A data-driven approach with uncertainty quantification for predicting future capacities and remaining useful life of lithium-ion battery

Predicting future capacities and remaining useful life (RUL) with uncertainty quantification is a key but challenging issue in the applications of battery health diagnosis and management. This paper applies advanced machine-learning techniques to achieve effective future capacities and RUL prediction for lithium-ion batteries with reliable uncertainty management. To be specific, after using the empirical mode decomposition (EMD) method, the original battery capacity data is decomposed into some intrinsic mode functions (IMFs) and a residual. Then the long short term memory (LSTM) sub-model is applied to estimate the residual while the gaussian process regression (GPR) sub-model is utilized to fit the IMFs with the uncertainty level. Consequently, both the long-term dependence of capacity and uncertainty quantification caused by the capacity regenerations can be captured directly and simultaneously. Experimental aging data from different batteries are deployed to evaluate the performance of proposed LSTM+GPR model in comparison with the solo GPR, solo LSTM, GPR+EMD and LSTM+EMD models. Illustrative results demonstrate the combined LSTM+GPR model outperforms other counterparts and is capable of achieving accurate results for both 1-step and multi-step ahead capacity predictions. Even predicting the RUL at the early battery cycle stage, the proposed data-driven approach still presents good adaptability and reliable uncertainty quantification for battery health diagnosis

Comparative transcriptome sequencing of germline and somatic tissues of the Ascaris suum gonad

<p>Abstract</p> <p>Background</p> <p><it>Ascaris suum </it>(large roundworm of pigs) is a parasitic nematode that causes substantial losses to the meat industry. This nematode is suitable for biochemical studies because, unlike <it>C. elegans</it>, homogeneous tissue samples can be obtained by dissection. It has large sperm, produced in great numbers that permit biochemical studies of sperm motility. Widespread study of <it>A. suum </it>would be facilitated by more comprehensive genome resources and, to this end, we have produced a gonad transcriptome of <it>A. suum</it>.</p> <p>Results</p> <p>Two 454 pyrosequencing runs generated 572,982 and 588,651 reads for germline (TES) and somatic (VAS) tissues of the <it>A. suum </it>gonad, respectively. 86% of the high-quality (HQ) reads were assembled into 9,955 contigs and 69,791 HQ reads remained as singletons. 2.4 million bp of unique sequences were obtained with a coverage that reached 16.1-fold. 4,877 contigs and 14,339 singletons were annotated according to the <it>C. elegans </it>protein and the Kyoto Encyclopedia of Genes and Genomes (KEGG) protein databases. Comparison of TES and VAS transcriptomes demonstrated that genes participating in DNA replication, RNA transcription and ubiquitin-proteasome pathways are expressed at significantly higher levels in TES tissues than in VAS tissues. Comparison of the <it>A. suum </it>TES transcriptome with the <it>C. elegans </it>microarray dataset identified 165 <it>A. suum </it>germline-enriched genes (83% are spermatogenesis-enriched). Many of these genes encode serine/threonine kinases and phosphatases (KPs) as well as tyrosine KPs. Immunoblot analysis further suggested a critical role of phosphorylation in both testis development and spermatogenesis. A total of 2,681 <it>A. suum </it>genes were identified to have associated RNAi phenotypes in <it>C. elegans</it>, the majority of which display embryonic lethality, slow growth, larval arrest or sterility.</p> <p>Conclusions</p> <p>Using deep sequencing technology, this study has produced a gonad transcriptome of <it>A. suum</it>. By comparison with <it>C. elegans </it>datasets, we identified sets of genes associated with spermatogenesis and gonad development in <it>A. suum</it>. The newly identified genes encoding KPs may help determine signaling pathways that operate during spermatogenesis. A large portion of <it>A. suum </it>gonadal genes have related RNAi phenotypes in <it>C. elegans </it>and, thus, might be RNAi targets for parasite control.</p

A Cell-to-Cell Equalizer Based on Three-Resonant-State Switched-Capacitor Converters for Series-Connected Battery Strings

Due to the low cost, small size, and ease of control, the switched-capacitor (SC) battery equalizers are promising among active balancing methods. However, it is difficult to achieve the full cell equalization for the SC equalizers due to the inevitable voltage drops across Metal-Oxide-Semiconductor Field Effect Transistor (MOSFET) switches. Moreover, when the voltage gap among cells is larger, the balancing efficiency is lower, while the balancing speed becomes slower as the voltage gap gets smaller. In order to soften these downsides, this paper proposes a cell-to-cell battery equalization topology with zero-current switching (ZCS) and zero-voltage gap (ZVG) among cells based on three-resonant-state SC converters. Based on the conventional inductor-capacitor (LC) converter, an additional resonant path is built to release the charge of the capacitor into the inductor in each switching cycle, which lays the foundations for obtaining ZVG among cells, improves the balancing efficiency at a large voltage gap, and increases the balancing speed at a small voltage gap. A four-lithium-ion-cell prototype is applied to validate the theoretical analysis. Experiment results demonstrate that the proposed topology has good equalization performances with fast equalization, ZCS, and ZVG among cells

