Search

Secondary growth is a key characteristic of trees, which requires the coordination of multiple regulatory mechanisms including transcriptional regulators and microRNAs (miRNAs). However, the roles of microRNAs in the regulation of secondary growth need to be explored in depth. Here, the role of miR319a and its target, PtoTCP20, in the secondary growth of Populus tomentosa stem was investigated using genetic and molecular analyses. The expression level of miR319a gradually decreased from primary to secondary growth in P. tomentosa, while that of PtoTCP20 gradually increased. MiR319a overexpression in seedlings resulted in delayed secondary growth and decreased xylem production, while miR319a knockdown and PtoTCP20 overexpression promoted secondary growth and increased xylem production. Further analysis showed that PtoTCP20 interacted with PtoWOX4a and activated PtoWND6 transcription in vitro and in vivo. Our data show that PtoTCP20 controls vascular cambium proliferation by binding to PtoWOX4a, and promotes secondary xylem differentiation by activating PtoWND6 transcription, thereby regulating secondary growth in P. tomentosa. Our findings provide insight into the molecular mechanisms underlying secondary growth in trees.

Trichomes are specialized epidermal cells that contribute to plant resistance against herbivores. Their formation is controlled precisely by multiple genetic and environmental signals. Previous studies have shown that microRNA319 (miR319) and gibberellin (GA) signaling are involved in trichome development in Arabidopsis, but little is known about their interaction between these factors. Here we reported that the miR319a/TEOSINTE BRANCHED/CYCLOIDEA/PCF (TCP) module participates in trichome initiation synergistically with GA signaling in Populus tomentosa. We demonstrated that overexpression of miR319a decreased transcription levels of its targeted TCPs and significantly elevated leaf trichome density in transgenic poplar, resulting in decreasing insect herbivory. Conversely, repressing miR319a by short tandem target mimics (STTM) elevated TCP expression levels and decreased trichome density in transgenic plants. The trichome phenotype of 35S:miR319a plants could be abolished by introducing a miR319a-resistant form of TCP19. Furthermore, the miR319a-targeted TCP19 interacted directly with REPRESSOR OF ga1-3 (RGA), a downstream repressor of GA signaling. TCP19 and RGA synergistically inhibited the GLABROUS1 (GL1)-induced expression of trichome marker gene GLABRA2 (GL2), thereby repressing leaf trichome initiation. Our results provide an insight into the molecular mechanism by which miR319/TCP19 module and GA signaling coordinated regulating trichome initiation in P. tomentosa.

Ferulate 5-hydroxylase (F5H) is a limiting enzyme involved in biosynthesizing sinapyl (S) monolignol in angiosperms. Genetic regulation of F5H can influence S monolignol synthesis and therefore improve saccharification efficiency and biofuel production. To date, little is known about whether F5H is post-transcriptionally regulated by endogenous microRNAs (miRNAs) in woody plants. Here, we report that a microRNA, miR6443, specifically regulates S lignin biosynthesis during stem development in Populus tomentosa. In situ hybridization showed that miR6443 is preferentially expressed in vascular tissues. We further identified that F5H2 is the direct target of miR6443. Overexpression of miR6443 decreased the transcript level of F5H2 in transgenic plants, resulting in a significant reduction in S lignin content. Conversely, reduced miR6443 expression by short tandem target mimics (STTM) elevated F5H2 transcripts, therefore increasing S lignin composition. Introduction of a miR6443-resistant form of F5H2 into miR6443-overexpression plants restored lignin ectopic composition, supporting that miR6443 specifically regulated S lignin biosynthesis by repressing F5H2 in P. tomentosa. Furthermore, saccharification assays revealed decreased hexose yields by 7.5-24.5% in miR6443-overexpression plants compared with the wild-type control, and increased hexoses yields by 13.2-14.6% in STTM6443-overexpression plants. Collectively, we demonstrate that miR6443 modulates S lignin biosynthesis by specially regulating F5H2 in P. tomentosa.

