batterydata/paper-abstracts huggingface dataset:
Voltage, temperature, and state of charge (SOC) are the main characterizing parameters for various battery faults that can cause these parameters’ abnormal fluctuations. Accurate prediction for these parameters is critical for the safe, durable, and reliable operation of battery systems in electric vehicles. This paper investigates a new deep-learning-enabled method to perform accurate synchronous multi-parameter prediction for battery systems using a long short-term memory (LSTM) recurrent neural network. A year-long dataset of an electric taxi was retrieved at the Service and Management Center for electric vehicles (SMC-EV) in Beijing to train the LSTM model and verify the model’s validity and stability. By taking into account the impacts of weather and driver’s behaviors on a battery system’s performance to improve the prediction accuracy, a Weather-Vehicle-Driver analysis method is proposed, and a developed pre-dropout technique is introduced to prevent LSTM from overfitting. Besides, the many-to-many(m-n) model structure using a developed dual-model-cooperation prediction strategy is applied for offline training the LSTM model after all hyperparameters pre-optimized. Additionally, the stability and robustness of this method have been verified through 10-fold cross-validation and comparative analysis of multiple sets of hyperparameters. The results show that the proposed model has powerful and precise online prediction ability for the three target parameters. This paper also provides feasibility for synchronous multiple fault prognosis based on accurate parameter prediction of the battery system. This is the first of its kind to apply LSTM to the synchronous multi-parameter prediction of the battery system.
Cyanoethylated carboxymethyl chitosan (CN-CCTS) has been synthesized through a straightforward cyanoethylation reaction by reacting CCTS with acrylonitrile in NaOH aqueous solution. CN-CCTS shows improved adhesion strength of 0.047N/cm as compared with 0.013N/cm for CCTS after introducing cyanoethyl group in the chemical structure of CCTS. The electrochemical performances of LiFePO4 electrode with CN-CCTS binder have been investigated and compared with those using water soluble sodium carboxymethyl cellulose (CMC) and non-aqueous polyvinylidene difluoride (PVDF) binder. LiFePO4 electrode with CN-CCTS exhibits better cycling stability and rate capability, retaining 56.3% capacity of C/5 at 5C rate as compared with 48.4% and 32.8% for CMC and PVDF, respectively. Cyclic voltammetry and electrochemical impedance spectroscopy measurement reveal that LiFePO4 electrode with CN-CCTS has a more favorable electrochemical kinetics than that with CMC and PVDF, thus better rate capability.
Profitable business models for value creation and value capture with smart grid services are pivotal to realize the transition to smart and sustainable electricity grids. In addition to knowledge regarding the technical characteristics of smart grids, we need to know what drives companies and consumers to sell and purchase services in a smart grid. This paper reviews 45 scientific articles on business models for smart grid services and analyses information on value in 434 European and US smart grid pilot projects. Our review observes that the articles and pilots most often discuss three types of smart grid services: vehicle-to-grid and grid-to-vehicle services, demand response services, and services to integrate renewable energy (RE). We offer a classification of business models, value creation and capture for each of these services and for the different actors in the electricity value chain. Although business models have been developed for grid-to-vehicle services and for services that connect RE, knowledge regarding demand response services is restricted to different types of value creation and capture. Our results highlight that business models can be profitable when a new actor in the electricity industry, that is, the aggregator, can collect sufficiently large amounts of load. In addition, our analysis indicates that demand response services or vehicle-to-grid and grid-to-vehicle services will be offered in conjunction with the supply of RE.
Aqueous electropolymerization of thiophene and 3-methylthiophene was accomplished on β-PbO2 electrodes. Poly 3-methylthiophene films were also formed on α-PbO2 surfaces under acidic conditions. It was also determined that the upper potential limit for thiophene electropolymerization could be lowered by about 400 mV using β-PbO2 compared to the platinum electrode in pure acetonitrile, whereas this limit was lowered only by about 200 mV on the α-PbO2 electrode. In the case of 3-methylthiophene, the upper potential limit was decreased to 1.1 V vs. Ag|AgCl on the β-PbO2 electrode and this lower limit was found to be 1.3 V vs. Ag|AgCl on the α-PbO2 electrode. It was also shown that the polymorphic composition and degrees of crystallinities of PbO2 films also influenced the extent of the electropolymerizations and the conductivity values.
