Analysis of refractometric fiber optic state-of-charge (SOC) monitoring sensor for lead acid battery

In situ monitoring of the state of charge (SOC) of lead acid battery is important to understand the residual electrical energy. Usage of battery reduces the charge content of the active electrolyte which in turn changes its refractive index. This paper reports refractometric fiber optic sensor developed for on-line monitoring of SOC. The SOC is monitored during discharging phases of the battery using the developed fiber optic sensor probe along with terminal voltage, temperature and depth of discharge using a LABVIEW based data acquisition system. The paper gives the working principle, design and construction details, results and calibration of the fiber optic sensor (FOS) probe. The in situ monitoring capability of the developed FOS is demonstrated in comparison with the contemporary off-line methods of specific gravity and terminal voltage measurements.     

The splitting of low-lying or low excited states for hydride molecules （cations） of the third period under spin-orbit coupling

This paper reports that the splitting of potential energy curves for the low-lying or low excited states for hydride molecules （cations） （MgH, AlH^＋, SiH, PH^＋, SH,ClH^＋） of the third period under Spin-Orbit Coupling has been calculated by using the Spin-Orbit Multi-Configuration Quasi-Degenerate Perturbation Theory （SO-MCQDPT） method. Then, spectroscopic constants of the split states have been derived from the Murrell-Sorbie function. The calculated dissociation energies for the spectrum branch terms have been given, respectively. The spectroscopic constants and dissociation energies for the spectrum branch terms are given for the first time in this paper.     

Generating synthetic time series from Bak-Sneppen co-evolution model mixtures

The Bak-Sneppen model of co-evolution is used to derive synthetic time series with a priori specified fractal dimension (or Hurst exponent) through a mixing of processes in various lattice dimensions. Both theoretical and numerical analyses concern the avalanches at the critical threshold and provide a model for time series reconstruction that can be tested as an alternative to the classical fractional Brownian motion (fBm) because of differences in properties. New results on critical threshold and avalanche structure are obtained up to Euclidean dimension d=6. The method involves a lattice-based structure and therefore is suitable for the application of parallel computing.     

Bose–Einstein condensates under a non-Hermitian spin–orbit coupling

We study the properties of Bose–Einstein condensates under a non-Hermitian spin–orbit coupling(SOC), induced by a dissipative two-photon Raman process. We focus on the dynamics of the condensate at short times, when the impact of decoherence induced by quantum jumps is negligible and the dynamics is coherently driven by a non-Hermitian Hamiltonian. Given the significantly modified single-particle physics by dissipative SOC, the interplay of non-Hermiticity and interaction leads to a quasi-steady-state phase diagram different from its Hermitian counterpart. In particular, we find that dissipation can induce a phase transition from the stripe phase to the plane-wave phase. We further map out the phase diagram with respect to the dissipation and interaction strengths, and finally investigate the stability of quasi-steady states through the time-dependent dissipative Gross–Pitaevskii equation. Our results are readily accessible based on standard experiments with synthetic spin–orbit couplings.     

Strong Semismoothness of the Fischer-Burmeister SDC and SOC Complementarity Functions

We show that the Fischer-Burmeister complementarity functions, associated to the semidefinite cone (SDC) and the second order cone (SOC), respectively, are strongly semismooth everywhere. Interestingly enough, the proof relys on a relationship between the singular value decomposition of a nonsymmetric matrix and the spectral decomposition of a symmetric matrix.The author’s research was partially supported by Grant R146-000-035-101 of National University of Singapore.The author’s research was partially supported by Grant R314-000-042/057-112 of National University of Singapore and a grant from the Singapore-MIT Alliance.Mathematics Subject Classification (2000): 90C33, 90C22, 65F15, 65F18     