Lithium-ion (Li-ion) cells degrade after repeated cycling and the cell capacity fades while its resistance increases. Degradation of Li-ion cells is caused by a variety of physical and chemical mechanisms and it is strongly influenced by factors including the electrode materials used, the working conditions and the battery temperature. At present, charging voltage curve analysis methods are widely used in studies of battery characteristics and the constant current charging voltage curves can be used to analyze battery aging mechanisms and estimate a battery’s state of health (SOH) via methods such as incremental capacity (IC) analysis. In this paper, a method to fit and analyze the charging voltage curve based on a neural network is proposed and is compared to the existing point counting method and the polynomial curve fitting method. The neuron parameters of the trained neural network model are used to analyze the battery capacity relative to the phase change reactions that occur inside the batteries. This method is suitable for different types of batteries and could be used in battery management systems for online battery modeling, analysis and diagnosis.

To realize the high-power density of the proton exchange membrane fuel cell (PEMFC), it is important to explain the influence of liquid water on cell voltage quantitatively, which is still not fully understood yet. This paper proposes a study on polarization decomposing of PEMFC considering effect of liquid water accumulation. The voltage model starts from oxygen transport resistance, which is described as the summation of molecular diffusion resistance, Knudsen diffusion resistance, and transport resistance in the ionomer of the catalyst layer. Then the concentration polarization on the cathodic side of the MEA is described using oxygen transport resistance and liquid water saturation ratio based on Fick’s law. Equations for the influences of liquid water saturation ratio on activation and concentration polarization are deduced mathematically. Based on the model and experiments, a comprehensive polarization decomposition method is proposed. Using this method, cell polarization can be decomposed in detail, and the liquid water saturation ratio under various operation conditions can also be estimated. This work can also be applied to the improvement of fuel cell performance and the evaluation of water content within fuel cells.

Background: Colic is a common condition in infants Bifidobacterium longum CECT7894 (KABP042) and Pediococcus pentosaceus CECT8330 (KABP041) mix (1 × 109 colony forming units) would improve the symptoms of infantile colic.Methods: A total of 112 exclusively breastfed or mixed fed infants aged n = 48) or placebo (placebo group, PG, n = 42) daily for 21 days.Results: Infants in the IG had significantly shorter crying time (p < 0.001) on day 7 [IG vs. PG, median (25−75th percentile): 38 (3.5–40.5) vs. 62 (40–108) min/day], day 14 [IG vs. PG: 20 (0–40) vs. 50 (30–75) min/day], and day 21 [IG vs. PG: 14 (0–33) vs. 40 (28–62) min/day]. Higher responder ratio and fewer crying/fussing episodes on days 7, 14, and 21 and better stool consistency on day 21 were observed in the IG (p < 0.01) as compared to the PG. Conversely, no significant effects on stool frequency or quality of life were observed.Conclusions: In summary, daily oral administration of B. longum CECT7894 (KABP042) and P. pentosaceus CECT8330 (KABP041) was an effective treatment for shortening crying time due to infantile colic and for improving fecal consistency. This trial was registered retrospectively in December 2019 with a trial number of ISRCTN92431452.

Battery electric buses (BEBs) play a very important role of reducing urban tailpipe emissions in transportation sector for China. The national strong incentive policies place China at the forefront of the BEBs' market in the world. However, challenges are even more severe owing to the negative effects of national subsidies on the BEBs industry and technologies’ option. The abovementioned problems indicate that the subsidy mechanism is not scientific and systematic. Therefore, this research focus on the comprehensive evaluating method of addressing the inner influencing principle of technological specification mentioned in new subsidy scheme on the technological development direction of BEBs. The evaluation indicators in the method include cost-benefit and electricity consumption rate and for different size BEBs. The scenario of maximum subsidy obtaining target based on the optimal install battery estimation is set up; then, the potential direction of the BEBs market penetration was investigated. The cost-benefit and energy consumption estimating models are set up to examine the economics of all size BEBs and the difference between BEBs and equivalent conventional bus. Furthermore, the potential positive and negative effects of the technological requirements in the subsidy scheme are investigated The results show that normal-charging BEBs, the market for light-duty BEBs will shrink greatly owing to significant reduction in the subsidy amounts. However, the market penetration of 12 m BEB will increase significantly. LFP batteries will dominate the normal-charging heavy-duty BEB market in near and medium term, but NCM–type traction batteries will gradually be dominating the energy storage market for normal-charging BEBs owing to increasing demands in terms of the energy density of traction batteries. However, the market penetration of fast-charging-type BEBs will growth more rapidly than ever before due to the great increasing in its cost-benefit.