Second-Order EKF White Noise Estimator Design for Hybrid Systems

The extended Kalman filter (EKF) has a wide range of applications (especially in power battery management systems) with a rapidly increasing market share. It aims to minimize the symmetric loss function (mean square error) and it has high accuracy and efficiency in battery state estimation. This study deals with the second-order extended Kalman filter-based process and the measurement white noise estimation problem for nonlinear continuous-discrete systems. The design of the white noise filter and smoother were, firstly, converted into a linear estimation problem by the second-order Taylor series expansion approximation and the function that makes the second-order term approximately equivalent to the estimation error variance. Secondly, based on the projection formula of the Kalman filtering (KF) theory and the Lemma of expectation for quadratic and quartic product traces of random vectors, the second-order EKF was derived. Then, to generate white noise estimators in the forms of filtering and smoothing, we derived a recursive solution, using an innovation method. Finally, a numerical example is given to show the effectiveness of the proposed method

Parameters Identification and Sensitive Characteristics Analysis for Lithium-Ion Batteries of Electric Vehicles

This paper mainly investigates the sensitive characteristics of lithium-ion batteries so as to provide scientific basises for simplifying the design of the state estimator that adapt to various environments. Three lithium-ion batteries are chosen as the experimental samples. The samples were tested at various temperatures (−20 ∘ C, −10 ∘ C, 0 ∘ C , 10 ∘ C , 25 ∘ C) and various current rates (0.5C, 1C, 1.5C) using a battery test bench. A physical equivalent circuit model is developed to capture the dynamic characteristics of the batteries. The experimental results show that all battery parameters are time-varying and have different sensitivity to temperature, current rate and state of charge (SOC). The sensitivity of battery to temperature, current rate and SOC increases the difficulty in battery modeling because of the change of parameters. The further simulation experiments show that the model output has a higher sensitivity to the change of ohmic resistance than that of other parameters. Based on the experimental and simulation results obtained here, it is expected that the adaptive parameter state estimator design could be simplified in the near future

A Cell-to-Cell Equalizer Based on Three-Resonant-State Switched-Capacitor Converters for Series-Connected Battery Strings

Due to the low cost, small size, and ease of control, the switched-capacitor (SC) battery equalizers are promising among active balancing methods. However, it is difficult to achieve the full cell equalization for the SC equalizers due to the inevitable voltage drops across Metal-Oxide-Semiconductor Field Effect Transistor (MOSFET) switches. Moreover, when the voltage gap among cells is larger, the balancing efficiency is lower, while the balancing speed becomes slower as the voltage gap gets smaller. In order to soften these downsides, this paper proposes a cell-to-cell battery equalization topology with zero-current switching (ZCS) and zero-voltage gap (ZVG) among cells based on three-resonant-state SC converters. Based on the conventional inductor-capacitor (LC) converter, an additional resonant path is built to release the charge of the capacitor into the inductor in each switching cycle, which lays the foundations for obtaining ZVG among cells, improves the balancing efficiency at a large voltage gap, and increases the balancing speed at a small voltage gap. A four-lithium-ion-cell prototype is applied to validate the theoretical analysis. Experiment results demonstrate that the proposed topology has good equalization performances with fast equalization, ZCS, and ZVG among cells

A sine-wave heating circuit for automotive battery self-heating at subzero temperatures

Self-heating is of extreme importance for improving the available capacity and lifetime of lithium-ion batteries in cold climates. However, few attempts have been done to achieve effective onboard self-heating for the batteries in electric vehicles. This paper derives a high-frequency sine-wave (SW) heater based on resonant LC converters to self-heat the automotive batteries at low-temperatures without the need of external heaters. To be specific, an interleaved-parallel topology is introduced to double the heating speed without extra damages to batteries compared to the single heater. Further, a corresponding thermoelectric model is developed to provide guidance for the optimal design of the parameters in the proposed SW heater. Experimental results show that with a high-frequency sinusoidal current motivated by the proposed heater, lithium-ion batteries could be effectively self-heated by the ohmic-loss and electrochemical heat. Moreover, the heating time could be significantly shortened through decreasing the characteristic impedance √(L/C) or increasing the ac-heating frequency