Structural variation is an important and abundant source of genetic and phenotypic variation. Here we describe the first systematic and genome-wide analysis of segmental duplications and associated copy number variants (CNVs) in the modern domesticated dog,Canis familiaris, which exhibits considerable morphological, physiological, and behavioral variation. Through computational analyses of the publicly available canine reference sequence, we estimate that segmental duplications comprise ∼4.21% of the canine genome. Segmental duplications overlap 841 genes and are significantly enriched for specific biological functions such as immunity and defense and KRAB box transcription factors. We designed high-density tiling arrays spanning all predicted segmental duplications and performed aCGH in a panel of 17 breeds and a gray wolf. In total, we identified 3583 CNVs, ∼68% of which were found in two or more samples that map to 678 unique regions. CNVs span 429 genes that are involved in a wide variety of biological processes such as olfaction, immunity, and gene regulation. Our results provide insight into mechanisms of canine genome evolution and generate a valuable resource for future evolutionary and phenotypic studies.

In the battery management system, it is important to accurately and efficiently estimate the state of charge (SOC) of lithium-ion batteries, which generally requires the establishment of a equivalent circuit model of the battery, whose accuracy and rationality play an important role in accurately estimating the state of lithium-ion batteries. The traditional single order equivalent circuit models do not take into account the changes of impedance spectrum under the action of multiple factors, nor do they take into account the balance of practicality and complexity of the model, resulting the low accuracy and poor practicability. In this paper, the theory of electrochemical impedance spectroscopy is used to guide and improve the equivalent circuit model. Based on the analysis of the variation of the high and intermediate frequency range of the impedance spectrum with the state of charge and temperature of the battery, a variable order equivalent model (VOEM) is proposed by Arrhenius equation and Bayesian information criterion (BIC), and the state equation and observation equation of VOEM are improved by autoregressive (AR) equations. Combined with the unscented Kalman filter (UKF), a SOC online estimation method is proposed, named VOEM-AR-UKF. The experimental results show that the proposed method has high accuracy and good adaptability.

To realize accurate estimation of SOC (state of charge) and SOH (state of health), Li-ion battery’s operating characteristic is analyzed in this paper while fully considering temperature, degree of aging and other practical factors that could impact their operating status. On the basis of nonlinear autoregressive with exogenous inputs (NARX) architecture, an improved dynamic recurrent neural network (DRNN) with ability of dynamic mapping is established, which is more suitable than static network for estimating the batteries’ state with strongly nonlinear and dynamic behaviors. Meanwhile, a self-adaptive weight particle swarm optimization (SWPSO) algorithm is introduced for training the network. Compared with gradient descent algorithm, the SWPSO algorithm could improve error convergence speed and avoid falling into local optimum. Validation results highlights that the presented method is able to improve the estimation accuracy of the SOC and SOH under different conditions including temperature, current and degree of aging, and has strong robustness and ability of generalization.

In this paper, a novel nonisolated bidirectional dc-dc converter (BDC) consisting of a quadratic voltage cell, a switched-capacitor(SC) cell and a zero current ripple cell has been proposed for hybrid energy storage system (HESS) in electric vehicles. The converter presented combines the advantages of high voltage gain, wide voltage gain range, a low voltage stress across power switches, zero current ripple and common ground between both sides. Besides, synchronous rectification technology is applied to achieve higher efficiency of the converter. A comprehensive analysis of the operation principle, the characteristics analysis and efficiency analysis of the converter in a continuous conduction mode are presented in detail. This paper also develop a 1 kW scaled-down prototype, which validates the effectiveness and feasibility of the proposed BDC. The maximum efficiency of the converter under full load is 95.09% in the step-up mode and 95.24% in the step-down mode.