Micro-short-circuit (MSC) is a latent risk in power batteries, which may give rise to thermal runaway and even catastrophic safety hazards. The motivation of this paper is to quantitatively analyze MSC in an initial stage, particularly for lithium-ion batteries. To verify the feasibility of the proposed method, an equivalent MSC experiment is carried out. Based on a cell difference model, the cell state of charge (SOC) differences with the mean SOC for a battery pack are estimated by extended Kalman filter. The evaluated SOC difference can track the actual value well. Furthermore, an MSC diagnostic method is developed by employing recursive least squares filter. The method is demonstrated to examine the short-circuit resistance accurately. The results also show that the proposed method requires low computational load for the SOC difference and short-circuit resistance diagnosis.

A 2D PEMFC model has been built to simulate the current density distribution and liquid water distribution in cathode. In this simulation, the air mass flow rate, relative humidity of the air and cell voltage are considered as the input parameters into the model, the diagram of current density and liquid water distribution in cathode are shown according to the simulation result and compared to each other. The result indicates that the liquid water distribution has a strong positive relation to the current density, where water drops diffuse mainly by the pressure difference (capillary force) in the porous media (the porous media coefficient ep is very low), where the shear force of the air can hardly drive the water drops due to the high friction force of the porous media. In the thin porous media (the porous media coefficient ep is relatively high), the purge effect of the air flow can be enhanced, decreasing the flooding areas in the cathode. Due to the purge effect of the air flow, the outlet of the cathode is the critical areas, where the flooding is most likely to happen. The steep trough at the current density distribution may mean the local flooding, which blocks the oxygen and weaken the chemical reaction.

Overcharge is one of the most severe safety issues of lithium-ion batteries. In this paper, the overcharge performance of a commercial lithium-ion battery is evaluated under different test conditions, considering the effects of charging current, restraining plate and heat dissipation. Charging current and heat dissipation are found to have only minor influence on the battery overcharge behaviors, while batteries with restraining plate and cuts on the pouches show improved overcharge performance, as SOCTR and TTR both increase significantly. Further analysis on TTR helps to identify the overcharge-induced thermal runaway mechanism for the batteries with different configurations.

The non-uniform internal status in one cell and the inconsistency between cells have significant impact on the performance and service life of commercial fuel cell stack. The identification of this phenomenon with in-situ method is the key technology for product development and optimization. This paper presents the corresponding analysis and a practical in-situ method, i.e., the multipoint voltage-monitoring method, to identify the fuel cell stack uniformity and consistency. Cross plate current and voltage variation in bipolar plate can be therefore observed using the proposed method. In addition, an one-dimensional model has been developed to explain this phenomenon. A variable loading rate experiment has been conducted in a four-cell stack to explore the relationship between consistency and uniformity in multi-cell stack. When the loading rate increases from 20 mA/cm2·s to 40 mA/cm2·s, the current concentrating in the cathode outlet also increases. Current non-uniformity is caused by gas distribution inconsistency between cells, which makes cell1 drier than the other cells. Voltage difference between the two monitors of cell1 is about 32mV, and it can be even larger in extreme conditions, like fuel starvation. It means the health condition estimation of fuel cell stack can be easily misdirected, when monitor is placed on different position. Experimental and simulation results show that the multipoint voltage monitoring method can avoid the ‘voltage cheat’ and therefore achieve the real consistency and uniformity performance.