Many conventional truck and working machines are equipped with additional hydraulic tooling or manipulation systems which are usually fed through a mechanical connection with the internal combustion engine, involving a poor efficiency. In particular, this is a common situation for industrial vehicles whose mission profiles involves a relevant consumption of energy by the on board hydraulic systems, respect to the one really needed for only traction purpose. In this work it is proposed an innovative solution based on the adoption of a system aimed to recover braking energy in order to feed an efficient on board hydraulic actuation system. The proposed system is then adopted to a real application, an Isuzu truck equipped with a hydraulic tooling for garbage collection. A prototype of the system has been designed, assembled and tested showing a relevant improvement of system efficiency and the feasibility of the proposed approach. In the paper the proposed solution is presented, showing the simulation models and preliminary validation results including experimental devices assembled to perform the tests.
As an advanced anode material for lithium-ion batteries, tin-chalcogenides receive substantial attention due to their high lithium-ion storage capacity. Here, tin chalcogenide (SnSe0.5S0.5) nanoplates are synthesized using a facile and quick polyol-method, followed by heating at different temperatures. Results show that the as-prepared of SnSe0.5S0.5 heated at temperature of 180 °C exhibits the best electrochemical performance with an outstanding discharge specific capacity of 1144 mA h g−1 at 0.1 A g−1 after 100 cycles and 682 mA h g−1 at 0.5 A g−1 after 200 cycles with a high coulombic efficiency (CE) of 98.7%. Even at a high current density of 5 A g−1, this anode material delivers a specific capacity of 473 mA h g−1. The high electrochemical performance of SnSe0.5S0.5 is shown by in-situ XRD analysis to originate from an enhanced Li+ intercalation and an alloy conversion process.
The gram-scale synthesis of graphene based mesoporous SnO2 composite (G-M-SnO2) has been successfully realized based on kirkendall effect. When used as anode for lithium ion batteries, it delivers a high reversible capacity of 1354 mAhg−1 after 50 cycles at 100 mAg−1 and excellent rate capability of 664 mAhg−1 at 2 Ag−1. The outstanding lithium storage performance mainly results from the synergistic effect of the ultrasmall SnO2 and conductive graphene nanoparticles, which not only enhanced the conductivity of the whole electrode but also provide buffer matrix for the expansion of SnO2 nanoparticles during charge-discharge process. Furthermore, the ultra-small size of SnO2 shortens the diffusion length of Li+/e− in SnO2.
The purpose of this study is to examine the relative importance of the force-based and velocity-based measures of muscle performance to explain inter-individual differences in power production capability and functional task performance. Participants included seventy-nine men and women: middle-aged healthy adults (MH: 40–55years), older healthy adults (OH: 70–85years), and older adults with mobility limitations (OML: 70–85years). Muscle power at 180°/s, isometric maximal torque, and maximal contraction velocity at 40% 1RM were measured during unilateral leg extension. The Short Physical Performance Battery (SPPB) was used to differentiate between healthy and mobility limited older adults. Functional task performance was assessed using multiple chair rise and stair climb tests. Leg extensor force (torque), but not maximal contraction velocity, was significantly associated with muscle power in MH. Both torque and velocity were significantly associated with muscle power in OH. Maximal velocity, but not torque, was associated with power in OML. Maximal velocity demonstrated an association with multiple chair rise time and stair climb time in OML, but not MH or OH. It is concluded that movement velocity is an increasingly important determinant of maximal power output with advancing age. Furthermore, movement velocity is also a critical component of functional task performance with aging and may contribute to functional deficits. These findings help to explain why the rate-dependent variable power has emerged as a critical component of both assessment and rehabilitation of muscular performance and physical function in older adults.
