. Furthermore, a real-time simulation platform has been developed for the future investigation of the control logic. The effectiveness of the proposed OCS is then verified through numerical simulations with a number of test cases

QUANTUM TELEPORTATION OF ENTANGLED STATES VIA GENERALIZED PHOTON-ADDED PAIR COHERENT STATE

In this paper, we study the quantum teleportation of an unknown atomic state based on the two-photon Jaynes-Cummings model, consisting of an effective two-level atom with a two-mode field in the generalized photon-added pair coherent state (GPAPCS). By applying the detecting method, we use a scheme that includes two two-level atoms and a cavity field to teleport the unknown atomic state from a sender to a receiver. The results show that the number of photons added to the field and the intensity of the initial field influence the average fidelity and success probability of the teleportation process. The time-evolution dependence of the average fidelity is also considered and compared for the field in the pair coherent state and in the GPAPCS

An enhanced nodal gradient finite element for non-linear heat transfer analysis

The present work is devoted to the analysis of non-linear heat transfer problems using the recent development of consective-interpolation procedure. Approximation of temperature is enhanced by taking into account both the nodal values and their averaged nodal gradients, which results in an improved finite element model. The novel formulation possesses many desirable properties including higher accuracy and higher-order continuity, without any change of the total number of degrees of freedom. The non-linear heat transfer problems equation is linearized and iteratively solved by the Newton-Raphson scheme. To show the accuracy and efficiency of the proposed method, several numerical examples are hence considered and analyzed

Vietnam’s Security Challenges: Priorities, Policy Implications and Prospects for Regional Cooperation

The historic end of the Cold War and the rising tide of globalization have significantly changed the nature of threats and security discourses in Asia. There is a notable shift of attention from military power as the core determinant of national security to several non-traditional sectors with a much enhanced role of economic, political, and societal forces. Non-traditional security issues—such as climate change, natural disasters, transnational crimes, and terrorism—require both policymakers and military strategists to deal with security threats in a more comprehensive manner. Increasing interdependence among states also magnifies the impacts of these threats, urging Asian countries to forge regional cooperation in multilateral forums such as ASEAN, EAS, APEC, and ARF. Though these efforts are commendable, their effectiveness in tackling such a wide canvass of threats is still open to questio

A study on electric vehicle battery ageing through smart charge and vehicle-to-grid operation

Electrification of transportation means brings positive impacts to the environment because of reduced fossil fuel depletion and related carbon emissions. Critical obstacles remain in terms of battery costs and their expected life. Vehicle-to-grid technologies can deliver benefits to support electrical power grid and vehicle owner, while their practical implementation faces challenges due to the concerns over accelerated battery degradation. This study presents the evaluation of battery degradation through different smart charge strategies and vehicle-to-grid scenarios. The simulation results show that the developed smart charge schemes can mitigate the battery ageing up to 5% while lowering the charge cost from 30 - 60% as comparing to the conventional charge method within the first five days operation of the battery. In addition, the calendar ageing can be diminished upto 80% by participating in suitable V2G scenario

Baseline strategy for remaining range estimation of electric motorcycle applications

Accurate predicting the remaining range of electric motorcycles (EMs) is important to help optimizing the energy consumption and improving the utilization of remaining energy in the batteries and therefore extending their life. In this paper, a range estimation strategy is developed to estimate the elapsed travel distance of the motorbike application and hence, the remaining range can be predicted. Then, daily riding cycles of the EM are identified and classified through machine learning technique based on the training and testing dataset of various standard ride cycles, which are combined with the proposed range estimation strategy to estimate the remaining travel distance of the motorcycle as the baseline to underpin and support the energy management system of the electric vehicle applications. The developed complete model is finally evaluated on a mixed daily riding cycles showing the effectiveness of the approach

An advanced hardware-in-the-loop battery simulation platform for the experimental testing of battery management system

Extensive testing of a battery management system (BMS) on real battery storage system (BSS) requires lots of efforts in setting up and configuring the hardware as well as protecting the system from unpredictable faults during the test. To overcome this complexity, a hardware-in-the-loop (HIL) simulation tool is employed and integrated to the BMS test system. By using this tool, it allows to push the tested system up to the operational limits, where may incur potential faults or accidents, to examine all possible test cases within the simulation environment. In this paper, an advanced HIL-based virtual battery module (VBM), consists of one “live” cell connected in series with fifteen simulated cells, is introduced for the purposes of testing the BMS components. First, the complete cell model is built and validated using real world driving cycle while the HIL-based VBM is then exercised under an Urban Dynamometer Driving Schedule (UDDS) driving cycle to ensure it is fully working and ready for the BMS testing in real-time. Finally, commissioning of the whole system is performed to guarantee the stable operation of the system for the BMS evaluation

State of power prediction for lithium-ion batteries in electric vehicles via Wavelet-Markov load analysis

Electric vehicle (EV) power demands come from its acceleration/braking as well as consumptions of the components. The power delivered to meet any demand is limited to the available power of the battery. This makes the battery state of available power (SoAP) a critical variable for battery management purposes. This paper presents a novel approach for long-term SoAP prediction by supervising the working conditions for prediction of future load. Firstly, a battery equivalent circuit model (ECM) coupled with a thermal model is established to accurately capture the battery dynamics. The battery model is then connected to an EV model in order to interpret the working conditions to battery power demand. By supervising the historical usage conditions, a long-term load prediction mechanism is designed based on wavelet analysis and Markov models. This facilitates the separation of low and high frequency load demands and addresses future uncertainties. Finally, the SoAP prediction is put forward along with a sensitivity analysis with respect to battery model and load prediction mechanism parameters. It is demonstrated that compared to the existing approaches for load and SoAP prediction, the developed method is more practical and accurate. Co-simulations via MATLAB and AMESim as well as experiments on a set of commercially available Lithium-ion (Li-ion) cylindrical cells under real-world drive cycles prove the given concept and validate the performance of the method

An identification of the tolerable time-interleaved analog-to-digital converter timing mismatch level in high-speed orthogonal frequency division multiplexing systems

High-speed Terahertz communication systems has recently employed orthogonal frequency division multiplexing approach as it provides high spectral efficiency and avoids inter-symbol interference caused by dispersive channels. Such high-speed systems require extremely high-sampling time-interleaved analog-to-digital converters at the receiver. However, timing mismatch of time-interleaved analog-to-digital converters significantly causes system performance degradation. In this paper, to avoid such performance degradation induced by timing mismatch, we theoretically determine maximum tolerable mismatch levels for orthogonal frequency division multiplexing communication systems. To obtain these levels, we first propose an analytical method to derive the bit error rate formula for quadrature and pulse amplitude modulations in Rayleigh fading channels, assuming binary reflected gray code (BRGC) mapping. Further, from the derived bit error rate (BER) expressions, we reveal a threshold of timing mismatch level for which error floors produced by the mismatch will be smaller than a given BER. Simulation results demonstrate that if we preserve mismatch level smaller than 25% of this obtained threshold, the BER performance degradation is smaller than 0.5 dB as compared to the case without timing mismatch