Due to the prominent advantages of low cost and efficient utilization, cemented hemihydrate phosphogypsum (HPG) backfill is becoming popular in mine goaf treatments in China as a new promising branch of cemented paste backfill (CPB). The HPG gelling activity time dependence determines its role in CPB, that is, whether it is used as a cementitious material or aggregate. Laboratory and field experiments showed that the HPG gelling activity decreases with an increasing aging time due to the gradual HPG conversion from the hemihydrate to the dihydrate form. The HPG conversion can be described by the Avrami equation, and further divided into acceleratory and slow reaction periods. Soluble P

A dead-ended anode (DEA) has advantages such as simple structure, high reliability, and low price, and is widely utilized in polymer electrolyte membrane fuel cell (PEMFC) systems. Empirical parameters are commonly adopted in control-oriented models for such systems, and detailed information about mass transport processes is usually not available. Such models are neither helpful for understanding the internal processes within fuel cells, nor for designing control algorithms to improve system performance. A control-oriented model considering the mass transport processes and actuator properties is still lacking. This paper proposes a nonlinear dynamic mechanism model for the DEA system that can describe the dynamic voltage drop during water flooding with a large current density. The properties of the major components are explained in details, and the procedure of how the purging valves affects the mass transport and cell voltage is revealed quantitatively. The relationship between the minimum cell voltage and purging operations is summarized. The results show that (1) the proposed model can capture the stable and dynamic properties of a fuel cell with a DEA, (2) the cell voltage loss during closing of the purging valve is mainly caused by a decrease in oxygen and hydrogen partial pressures on the catalyst layers and an increase in the liquid water saturation ratio in the gas diffusion layers (GDLs); (3) the most important internal states that affect the stack voltage during purging is the liquid water saturation ratio in the GDLs.

Thermal runaway (TR) is a major safety concern in lithium-ion batteries. Model-based TR prediction is critically needed to optimize safety designs of cells. This paper presents a novel scheme for developing reliable battery TR model from kinetics analysis of cell components. First, differential scanning calorimetry (DSC) tests on the individual cell components and their mixtures are conducted to reveal the TR mechanism and characterize the exothermic reactions, of which the major six (such as the decomposition of solid electrolyte interface (SEI) film) are determined as the dominant heat sources. The kinetics parameters of each exothermic reactions are identified from the DSC tests results at variant heating rates using Kissinger’s method and nonlinear fitting method. A predictive battery TR model is established by superimposing the chemical kinetics equations of the six exothermic reactions. The model fits well with the adiabatic TR test results and the oven tests results of a 24 Ah lithium-ion battery, indicating that the model can well reflect the battery TR mechanism and be trusted to predict battery safety performance without assembling a real battery.

This paper presents a performance analysis of plug-in hybrid electric vehicles (PHEVs) considering battery preheating economy under low temperature conditions. In subzero temperature environments, PHEVs suffer a dramatic loss of all-electric driving range due to the energy and power reduction of LiFePO4 batteries, as well as severe battery degradation due to lithium ion plating. This decreases the battery life time and thus increases the operating cost of the PHEV. A quasi-static model is adopted for the simulated bus, and a battery dynamic degradation model is established based on the Arrhenius degradation theory. The PHEV performance under low-temperature conditions is evaluated considering three factors: fuel cost, electricity cost, and battery degradation cost. In addition, the economics of battery preheating powered by the engine or grid is first investigated in this paper. The charge depleting-charge sustaining energy management strategy and convective heating method are adopted. Simulation results show that the preheating strategy can reduce the PHEV operating cost by up to 22.3% in 40 Harbin driving cycles. The heating process becomes increasingly necessary as the battery price, heating efficiency, and daily recharging time of the PHEV increase as well as the environment temperature decreases.

Summary We demonstrate herein that not only internal short circuiting, but also chemical crossover, is the mechanism behind thermal runaway that can occur in lithium-ion batteries due to abuse conditions. In situ experiments showed that during thermal runaway, the cathode releases oxygen by a phase transition, and this oxygen is consumed by the lithiated anode. The released highly oxidative gas reacts with reductive LiCx with tremendous heat generation centered at 274.2°C with heat flow of 87.8 W g−1. To confirm the proposed mechanism, we froze a battery undergoing the thermal runaway process by liquid nitrogen and subjected it to detailed post-test analysis. Our results revealed the hidden thermal runaway mechanism of chemical crossover between the battery components without a severe internal short circuit. These findings provide an important insight into the rational design of automotive lithium-ion batteries as well as solid-state batteries.

