batterydata/paper-abstracts huggingface dataset:
An appropriate energy management strategy is able to further improve the fuel economy of PHEVs. The rule-based energy management algorithms are dominated in industry due to their fast computation and ease of establishment potentials, however, their performance differ a lot from improper setting of parameters and control actions. This paper employs the dynamic programming (DP) to locate the optimal actions for the engine in PHEVs, and more importantly, proposes a recalibration method to improve the performance of the rule-based energy management through the results calculated by DP algorithm. Eventually, an optimization-based rule development procedure is presented and further validated by hardware-in-loop (HIL) simulation experiments. The HIL simulation results show that, the improved rule-based energy management strategy reduces fuel consumption per 100km from 25.46L diesel to 22.80L diesel. The main contribution of this study is to explore a novel way to calibrate the existed heuristic control strategy with the global optimization result through advanced intelligent algorithms.
A new facile approach is proposed to synthesize nitrogen-doped graphene sheets with the nitrogen-doping level as high as 7.04at.% by thermal annealing pristine graphene sheets and low-cost industrial material melamine. The high-level nitrogen-doped graphene sheets exhibit a superhigh initial reversible capacity of 1123mAhg−1 at a current density of 50mAg−1. More significantly, even at an extremely high current density of 20Ag−1, highly stable capacity of about 241mAhg−1 could still be obtained. Such an electrochemical performance is superior to those previously reported nitrogen-doped graphene sheets. The excellent electrochemical performance can be attributed to the two-dimensional structure, disordered surface morphology, high nitrogen-doping level, and the existence of pyridinic nitrogen atoms. The results indicate that the high-level nitrogen-doped graphene sheets could be a promising anode material for high-performance lithium-ion batteries.
This paper deals with the real-time energy management strategies for a hybrid energy storage system (HESS), including a battery and a supercapacitor (SC), for an electric city bus. The most attractive advantage deriving from HESSs is the possibility of reducing the battery current stress to extend its lifetime. To quantitatively compare the effects of different control strategies on reducing battery degradation, a dynamic degradation model for the LiFePO4 battery is proposed and validated in this paper. The battery size is optimized according to the requested minimal mileage, while the size of SC is optimized based on the power demand profile of the typical China Bus Driving Cycle (CBDC). Based on the optimized HESS, a novel fuzzy logic controller (FLC) and a novel model predictive controller (MPC) are proposed and compared with the existing rule-based controller (RBC) and filtration based controller (FBC), after all the controllers are tuned to their best performance along the CBDC. It turns out that FLC and RBC achieve the best performance among the four controllers, which is validated by the DP-based result. Furthermore, about 50% of the HESS life cycle cost is reduced in comparison with the battery-only configuration. In addition, the controllers are also compared along the New European Driving Cycle (NEDC), which represents another normalized driving cycle. The results show that the RBC, MPC, and FLC achieve a similar performance, and they reduce about 23% of the HESS life cycle cost when compared to the battery-only configuration. The RBC and FLC are regarded as the best choices in practical applications due to their remarkable performance and easy implementation.
Fe2P–LiFePO4 composites were synthesized by a novel method consisting of co-precipitation modified with in situ polyacrylamide (PAM) formation. Simultaneous thermogravimetric-differential scanning calorimetric analysis indicated that the in situ PAM precursor exhibited a moderate continuous weight loss rather than a sharp mass loss process. The best Fe2P–LiFePO4 composite was obtained from 14 wt% in situ PAM precursor under a sintering temperature of 750 °C for 20 h, which delivered a discharge capacity of 131 mAh g−1 at a rate of C/5 and 110 mAh g−1 at 1 C and sustained 30 cycles with almost no capacity fading. The relatively good electrochemical performance originates mainly from the well-mixed gelation precursor and conductive Fe2P phase with better electronic conductivity. This novel method verified that the electrochemical performance was improved compared to the conventional LiFePO4 without in situ PAM. It can be anticipated that the same process should be readily extendable to other olivines, such as LiMnPO4 and LiCoPO4, and also to other phosphates.
