Abstract
Accurate evaluation of Li-ion battery (LiB) safety conditions can reduce unexpected cell failures, facilitate battery deployment, and promote low-carbon economies. Despite the recent ...progress in artificial intelligence, anomaly detection methods are not customized for or validated in realistic battery settings due to the complex failure mechanisms and the lack of real-world testing frameworks with large-scale datasets. Here, we develop a realistic deep-learning framework for electric vehicle (EV) LiB anomaly detection. It features a dynamical autoencoder tailored for dynamical systems and configured by social and financial factors. We test our detection algorithm on released datasets comprising over 690,000 LiB charging snippets from 347 EVs. Our model overcomes the limitations of state-of-the-art fault detection models, including deep learning ones. Moreover, it reduces the expected direct EV battery fault and inspection costs. Our work highlights the potential of deep learning in improving LiB safety and the significance of social and financial information in designing deep learning models.
Electrochemical impedance spectroscopy (EIS) is a powerful tool for investigating electrochemical systems, such as lithium-ion batteries or fuel cells, given its high frequency resolution. The ...distribution of relaxation times (DRT) method offers a model-free approach for a deeper understanding of EIS data. However, in lithium-ion batteries, the differential capacity caused by diffusion processes is non-negligible and cannot be decomposed by the DRT method, which limits the applicability of the DRT method to lithium-ion batteries. In this study, a joint estimation method with Tikhonov regularization is proposed to estimate the differential capacity and the DRT simultaneously. Moreover, the equivalence of the differential capacity and the incremental capacity is proven. Different types of commercial lithium-ion batteries are tested to validate the joint estimation method and to verify the equivalence. The differential capacity is shown to be a promising approach to the evaluation of the state-of-health (SOH) of lithium-ion batteries based on its equivalence with the incremental capacity.
Heating battery at low temperatures is fundamental to avoiding the range anxiety and the time-consuming charging associated with electric vehicles (EVs). One method for achieving fast and uniform ...battery heating is to polarize the cell under pulse currents. However, the on-board implementation of this method leads to an increase in the cost and size. Therefore, in this study, an adapted EV circuitry compatible with the existing one and an optimized operating condition are proposed to enable rapid battery heating. With this circuit, electricity transfer between the cells can be realized through a motor, leading to remarkably higher battery currents than those of the conventional circuit. The increase in the maximum heating currents (from 1.41C to 4C) resulted in a battery temperature rise of 8.6°C/min at low temperatures. This heating method exhibits low cost, high efficiency, and negligible effects on battery degradation, practical and promising on battery heating of EVs.
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•Rapid temperature rise, high efficiency, and low cost for battery heating are obtained•The batteries are divided into two modules and connected to the inverter individually•The electricity transferred between battery modules is motivated by a static motor•The pulse currents for battery heating are improved significantly at any frequency
Electrochemistry; Electrochemical Energy Storage; Energy Engineering; Energy Systems; Energy Materials
The tectonic background and sedimentary environment during the transition period from the Ordovician to Silurian have been widely studied by many scholars. This study focuses on the Upper Ordovician ...Wufeng Formation and Lower Silurian Longmaxi Formation in the Bajiaokou profile at the southern margin of the Qinling Orogenic Belt in southern China. In order to study the aggregation mechanism of organic matter, geochemical proxies were proposed, including redox proxies (V, V/Al, U, U/Al, Mo, and Mo/Al), paleoproductivity proxies (P, P/Ti, Ba, Ba/Al, and SiXS), paleoclimate proxies (CIA), and terrigenous flux proxies (Al, Zr, and Zr/Al). In addition, Al–CoEF × MnEF is used to provide information on paleoenvironmental parameters such as watermass restriction conditions. The redox proxies show that the Wufeng–Longmaxi shale is mainly accumulated under oxic–dysoxic conditions. During the shale deposition period of Wufeng–Longmaxi formations, the marine surface primary productivity in the southern Qinling area is generally low to moderate. The paleoclimate proxies show that from the Late Ordovician to the Early Silurian the southern Qinling area generally had a warm and humid climate. The upwelling current is widely developed in the northern margin of the Sichuan Basin and the southern margin of the Qinling area. Although the upwelling current was highly developed during the deposition of the Wufeng Formation in the Bajiaokou profile, the concentrated accumulation of a large amount of volcanic ash resulted in the low primary productivity of the ocean. During the sedimentary period of the Longmaxi Formation in the Bajiaokou profile, the development of seasonal upwelling currents and a small amount of volcanic ash supply increased the primary productivity to moderate, which provided a good material basis for the enrichment of organic matter, but the high detritus flux and the water body condition of oxic–dysoxic resulted in the slight enrichment of organic matter.