Flexible Zn-based batteries with intrinsic safety, non-toxicity and biocompatibility are promising power sources for wearable electronics. To meet practical applications, they need to be durable, robust and stable. However, inevitable self-discharge and interface delamination between electrodes and hydrogel electrolytes often cause serious capacity fading or even failure for flexible Zn-based batteries. Here, inspired from nature, we report hydrogel diodes with strong and tunable interfacial adhesion by attaching oppositely charged hydrogels together. The high adhesion energy is stemmed from strong coulombic interaction and effectively dissipating energy of hydrogel matrix. The adhesion is facilely tuned by narrowing the depletion region in hydrogel diodes. Subsequently we design Hook&Loop-like Cu-Zn batteries by using hydrogel diodes as electrolytes, which are robust, stable and durable and capable for powering wearable electronics. The batteries can eliminate self-discharge and maintain their capacity by splitted into two half cells during long-term storage and easily reattaching together at working stage. Further, the batteries are ultra-stable during 2000 stretching and bending cycles because of their robust interfacial adhesion. It is believed the hydrogel-electrolyte platforms can be utilized to harness issues including interface contact, stability, durability and safety for flexible power sources.
Since the 90's, porous silicon has been studied and implemented in many devices, especially in MEMS technology. In this article, we present a new approach to build miniaturized proton exchange membrane micro-fuel cells using porous silicon as a hydrogen diffusion layer. In particular, we propose an innovative process to build micro fuel cells from a “corrugated iron like” 3D structured porous silicon substrates. This structure is able to increase up to 40% the cell area keeping a constant footprint on the silicon wafer. We propose here a process route to perform electrochemically 3D porous gas diffusion layers and to deposit fuel cell active layers on such substrates. The prototype peak power performance was measured to be 90 mW cm−2 in a “breathing configuration” at room temperature. These performances are less than expected if we compare with a reference 2D micro fuel cell. Actually, the active layer deposition processes are not fully optimized but this prototype demonstrates the feasibility of these 3D devices.
Titanium dioxide is a promising photocatalyst and has been widely used in many applications. However, it remains challenging to improve the photocatalytic performance of TiO2 under visible light illumination. Herein, a facile one step method was put forward to produce Mn-doped TiO2 nanotube arrays (TNTs) without the formation of manganese oxides. Intermediate band states were generated in Mn-doped TNTs, leading to enhanced visible light absorption and more efficient separation of photo-generated electron–hole pairs. The visible light photocatalysis of Mn-doped TNTs was significantly improved. The method reported here might be extended to the doping of other elements in TNTs and provides opportunities for the design of advanced photocatalysts.
Seven cell design concepts for aqueous (alkaline) lithium–oxygen batteries are investigated using a multi-physics continuum model for predicting cell behavior and performance in terms of the specific energy and specific power. Two different silver-based cathode designs (a gas diffusion electrode and a flooded cathode) and three different separator designs (a porous separator, a stirred separator chamber, and a redox-flow separator) are compared. Cathode and separator thicknesses are varied over a wide range (50 μm–20 mm) in order to identify optimum configurations. All designs show a considerable capacity-rate effect due to spatiotemporally inhomogeneous precipitation of solid discharge product LiOH·H2O. In addition, a cell design with flooded cathode and redox-flow separator including oxygen uptake within the external tank is suggested. For this design, the model predicts specific power up to 33 W/kg and specific energy up to 570 Wh/kg (gravimetric values of discharged cell including all cell components and catholyte except housing and piping).
The battery system plays an important role in a number of modern power applications. In practice, cell charge imbalance is a very common issue in battery system operations, which may cause serious problems in power efficiency, equipment reliability and safety, etc. To analyze the performance of battery equalization systems, physical experiments with actual devices and computer simulations based on circuit models are typically used. These approaches, however, may be time-consuming and energy-inefficient for larger-scale systems. In this paper, based on the proposed mathematical model for series-connected battery equalization systems, we develop an analytical algorithm to approximate the state of charge (SOC) of battery cells at any time instant during the equalization process, and derive the formulas to calculate critical performance measures of the system. Extensive numerical experiments are carried out to justify the accuracy of the algorithm and formulas developed. In addition, the proposed methods use much less computational time as compared to computer simulations.