We present the results of a density functional theory study of sodium storage and mobility on graphdiyne (GDY) and consider the applicability of GDY intercalated with sodium (Na) as an anode material for rechargeable batteries. The maximum capacity, energy barriers for Na diffusion throughout the layers, and expansion of the layers due to Na insertion are determined. The calculations indicate that Na intercalates within the GDY bulk layers with a capacity of NaC5.14 without expansion (316 mA h g−1) and NaC2.57 with expansion of 28% (497 mA h g−1). The energy barrier for movement of Na in the slit pore formed by two GDY bulk layers is found to be 0.82 eV for bulk GDY with an AB-2 stacking, and the barrier for movement through a GDY sheet is found to be 0.12 eV. The barrier for movement in the slit pore formed by sheets becomes even lower for AB-3 stacking, with values of 0.68 and 0.40 eV found for different pathways. Movement from one GDY sheet to another for the AB-3 stacking also has a moderate energy of 0.37 eV. Therefore, GDY intercalated with Na is proposed to have potential as an anode material for rechargeable batteries.
We report a 3.8 V manganese-based mixed-phosphate cathode material for applications in sodium rechargeable batteries; i.e., Na4Mn3(PO4)2(P2O7). This material exhibits a largest Mn2+/Mn3+ redox potential of 3.84 V vs. Na+/Na yet reported for a manganese-based cathode, together with the largest energy density of 416 W h kg−1. We describe first-principles calculations and experimental results which show that three-dimensional Na diffusion pathways with low-activation-energy barriers enable the rapid sodium insertion and extraction at various states of charge of the Na4−xMn3(PO4)2(P2O7) electrode (where x = 0, 1, 3). Furthermore, we show that the sodium ion mobility in this crystal structure is not decreased by the structural changes induced by Jahn–Teller distortion (Mn3+), in contrast to most manganese-based electrodes, rather it is increased due to distortion, which opens up sodium diffusion channels. This feature stabilizes the material, providing high cycle stability and high power performance for sodium rechargeable batteries. The high voltage, large energy density, cycle stability and the use of low-cost Mn give Na4Mn3(PO4)2(P2O7) significant potential for applications as a cathode material for large-scale Na-ion batteries.
Biomaterials play a significant role in energy storage devices owing to their renewable, inexpensive and eco-friendly peculiarity. In this study, potato biomass porous carbon (PBPC), which was fabricated by a facile two-step carbonization, was used as the anode material for potassium-ion batteries (KIBs). The crystal structure and mesoporous morphology of the carbon derivative at various carbonation temperatures are fully investigated. The electrochemical performance of PBPC electrodes is evaluated, presenting a high reversible specific capacity (248 mA h g−1 at 100 mA g−1), an excellent rate performance (152 mA h g−1 at 1000 mA g−1) and a superior cycle stability (almost no capacity decay after 400 cycles at a current density of 500 mA g−1 with a Coulombic efficiency about 100%). The superior electrochemical performance is mainly attributed to the uniformly distributed mesopores on PBPC electrode which facilitate the electrolyte transportation and diffusion. This work provides a simple and novel strategy to construct porous carbon as high-performance anode materials for KIBs through a sustainable and environment-friendly way.
Electric vehicles (EVs) are vehicles that are propelled by electric motors powered by rechargeable battery. They are generally asserted to have GHG emissions, driveability and life cycle cost benefits over conventional vehicles. Despite this, EVs face significant challenges due to their limited on-board energy storage capacity. In addition to providing energy for traction, the energy storage device operates HVAC systems for cabin conditioning. This results in reduced driving range. The factors such as local ambient temperature, local solar radiation, local humidity, duration and thermal soak have been identified to affect the cabin conditions. In this paper, the development of a detailed system-level approach to HVAC energy consumption in EVs as a function of transient environmental parameters is described. The resulting vehicle thermal comfort model is used to address several questions such as 1) How does day to day environmental conditions affect EV range? 2) How does frequency of EV range change geographically? 3) How does trip start time affect EV range? 4) Under what conditions does cabin preconditioning assist in increasing the EV range? 5) What percentage increase in EV range can be expected due to cabin preconditioning at a given location?