Flood forecasting has been an effective way to reduce the potential flood hazards for a sustainable socio-economy. However, the lack of in-situ precipitation records has limited the applicability of flood forecasting with hydrologic models in poorly gauged basins. To address this problem, we aim to develop a flood forecasting framework based on the merged satellite precipitation and a hydrologic model. The framework was then applied to a small basin in the upper Lequan River Basin, Hainan, China for flood forecasting experiments. Results indicate that the combination of merged satellite precipitation and hydrologic model can generally well reproduce the past major flood events occurred in the basin. Our approaches are expected to provide new insights into the flood forecasting in small and poorly gauged basins and can be used to support the sustainable development of the socio-economy.

9 pages, 3 figures, 2 tables, With the development of modern technologies, the exploitation and application of rare earth metals (REMs) have increased parallelly. Consequently, more REMs are entering into the environment and therefore there is a pressing need to assess their potential environmental hazards. Here, a standard toxicity test with wheat (Triticum aestivum) was conducted to investigate the single and mixture toxicity of La and Ce in solutions with different levels of calcium and nitrilotriacetic acid (NTA) and results were deciphered by different modeling approaches. Both La and Ce caused adverse effect to wheat, but the presence of Ca and NTA alleviated their toxicity. The obtained EC50 for [La] or [Ce] changed by more than 28-fold and by 4-fold, respectively, with the increase of Ca or NTA. The biotic ligand model (BLM) explained approximately 93% variation of single La or Ce toxicity. The binding constants obtained were 4.14, 6.67, and 6.59 for logKCaBL, logKLaBL, and logKCeBL respectively. The electrostatic toxicity model (ETM) was proved as effective as the BLM, with R2 = 0.93 for La and R2 = 0.92 for Ce. For La–Ce mixtures, parameters from single toxicity approaches were applied successfully to predict the mixture toxicity with concentration addition (CA) model based on the BLM or ETM theory (R2 = 0.92 and RMSE = 8.56; R2 = 0.90 and RMSE = 9.6, respectively). Thus, the results obtained in this study prove that both ETM and BLM theories are appropriate to predict single and mixture REMs toxicity, providing coherent and promising tools for the risk assessment of REM pollution, This study was supported by the Key Laboratory of Original Agro-Environmental Pollution Prevention and Control, Ministry of Agriculture and Rural Affairs/Tianjin Key Laboratory of Agro-Environment and Agro-Product Safety, Agro-Environment Protection Institution, Ministry of Agriculture and Rural Affairs (No. 17Z1170010019), the National Natural Science Foundation of China (No. 41701573, No. 41701571, No. 41877500, and No. 41977115), the National Key R&D Program of China (No. 2018YFC1800600, No. 2018YFD0800700), and the Research Fund Program of Guangdong Provincial Key Laboratory of Environmental Pollution Control and Remediation Technology (No. 2018K01

Model-based observers are widely applied in state-of-charge (SOC) estimation. The existing model-based observers can achieve high precision in theory, but the estimation precision is influenced by many factors in practical application. The impact of the possible error sources on the SOC estimation needs to be clarified in order to enhance the practical estimation accuracy. In this paper, the effect of five error sources in the model-based SOC observer is analyzed, including the initial error, the capacity error, the current measurement error, the voltage measurement error, and the model prediction error. Both theoretical derivation and simulation analysis are implemented. The results show that the initial SOC error converges to zero during the iteration, while the errors of the capacity, current, voltage, and model cause the SOC estimation error in different extents. Quantitative comparisons of these different error sources are carried out in order to determine the critical factors of the SOC estimation. The SOC estimation accuracy is mainly limited by the model precision under the current hardware and software conditions of the battery management system, indicating a possible improving direction of the SOC estimation.