SOIL AGGREGATE AND ITS RESPONSE TO LAND MANAGEMENT PRACTICES

This paper provides a broad review of the existing study on soil aggregate and its responses to land management practices. Soil aggregate is used for structural unit, which is a group of primary soil particles that cohere to each other more strongly than other surrounding particles. The mechanism of soil particle aggregation may be expressed by a hierarchical model, which is based upon the hypothesis that macroaggregates （〉250μm） are collections of smaller microaggregates （〈250μm） held together with organic binding agents. Primary particles form microaggregates and then macroaggregates. Carbon （C）-rich young plant residues form and stabilize macroaggregates, whereas old organic C is occluded in the microaggregates. The interaction of aggregate dynamics with soil organic carbon （SOC） is complex and embraces a range of spatial and temporal processes within macroaggregates and microaggregates. The nature and properties of aggregates are determined by the quantity and quality of coarse residues and humic compounds and by the degree of their interaction with soil particles. The mechanisms resulting in the binding of primary soil particles into stable aggregates vary with soil parent material, climate, vegetation, and land management practices. Land management practices, including tillage methods, residue management, amendments, and soil fertility management, enhance soil aggregation. However, there is still much uncertainty in the dynamics of organic matter in macroaggregation and microaggregation, and research is still needed to understand further the mechanisms of aggregate formation and its responses to human activities.     

基于野外可见近红外光谱和水分影响校正算法的土壤剖面有机碳预测

土壤是陆地碳循环的中枢,充分发挥土壤固碳潜力有助于减缓全球气候变化。土壤有机碳 (SOC) 的高度分异性同时体现在空间和垂直分布上,但是许多前期研究往往只考虑了空间分异,而忽略了垂直分异。尤其在青藏高原这种高寒山区,土壤样品采集难度较大且费用昂贵。可见近红外 (Vis-NIR) 光谱作为传统土壤实验室化学分析的辅助手段,能够较为快速和精准地估测SOC含量。但是土壤水分等环境因素会掩盖或改变SOC的Vis-NIR光谱吸收特征进而削弱模型预测精度。外部参数正交化 (EPO) 和分段直接标准化 (PDS) 算法可以有效校正水分对光谱的影响,但其在野外新鲜土柱上的表现还不得而知。本研究旨在探索不同水分影响校正算法对野外剖面土壤光谱的校正能力,对采自中国青藏高原海拔2 900～4 500 m色季拉山的共26个1 m深土柱。沿深度以5 cm×5 cm为测量单元,从各单元中心采集共计386个野外原状湿样Vis-NIR光谱,并在实验室内测得相应386个研磨干样的Vis-NIR光谱以及SOC含量。经EPO和PDS算法校正土壤水分对光谱的影响后,通过随机森林建立土壤光谱和SOC含量的定量预测模型,并使用靴襻法评估不同校正处理下预测模型的不确定。土柱整体及垂直分布的精度结果表明,经PDS法转换的农田和草地土柱湿样光谱均表现出良好的水分校正效果,而EPO法仅对农田土柱有效。水分影响校正算法在不同土壤深度上也存在显著差异,EPO和PDS对农田和草地表层样本的水分校正均效果明显。两种校正方法的效果显示出地类和土层深度的依赖性。本研究为利用Vis-NIR光谱技术在高寒山区野外快速准确估算土壤碳含量的垂直分异提供了必要参考。     

Research on estimation model of the battery state of charge in a hybrid electric vehicle based on the classification and regression tree

ABSTRACT

In order to achieve the accurate estimation of state of charge (SOC) of the battery in a hybrid electric vehicle (HEV), this paper proposed a new estimation model based on the classification and regression tree (CART) which belongs to a kind of decision tree. The basic principle and modelling process of the CART decision tree were introduced in detail in this paper, and we used the voltage, current, and temperature of the battery in an HEV to estimate the value of SOC under the driving cycle. Meanwhile, we took the energy feedback of the HEV under the regenerative braking into consideration. The simulation data and experimental data were used to test the effectiveness of the estimation model of CART, and the results indicate that the proposed estimation model has high accuracy, the relative error of simulation is within 0.035, while the relative error of experiment is less than 0.05.     

基于DE-ELM的电池SOC预测研究

针对极限学习机的随机性较大的问题,提出一种基于差分演化的极限学习机算法模型(DE-ELM).采用差分演化算法(DE)对极限学习机(ELM)随机给定的输入权值矩阵和隐含层阈值进行寻优,降低了随机性给ELM造成的影响,减少ELM网络震荡,提高了ELM预测精度.并且将DE-ELM应用在电池SOC的预测上,同时与ELM和BP神经网络的预测进行了对比,结果表明:DE-ELM在电池SOC预测上的表现优于ELM和BP神经网络,能满足电池SOC的预测精度要求.