Li dendrite formed in Li metal batteries can be categorized into two different types. One is the detrimental Li dendrite that heads towards the separator with a potential to short cell. The other is the ill-defined fibrous Li formed within bulk Li metal. The detrimental Li dendrite may cause cell short, while the other dendrites, covered by SEI, mainly increase cell impedance and terminate the cell operation, most often, before any “short” really happens. Without decoupling these two different Li dendrites, it is hard to develop any effective approach to realize both stable and safe Li metal batteries. Herein, a straightforward approach is proposed to induce the growth of detrimental dendritic Li so the cells are “shorted” frequently and consistently. Based on this new protocol, various electrolytes are revisited and the SEI derived are compared and quantified, providing new insights for addressing the challenges in rechargeable Li metal battery technologies.
Background Verbal and visual memory deficits are prominent trait markers for schizophrenia, with impairments also observed in first-degree relatives [Snitz, B.E., Macdonald, A.W., 3rd, & Carter, C.S. (2006). Cognitive deficits in unaffected first-degree relatives of schizophrenia patients: a meta-analytic review of putative endophenotypes. Schizophr Bull, 32(1), 179–194]. It remains unclear whether deficits lie in encoding or savings, and whether the deficit is heritable. Objective To determine which features of memory performance are impaired in both patients and their healthy siblings, possibly reflecting shared genetic effects. Method We tested episodic memory using Logical Memory (LM) and Visual Reproduction (VR) tasks of the Wechsler Memory Scale (Revised). Participants included patients with schizophrenia (n =162), their nonpsychotic siblings (n =146), and controls (n =205), recruited for the “CBDB/NIMH Sibling Study”. We assessed immediate encoding and 30 minute and 24 hour delayed recall as well as savings scores for the “short delay” (immediate to 30 min) and “long delay” (30 min to 24 h) intervals. Results We observed marked verbal recall deficits in both patients and siblings compared to controls for all stages (p <.0001). Only patients experienced significant verbal and visual savings deficits over short delays (p <.0001) as well as verbal deficits over long delays (p <.005). In siblings, no saving score difficulty was apparent for either measure. Conclusions Our results confirm shared impairment in verbal learning, but not memory, for both patients and siblings, therefore marking it as a potential schizophrenia-associated intermediate phenotype. The results implicate neural systems involved in immediate encoding and stabilization of memory representations in genetic risk for schizophrenia. In contrast, visual recall and savings impairments appear to be illness, i.e. state, deficits.
Peripheral nerve injury causes long-term disabilities for patients and also major socio-economic costs. The common approach to repair a short-distance gap in peripheral nerve is direct suturing of two stumps. In cases of long nerve gaps, implantation of autologous nerve grafts such as sural nerve to bridge the gap is still the gold standard, but it suffers from limited length, lack of donor nerves, morbidity of donor site and scar tissue invasion. The use of allogenic and xenogeneic tissues has also been suggested which eliminate the need of secondary surgeries on patients; however, they may arise the risk of disease transmission and immunogenicity problems. Nerve tissue engineering can be an alternative approach which provide a suitable and permissive microenvironment at the injury site using biocompatible scaffolds. An effective scaffold should provide required mechanical support for growing neurites, reduce scar tissue formation, and also chemical (e.g., release of nerve growth factors) and physical (e.g., topographical and electrical) signals [1–3].
Flexible ceramic separators based on Li+-conducting lithium lanthanum zirconium oxide are prepared as thin films and directly applied onto negative electrode to produce a separator-electrode assembly with good interfacial adhesion and low interfacial resistances. The ceramic separators show an excellent thermal stability and high ionic conductivity as compared to conventional polypropylene separator. The lithium-ion batteries assembled with graphite negative electrode, Li+-conducting ceramic separator and LiCoO2 positive electrode exhibit good cycling performance in terms of discharge capacity, capacity retention and rate capability. It is also demonstrated that the use of a ceramic separator can greatly improve safety over cells employing a polypropylene separator, which is highly desirable for lithium-ion batteries with enhanced safety.