Micro-short circuit (MSC) of a lithium-ion battery cell is a potential safety hazard for battery packs. How to identify the cell with MSC in the latent phase before a thermal runaway becomes a difficult problem to solve. We propose a diagnosis method to detect the MSC according to the remaining charging capacity (RCC) variations between cells. When the charging cell voltage curve (CCVC) of the first fully charged cell is regarded as the benchmark, the RCC of each cell can be obtained by the CCVC transformation based on the uniform CCVC hypothesis. The accuracy of the RCC estimation method is validated under constant current and constant power charging experiments. The leakage current of the MSC cell can be obtained by the increase of the RCC after each charge, and it can be converted into the MSC resistance. We set up the battery pack system model with the MSC fault in Simulink® to verify the effectiveness of the method when the battery pack is charged up to different charge cutoff voltages. Through a series of experiments with external resistors, the adaptability of the MSC diagnosis method is further validated for the aged cell, multi-stage charging, and constant power charging.

In a fuel cell vehicle, a direct current boost converter (DCC) is required to link a polymer electrolyte membrane fuel cell system (FCS) and lithium battery packages. The DCC is installed to regulate the output power of the FCS, and can be controlled in different ways, via current, voltage, or power modes. Interactions between a DCC and FCS have attracted growing interests in recent years, because they affect dynamic and stable performances of the entire system. This paper outlines a simulation study on interactions between high-frequency switching operations of a DCC and internal states of an FCS based on a multiscale model. Results are as follows. (1) High-frequency switching operations have a major influence on the cathode overpotential, voltage ohmic loss and water transport through the membrane, whereas the influence on the partial pressures of gas species inside the stack is slight. (2) The FCS is more stable in the case of membrane dehydration than in that of water flooding. DCC's control mode has a greater influence on the FCS when water flooding occurs than membrane dehydration. The power control mode is the most unstable of the three, whereas the current control mode is the most stable.

Sate of charge (SOC) estimation is generally acknowledged as one of the most important functions in battery management system for lithium-ion batteries in new energy vehicles. Though every effort is made for various online SOC estimation methods to reliably increase the estimation accuracy as much as possible within the limited on-chip resources, little literature discusses the error sources for those SOC estimation methods. This paper firstly reviews the commonly studied SOC estimation methods from a conventional classification. A novel perspective focusing on the error analysis of the SOC estimation methods is proposed. SOC estimation methods are analyzed from the views of the measured values, models, algorithms and state parameters. Subsequently, the error flow charts are proposed to analyze the error sources from the signal measurement to the models and algorithms for the widely used online SOC estimation methods in new energy vehicles. Finally, with the consideration of the working conditions, choosing more reliable and applicable SOC estimation methods is discussed, and the future development of the promising online SOC estimation methods is suggested.

City buses using polymer electrolyte membrane (PEM) fuel cells are considered to be the most likely fuel cell vehicles to be commercialized in China. The technical specifications of the fuel cell systems (FCSs) these buses are equipped with will differ based on the powertrain configurations and vehicle control strategies, but can generally be classified into the power-follow and soft-run modes. Each mode imposes different levels of electrochemical stress on the fuel cells. Evaluating the aging behavior of fuel cell stacks under the conditions encountered in fuel cell buses requires new durability test protocols based on statistical results obtained during actual driving tests. In this study, we propose a systematic design method for fuel cell durability test protocols that correspond to the power-follow mode based on three parameters for different fuel cell load ranges. The powertrain configurations and control strategy are described herein, followed by a presentation of the statistical data for the duty cycles of FCSs in one city bus in the demonstration project. Assessment protocols are presented based on the statistical results using mathematical optimization methods, and are compared to existing protocols with respect to common factors, such as time at open circuit voltage and root-mean-square power.

Cyclic voltammetry and linear sweep voltammetry are the most commonly used diagnosis methods to estimate the internal statement of fuel cell stack. However, both methods can only be applied in a single fuel cell. There is a lack of suitable in situ diagnosis methods for a multi-burl fuel cell stack. The galvanostatic charge method (GSC) is a very convenient in situ diagnosis method, which can be applied to a multi-burl fuel cell stack to calculate the electrochemical active surface area (ECSA), double-layer capacitance, and hydrogen crossover current. However, there are not enough experiments to analyze the adaption of GSC or apply this method to analyze fuel cell degradation process. In this study, we conducted experiments to validate the accuracy of GSC under different test conditions, and proposed a new correction algorithm to improve the accuracy. Next, this method was applied to analyze the performance degradation process of a four-cell stack. The experimental results showed that the estimated GSC parameters exactly coincide with the standard values. Additionally, for the degradation analysis of a four-cell stack, the GSC results showed that the ECSA reduction of cell four is the direct reason for performance degradation. Moreover, the assumptions of ECSA reduction and carbon corrosion were validated by material experiments. About 5° decrease in the contact angle of the gas diffusion layer (GDL) in the cathode catalyst was observed in the worst cell.