So-called full-face masks are essential for fire fighters to ensure respiratory protection in smoke diving incidents. While such masks are absolutely necessary for protection purposes on one hand, they impair the voice communication of fire fighters drastically on the other hand. For this reason communication systems should be used to amplify the speech and, therefore, to improve the communication quality. This paper gives an overview of communication enhancement techniques for masks based on digital signal processing. The presented communication system picks up the speech signal by a microphone in the mask, enhance it, and play back the amplified signal by loudspeakers located on the outside of such masks. Since breathing noise is also picked up by the microphone, it’s advantageous to recognize and suppress it – especially since breathing noise is very loud (usually much louder than the recorded voice). A voice activity detection distinguishes between side talkers, pause, breathing out, breathing in, and speech. It ensures that only speech components are played back. Due to the fact that the microphone is located close to the loudspeakers, the output signals are coupling back into the microphone and feedback may occur even at moderate gains. This can be reduced by feedback reduction (consisting of cancellation and suppression approaches). To enhance the functionality of the canceler a decorrelation stage can be applied to the enhanced signal before loudspeaker playback. As a consequence of all processing stages, the communication can be improved significantly, as the results of measurements of real-time mask systems show.
Natural wetland excluding lake and floodplain in China at present covers an area of around 94,000 km 2 and are mainly located in Qinghai-Tibet Highland (∼50%) and northeast China (∼30%), which can be divided into the peatlands (∼42,000 km 2), freshwater marsh (∼25,000 km 2), swamp (∼2,500 km 2), and salt marsh (∼24,000 km 2). The CH4 flux measured in 2001 and 2002 from the peatland in Qinghai-Tibet Highland and the freshwater marsh in Sanjiang Plain ranged from 0.16 to 10.0 and 1.18 to 54.6 mgCH 4 m −2 h −1 , and averaged 2.96 and 19.6 mgCH 4 m −2 h −1 , respectively. Based on our in situ measurement and the available data measured in the previous studies, the preliminarily estimated budget of CH4 emissions from natural wetlands in China was 1.48 TgCH 4 over the growing season and 1.76 TgCH 4 yr −1 .
Battery State of Charge (SOC) estimation is an important function for battery management systems and critical for the reliable operations of batteries. This paper analyzes the robustness of SOC estimation algorithms for two types of Li-ion batteries under varying loading conditions, temperatures and aging levels. Based on the model templates identified in an earlier research, the model parameters are determined. The Extended Kalman Filter (EKF) technique is then adopted as the SOC estimation algorithm. The robustness of the estimator against varying loading profiles and temperatures is evaluated and compared against the Coulomb counting method. We subsequently used data from cells that have significantly aged to assess the robustness of the SOC estimation algorithm. Finally, the need for model parameter updates is analyzed.
Battery systems and charging infrastructures are essential, cost intense, and partly interchangeable building blocks of electric mobility. Although both building blocks are expected to develop favorably in the coming years, their current limitations hinder the adoption of electric vehicles. As their advancement competes for limited resources, it is of interest to quantify the trade-offs between battery capacity and charging infrastructure improvements in order to allocate research and development resources and public spending effectively. In an analysis that utilizes mobility data from a large cohort of regular drivers, we assess the impact of three electric mobility scenario parameters – battery capacity, charging infrastructure coverage, and charging power – on key performance indicators and side effects of electric mobility. The study goes beyond the state-of-the-art in several ways, including the large amount of driving data that serves as input (909 conventional vehicles monitored over two years while traveling over 46.5 million km (28.9 million miles)), the quality of the movement data (profiles based on global positioning systems), and the use of clustering that allows us to assess driver segments separately within one coherent analysis. For 180 battery-infrastructure scenarios, we derive energy consumption and charging behavior of the vehicles, electric reachability of destinations, electric mileage share of hybrid vehicles, and grid impact (electricity demand and time of peaks). Results show that realistic battery capacity improvements dispel concerns about the need for a dense charging infrastructure. We find that only small segments of long-range drivers and vehicles with very limited electric range benefit much from a dense charging network. Moreover, we observe that the benefits of fast charging are small for most driver segments even if charging can take place only at the home location.