The state estimation of lithium-ion battery is the basis of an intelligent battery management system; therefore, both model-based and data-driven methods have been designed and developed for state ...estimation. Rather than using complex partial differential equations and the complicated parameter tuning of a model-based method, a machine learning algorithm provides a new paradigm and has been increasingly applied to cloud big-data platforms. Although promising, it is now recognized that big data for machine learning may not be consistent in terms of data quality with reliable labels. Moreover, many algorithms are still applied as a black box that may not learn battery inner information well. To enhance the algorithm generalization in realistic situations, this paper presents a fractional-order physics-informed recurrent neural network (PIRNN) for state estimation. The fractional-order characteristics from battery mechanism are embedded into the proposed algorithm by introducing fractional-order gradients in backpropagation process and fractional-order constraints into the convergence loss function. With encoded battery knowledge, the proposed fractional-order PIRNN would accelerate the convergence speed in training process and achieve improved prediction accuracies. Experiments of four cells under federal urban driving schedule operation conditions and different temperatures are conducted to illustrate the estimation effects of the proposed fractional-order PIRNN. Compared to the integer-order gradient descent method, the fractional-order gradient descent method proposed in this work can optimize network convergence and obtains regression coefficient larger than 0.995. Moreover, the experimental results indicate that the proposed algorithm can achieve 2.5% estimation accuracy with the encoding fractional-order knowledge of lithium-ion batteries.
To explore the sedimentary environment and the background of the source area of organic-rich shales in the Wufeng–Longmaxi Formations in the northern Sichuan Basin, samples from Well XX1 in the area ...were subjected to geochemical testing and analysis of organic carbon content, trace elements, and rare earth elements (REEs). The results show that the total content of REE (ΣREE) of the shale in the Wufeng–Longmaxi Formations varied from 183.08 to 234.66 μg/g with an average of 212.59 μg/g, which is significantly higher than the content of the North American shale composite. The fluctuations in the total amount of REEs in the shale of the Wufeng–Longmaxi Formations reflect certain differences in the geochemical conditions of the Upper Ordovician–Lower Silurian shale. The ratios of LREE/HREE, LaN/YbN, LaN/SmN, and GdN/YbN and the distribution of normalized REE patterns indicate that the source supply or sedimentary structural background may have changed during the shale deposition period of the Wufeng Formation, while the shale deposition period of the Longmaxi Formation may be in a relatively stable source supply and sedimentary structural background. There is no significant correlation between δCe and ΣREE, and the obviously negative Eu abnormity and the weak Ce abnormity indicated that the diagenesis had a limited impact on REEs. Geochemical parameters such as values of ∑REE, δEu, δCe, Ceanom, and LaN/YbN indicate that the climate during the Wufeng–Longmaxi Formation shale deposition period was warm and humid, and the shale was deposited mainly in the suboxic-anoxic water environment. The deposition rate was stable and slow, providing good conditions for the production and preservation of organic matter. At the same time, this shows that the water environment of Wufeng Formation is more anoxic and reductive than that of Longmaxi Formation, which is more conducive to the preservation of organic matter. The correlation between ΣREE and the content of Sc, Ti, Cr, Co, Zr, Nb, Th, Hf, Ta, and other elements indicates that the sources of REEs in the shale of Wufeng and Longmaxi Formations in the study area are similar, mainly terrestrial clasts, and some may come from the sea. The REE distribution pattern shows that the shale provenance of the Wufeng–Longmaxi Formations mainly comes from the upper crust. The La/Yb–∑REE diagram shows that the sediment-parent rocks are mainly early sedimentary rocks and these sediment-parent rocks have granite provenance characteristics. Compared to La/Yb, LREE/HREE, LaN/YbN, and other REE characteristic parameters, it is inferred that the tectonic background of the study area is dominated by passive continental margin.
The physicochemical properties of starch acetates with an equal degree of substitution prepared from pea, corn, and wheat starch and their effects on frozen cooked noodle (FCN) quality were ...investigated. The result showed that the three kinds of starch acetates had different effects on the quality of FCN due to their different blue values, freeze‐thaw stability, and crystalline morphology analyzed by XRD (p < .05). The FCN with the addition of 20% CAS exhibited slow deterioration of textural properties during holding for 30 min. The analysis of the changes in the content of free SH group and glutenin macropolymer (GMP) demonstrated that the addition of CAS promoted protein disulfide cross‐linking and decreased protein mobility during holding. Fourier transform infrared spectroscopy (FT‐IR) revealed that FCN with the addition of CAS had low decrement in α‐helix and β‐sheet during holding, indicating that starch acetates contributed to the maintenance of the gluten network structure.
Starch acetates with an equal degree of substitution have different effects on the quality of frozen cooked noodles (FCNs); acetylated corn starch (CAS), acetylated wheat starch (WAS), and acetylated pea starch (PAS) were effective in reducing cooking loss and improving springiness of FCNs. Starch acetates can be used as a novel additive in FCNs to provide specific functionality and alleviate the deterioration of quality during holding.