This paper proposes a co-estimation scheme of state of charge (SOC), state of health (SOH), and state of function (SOF) for lithium-ion batteries in electric vehicles. The co-estimation denotes that the SOC, SOH, and SOF are estimated simultaneously in real-time application. The model-based SOC estimation is fulfilled by the extended Kalman filter. The battery parameters related with the battery SOH and SOF are online identified using the recursive least square algorithm with a forgetting factor. The capacity and the maximum available output power are then estimated based on the identified parameters. The online update of the capacity and correlated parameters help improve the accuracy of the state estimation but with limited increase in the computation load, by making good use of the correlations among the states. The co-estimation scheme is validated in a real battery management system with good real-time performance and convincible estimation accuracy.

The utilization of multiple independently controlled electric wheels offers possibilities for enhancing not only the vehicle stability control but also energy efficiency of a vehicle. Previous research on energy-efficient torque allocation mainly focuses on four-wheel-independent-drive vehicles but not multi-axle all-wheel-drive vehicles. In this paper, we propose an energy-efficient torque-allocation strategy for a vehicle equipped with six identical electric wheels, using the Karush–Kuhn–Tucker (KKT) conditions to find candidates for globally optimal solutions. We present and compare the analytical forms of these candidates, including typical modes such as single-wheel-drive, two-wheel even-distribution, and three-wheel even-distribution modes. It shows that reallocating torques other than even distribution has energy-saving effects when the power loss characteristics of an electric wheel are not convex. For the studied electric wheel, the optimal mode revealed by KKT conditions is to progressively increase the number of active wheels with the torque demand. This method can be employed regardless of whether the power loss characteristics with respect to the torque demand are convex or nonconvex. The KKT conditions also allow the establishment of an online rule-based strategy to switch between different modes, depending on the vehicle speed and torque demand. Examples based on the electric wheel's power loss characteristics validate the effectiveness of the KKT-based allocation strategy. Compared with an even-distribution strategy, the electric wheels' energy losses and the vehicle's energy consumption can be reduced by 12.5% and 3.7%, respectively, over a complete driving cycle using the KKT-based strategy.

It is an essential issue that fast charging of lithium ion battery which is restricted by lithium deposition. The aim of this research is to provide an optimal charge current of lithium ion battery, by which the theoretically fastest charging speed without lithium deposition is able to be reached. In other words, a maximal acceptable charge current of lithium ion battery is proposed. The expression of the charge curve is derived mathematically according to the lithium deposition criterion and validated by an electrochemical model. The charge current is found highly related with the anode equilibrium potential Un, as well as the charge transfer resistance Rct which is a critical parameter. Lower Rct can accommodate higher acceptable charge current amplitude, indicating that better charge capability of the battery. For real applications, the charge current can be easily derived from this method and directly used to charge the lithium ion battery in electric vehicles.

Fast charging is critical for the application of lithium-ion batteries in electric vehicles. Conventional fast charging algorithms may shorten the cycle life of lithium-ion batteries and induce safety problems, such as internal short circuit caused by lithium deposition at the negative electrode. In this paper, a novel, non-destructive model-based fast charging algorithm is proposed. The fast charging algorithm is composed of two closed loops. The first loop includes an anode over-potential observer that can observe the status of lithium deposition online, whereas the second loop includes a feedback structure that can modify the current based on the observed status of lithium deposition. The charging algorithm enhances the charging current to maintain the observed anode over-potential near the preset threshold potential. Therefore, the fast charging algorithm can decrease the charging time while protecting the health of the battery. The fast charging algorithm is validated on a commercial large-format nickel cobalt manganese/graphite cell. The results showed that 96.8% of the battery capacity can be charged within 52 min. The post-mortem observation of the surface of the negative electrode and degradation tests revealed that the fast charging algorithm proposed here protected the battery from lithium deposition.