ABSTRACT In this paper, an ultrathin layer of acid treated multiwalled carbon nanotubes (CNTs) are conformally wrapped on everyday cotton textiles for subsequently controlled electrodeposition of MnO2 nanoflakes. The general morphology and detailed microstructure of the as-prepared composites are characterized and the formation mechanism is investigated by time-dependent experiments. Such conductive textiles show outstanding flexibility and strong adhesion between the CNTs and the textiles of interest. Supercapacitors made from these ternary conductive textiles show high specific capacitance up to 247F·g−1 at 1A·g−1. A capacity retention of 94.7% can be maintained at 2000 continuous charge-discharge cycles, after which the textiles electrode essentially maintained its whole structural integrity. The discharge curves remain unchanged with a slight capacitance decrease even under vertical folding condition. All these demonstrate that hybrid flexible electrode of MnO2 and conductive textile is an effective strategy towards high-energy supercapacitors and may provide a promising design direction for optimizing the electrochemical performance of insulating metal oxide based on electrode materials.
This paper focuses on the development of a prognostic scheme for estimating the remaining useful life (RUL) of Lithium-ion batteries with missing observations. The scheme has two main modules based on extreme learning machines: pre-processing and prediction. The pre-processing module uses novel single and multiple imputation techniques to estimate the missing observations. The prediction module aims to obtain precise predictions even in the presence of missing observations and with the related uncertainty. The pre-processing module sends imputed subsets of samples to the prediction module, which makes use of extreme learning machines for one-step and multi-steps predictions. The prediction module contains various multi-steps prediction strategies including iterative, direct and DirRec, which use the constant-current experimental capacity data for the long-term prediction of the remaining useful life. Accurate prediction of RUL requires continuity in the time-series dataset. The proposed scheme is designed to build an intelligent prediction system with the ability to handle time-series data containing missing values and is robust enough to generate a complete time-series dataset and, then, make short or long term predictions. The experimental results confirm that the proposed framework can be beneficial for intelligent diagnostic and prognostic systems related to battery as well as other wide range of applications. The main focus of the paper is the development of an integrated imputation-prediction scheme and not the evaluation of individual performances of the imputation or prediction techniques.
Highly homogeneous coatings several microns in thickness were prepared by electrophoretic deposition (EPD) from suspensions of a well-crystallized spinel of nominal composition LiNi0.5Mn1.5O4 mixed with 10% carbon black. The best dispersing conditions were found to be those provided by acetone containing citric acid and polyethyleneimine as dispersing agents; this combination resulted in increased mobility of particles and improved adherence to the substrate. These experimental conditions favored deposition of the smallest particles, thereby increasing coating uniformity. The as-prepared coatings were used as electrodes in lithium cells and found to provide virtually no electrochemical response owing to the lack of interparticle connectivity. This problem was easily overcome by compressing the coatings. Thus, coatings compressed at 517MPa resulted in cell performance on a par with that of the cell made from the bulk spinel. Moreover, their small particle size facilitates lithium-ion diffusion and the deposits exhibit good rate capabilities and coulombic efficiencies.
Systems of linear poly(ethylenimine), LPEI, with dissolved LiCF3SO3 and NaCF3SO3 have been studied using Raman and infrared spectroscopy. As the salt concentration is increased in the LPEI–LiCF3SO3 system, in turn “free” ions, contact ion pairs and the triple cation [Li2CF3SO3]+ each become the dominant species present, whereas contact ion pairs appear to be the dominant ionic species over the same composition range in the LPEI–NaCF3SO3 system. One of the major effects of adding salts to LPEI is the breaking of hydrogen bonds in the host polymer. As the salt concentration is increased in both systems, a somewhat abrupt onset of band broadening and widespread loss of band structure is observed.