Luminescent materials that display quick spectral responses to thermal stimuli have attracted pervasive attention in sensing technologies. Herein, a programmable luminescence color switching in ...lanthanide‐doped LiYO2 under thermal stimuli, based on deliberate control of the monoclinic (β) to tetragonal (α) phase transition in the crystal lattice, is reported. Specifically, a lanthanide‐doping (Ln3+) approach to fine‐tune the phase‐transition temperature in a wide range from 294 to 359 K is developed. Accordingly, an array of Ln3+‐doped LiYO2 crystals that exhibit progressive phase transition, and thus sequential color switching at gradually increasing temperatures, is constructed. The tunable optical response to thermal stimuli is harnessed for colorimetric temperature indication and quantitative detection, demonstrating superior sensitivity and temperature resolution (Sr = 26.1% K−1, δT = 0.008 K). The advances in controlling the phase‐transition behavior of luminescent materials also offer exciting opportunities for high‐performance personalized health monitoring.
Ultrasensitive optical thermometry is realized over a broad temperature range through progressive phase transitions in LiYO2 crystals. Remarkably, a programmable luminescence color switching at prescribed temperatures is realized. Thus an ultra‐high thermal sensitivity and resolution that outperforms the existing luminescent thermometers is obtained. The superiority of this thermometer for intelligent wearable devices is substantiated.
Simplified geological map showing the location of carbonatites, carbonatite-related REE deposits, and bastnäsite-dominated carbonatite-related REE deposits (i.e., where bastnäsite is among the three ...most abundant REE minerals; Weng et al., 2015; Smith et al., 2016). Map modified after Tang et al. (2013).
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•Ba, Sr, Ca, Th, U, and Sc commonly replace La and Ce in bastnäsite.•Large-scale bastnäsite crystallization occurred at the later stage of the hydrothermal system.•The process of REE enrichment in the Mianing-Dechang deposits is established.•The barite–calcite–fluorite assemblage can be regarded as a valuable guide in exploration for REE deposits.
Bastnäsite is the main ore mineral in many carbonatite-related rare earth element (REE) deposits, which account for ∼51% of rare-earth oxide reserves worldwide. However, the occurrence, geochemistry, and genetic significance of bastnäsite has not been methodically investigated. The Cenozoic Mianning–Dechang (MD) REE belt in Sichuan Province, SW China, contains the Maoniuping, Dalucao, Lizhuang, and Muluozhai deposits as well as numerous smaller REE occurrences. Individual deposits within the belt contain different types of bastnäsite-bearing ore, which provides a unique opportunity to explore in detail the common mechanisms controlling the formation of bastnäsite-rich REE deposits.
Here, we present detailed results from field observations and petrographic, geochemical, and fluid inclusion studies of bastnäsite from the main MD deposits. Calcite, fluorite, and barite form stable mineral assemblages that are commonly overprinted by bastnäsite. Homogenization temperatures of fluid inclusions in bastnäsite of ∼150–270 °C (Dalucao and Lizhuang deposits) and 155–210 °C (Maoniuping deposit) are systematically lower than those of fluid inclusions in gangue minerals. Therefore, the petrographic studies and homogenization temperatures both show that large-scale crystallization of bastnäsite took place during the later stage of the hydrothermal system. The bastnäsite, relatively geochemically homogeneous within all of the MD deposits, is enriched in Ba (293–8425 ppm), Th (16.4–2527 ppm), and U (4.19–92.7 ppm), and relatively depleted in high field strength elements such as Nb (0.15–17.4 ppm), Ta (0.06–6.48 ppm), Zr (0.71–31.1 ppm), Hf (0.62–5.65 ppm), and Ti (<60 ppm), the same to carbonatite, and ore veins. In comparison, the samples from the study area show an increase in average REE contents from syenites to carbonatites to ore veins (i.e., bastnäsite-bearing ores) and finally to bastnäsite. Lanthanum and Ce were commonly substituted by Th, U, Sc, Ba, and Sr supplied by more evolved hydrothermal fluids.
Combining the present results with existing data, we present a three-stage model for the formation of carbonatite-related REE deposits. First, partial melting of metasomatized sub-continental lithospheric mantle, fluxed by REE- and CO2-rich fluids, forms the parental carbonatite–syenite magma. Second, Sr, Ba, and REEs are strongly partitioned into carbonatite melts during liquid immiscibility in the carbonatite–syenite magmatic system. Third, hydrothermal fluids exsolved from the crystalizing syenite and carbonatite magmas form ore veins with early gangue minerals and later bastnäsite overgrowths. Consequently, barite, calcite, and fluorite assemblages are a valuable guide in REE exploration.
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