A microgrid energy management framework for the optimization of individual objectives of microgrid stakeholders is proposed. The framework is exemplified by way of a microgrid that is connected to an external grid via a transformer and includes the following players: a middle-size train station with integrated photovoltaic power production system, a small energy production plant composed of urban wind turbines, and a surrounding district including residences and small businesses. The system is described by Agent-Based Modelling (ABM), in which each player is modelled as an individual agent aiming at a particular goal, (i) decreasing its expenses for power purchase or (ii) increasing its revenues from power selling. The context in which the agents operate is uncertain due to the stochasticity of operational and environmental parameters, and the technical failures of the renewable power generators. The uncertain operational and environmental parameters of the microgrid are quantified in terms of Prediction Intervals (PIs) by a Non-dominated Sorting Genetic Algorithm (NSGA-II) – trained Neural Network (NN). Under these uncertainties, each agent is seeking for optimal goal-directed actions planning by Robust Optimization (RO). The developed framework is shown to lead to an increase in system performance, evaluated in terms of typical reliability (adequacy) indicators for energy systems, such as Loss of Load Expectation (LOLE) and Loss of Expected Energy (LOEE), in comparison with optimal planning based on expected values of the uncertain parameters.
Electrolyte distribution using parallel flow field for redox flow battery (RFB) applications shows severe non-uniformity, while the conventional design of using the carbon felt itself as the flow distributor gives too high pressure drop. An optimized flow field design for uniform flow distribution at a minimal parasitic power loss is therefore needed for RFB systems. Since the materials and geometrical dimensions in RFBs are very different from those used in fuel cells, the hydrodynamics of the flow fields in RFBs is likely to be very different. In the present paper, we report on a fundamental study of the hydrodynamics of a serpentine flow field relevant to RFB applications. The permeability of the porous medium has been measured under different compression ratios and this is found to be in the range of 5–8 × 10−11 m2. The pressure drop in two serpentine flow fields of different geometric characteristics has been measured over a range of Reynolds numbers. Further analysis using computational fluid dynamics simulations brings out the importance of the compression of the porous medium as an additional parameter in determining the flow distribution and pressure drop in these flow fields.
The air electrodes with high activity toward oxygen electrocatalysis and high stability are essential for high-performance Zn-air batteries. Herein, we report an electrode made of Al and Co co-doped NiO nanosheets, which are directly grown on the surfaces of carbon cloth without the addition of binders, facilitating the transport of electrons. Additionally, the hierarchical structure shortens the length for species transport and provides abundant active sites for reactions. In the alkaline solution, the Al and Co co-doped NiO electrode exhibits higher activity in both oxygen reduction and evolution reactions than the pristine NiO electrode without doping and superior stability. When assembled in a Zn-air battery, impressively, this electrode results in stable charge-discharge voltage gaps and energy efficiency of 62% over 1000 cycles (330 h) at 5 mA cm−2. In comparison, a battery with the electrode made of Pt/C and Ir/C shows large voltage gaps and can only be operated for 400 cycles. The characterization of the electrode after cycling illustrates that both the nanosheet morphology and the NiO phase are well maintained. The results demonstrate that the carbon cloth with Al and Co co-doped NiO nanosheets is a promising air electrode to enable the high cycling stability of rechargeable Zn-air batteries.
Changing world politics and military emphasis have brought considerable pressure on space agency financial budgets and a shift to increasing commercialisation of space activities. Budgetary pressure, coupled with the rapid advancement of commercial and consumer micro-electronics, has catalysed the use of smaller and more computationally capable satellites as a ‘faster, cheaper, better’ means of realising space missions - complementary to conventional large satellite systems. Affordable small satellites, however, require a very different approach compared with established space engineering techniques.