A appropriate size with three-dimension (3D) channels for lithium diffusion plays an important role in constructing high-performing LiNi0.5Mn1.5O4 (LNMO) cathode materials, as it can not only reduce the transport path of lithium ions and electrons, but also reduce the side effects and withstand the structural strain in the process of repetitive Li+ intercalation/deintercalation. In this work, an efficient method for designing the hollow LNMO microsphere with 3D channels structure by using polyethylene oxide (PEO) as soft template agent assisted solvothermal method is proposed. Experimental results indicate that PEO can make the reagents mingle evenly and nucleate slowly in the solvothermal process, thus obtaining a homogeneous distribution of carbonate precursors. In the final LNMO products, the hollow 3D channels structure obtained by the decomposition of PEO and carbonate precursor in the calcination can provide abundant electroactive zones and electron/ion transport paths during the charge/discharge process, which benefits to improve the cycling performance and rate capability. The LNMO prepared by adding 1 g PEO possesses the most outstanding electrochemical performance, which presented an excellent discharge capacity of 143.1 mAh g−1 at 0.1 C and with a capacity retention of 92.2% after 100 cycles at 1 C. The superior performance attributed to the 3D channels structure of hollow microspheres, which provide uninterrupted conductive systems and therefore achieve the stable transfer for electron/ion.
Di-urea cross-linked POE/siloxane hybrid ormolytes (di-ureasils) doped with a wide concentration range of lithium perchlorate trihydrate (LiClO4·3H2O) (200≥ n ≥0.5, where n expresses the salt content in terms of the number of ether oxygen atoms per Li+ ion) have been analysed by Fourier transform infrared and Raman (FT-IR and FT-Raman, respectively) spectroscopies and X-ray diffraction (XRD). The results obtained lead us to conclude that the xerogels with n ≥5 are totally amorphous. At n ≤1 free salt is observed. “Free” ClO4 − ions appear to be the main charge carriers at the conductivity maximum located within the 25≤ n ≤8 composition range of this family of ormolytes. At n =15 ClO4 − ions coordinated in mono/tridentate (C3v symmetry) and bidentate (C2v symmetry) configurations were detected. In salt-rich samples with n <15 there is a marked tendency for ionic association. The resulting decrease that occurs in the concentration of “free” ions is consistent with the observed significant decrease of the ionic conductivity. The analysis of the “amide I” and “amide II” regions provided solid proof that the Li+ ions bond to the urea carbonyl oxygen atoms over the entire range of salt concentration studied.
Umicore has selected a site in Nysa, Poland, to build a plant to make cathode materials for the European automotive market. The first phase of this investment is included in a €660 million program announced earlier in 2018 and is due to start deliveries in late 2020. Nysa is reportedly near the company’s European customers and will give access to a workforce as well as low-carbon electricity supply. The first phase is expected to create up to 400 jobs. Umicore also plans to build a process competence center at its existing site in Olen, Belgium. The center is expected to be commissioned in late 2019 and will be employing around 20 researchers. ‘Both decisions are major milestones for Umicore and will significantly contribute to the European Union’s initiative to promulgate a leading rechargeable battery industry based on innovative technologies and a sustainable supply chain,’ said Marc Grynberg, CEO of Umicore. Umicore;www.umicore.com
Poor cycling performance and rate capability are the major barriers to the application of layered transition-metal sulfide as the next generation anodes materials for lithium-ion batteries (LIBs). In this paper, a smart composite consisting of defect-rich MoS2/carbon-coated ultrathin TiO2/defect-rich MoS2 sandwich-like nanosheets has been constructed to enhance the cycling and rate performances of MoS2. In this uniform sandwich-like structure, carbon-coated ultrathin TiO2 is conformably embedded by defect-rich MoS2 shells via intimate interfacial contacts, while the carbon coats TiO2 via Ti–O–C bonds. It is first revealed that the synergistic effect between rich defect in few-layer MoS2 nanosheets and abundant interfaces in the composites, as well as the high structure stability of TiO2 during discharge and charge process, results in excellent performance of the composites as LIBs anode materials. These LIBs anodes achieve the best rate capability (785.9, 507.6 and 792.3mAhg−1 at 0.1, 2 and 0.1Ag−1, respectively) and cycling performance (805.3mAhg−1 at 0.1Ag−1 after 100 cycles) among the TiO2 supported MoS2 based composites reported previous. The synergistic strategy can be expected to benefit the rational design of other anode materials for high-performance LIBs.