This paper presents an electrochemical-thermal coupled overcharge-to-thermal-runaway (TR) model to predict the highly interactive electrochemical and thermal behaviors of lithium ion battery under the overcharge conditions. In this model, the battery voltage equals the difference between the cathode potential and the anode potential, whereas the temperature is predicted by modeling the combined heat generations, including joule heat, thermal runaway reactions and internal short circuit. The model can fit well with the adiabatic overcharge tests results at 0.33C, 0.5C and 1C, indicating a good capture of the overcharge-to-TR mechanism. The modeling analysis based on the validated model helps to quantify the heat generation rates of each heat sources during the overcharge-to-TR process. And the two thermal runaway reactions including the electrolyte oxidation reaction and the reaction between deposited lithium and electrolyte are found to contribute most to the heat generations during the overcharge process. Further modeling analysis on the critical parameters is performed to find possible solutions for the overcharge problem of lithium ion battery. The result shows that increasing the oxidation potential of the electrolyte, and increasing the onset temperature of thermal runaway are the two effective ways to improve the overcharge performance of lithium ion battery.

High frequency resistance (HFR) has become the most important input signal for the on-board water management of polymer electrolyte membrane fuel cell (PEMFC) vehicles in practical applications, due to its close physical relation to the membrane water content. However, according to our latest experimental result, the paradox arises that HFR reaches a steady state regardless of continuous reduction in membrane water content, in other words, the pseudo-steady state of HFR is achieved. To investigate the triggering mechanism, for the first time, we combine current mapping technique with image difference technique to observe dynamic evolution of current in-plane distribution, and, furthermore, to analyze membrane water distribution. We can demonstrate that, the heterogeneity of membrane water in-plane distribution triggers the pseudo-steady HFR, and it can be distinguished by the distributed monitoring, to avoid the potential failure of water management.

For fuel cell research, fuel economy evaluation methods for fuel cell systems are the basic tools; however, current fuel economy evaluation methods do not meet the demand for comprehensive analyses of the economy of fuel cell systems. In this study, we propose an all-condition economy evaluation method for fuel cell systems. To estimate the all-condition state of fuel cell systems, we developed a 1-D water transport model and an air compressor model for all operating conditions. Inspired by the knowledge of internal combustion engines, we developed an innovative fuel cell system efficiency contour map for evaluating all operating conditions. This method decouples the economy evaluation from test operating conditions and control strategy and demonstrates the fundamental characteristics of fuel cell systems. Based on the fuel cell system efficiency contour map, we propose an optimized control strategy for fuel cell hybrid vehicles, which reduces fuel consumption by 1.45%–13.14%.

The transient water transport problem within polymer electrolyte membrane fuel cell (PEMFC) makes its dynamic behavior unpredictable occasionally, bringing uncertainties to the water management. In this work, a novel experimental methodology is proposed, where the dynamic processes of gas diffusion layer (GDL) imbibition-drainage are accomplished by galvanostatic discharge and alterable air feeding, meanwhile, the PEMFC voltage characteristic is measured as an external state to derive stoichiometry-voltage curve (λ-V curve). The other transient processes within PEMFC, including membrane sorption/desorption, catalyst surface covering/uncovering and gas channel blocking/unblocking, are also analyzed by high frequency resistance (HFR) measurement, air & oxygen feeding comparison, and pressure drop measurement, respectively. Taking a commercial PEMFC for example, the liquid water's transient capillary transport within GDL is found to dominate PEMFC's λ-V hysteresis under the condition of high humidification. For the first time, three cycles of GDL imbibition/drainage are in-situ accomplished on the PEMFC, demonstrating: (a) V(λ) during 1st imbibition is lower than V(λ) during 2nd and 3rd imbibition, which agree closely, implying ‘water pathways’ built after 1st imbibition improve PEMFC's performance. (b) V(λ) during drainage is always higher than V(λ) during imbibition, despite the steady-existing ‘water pathways’. (c) ‘Water pathways’ in GDL are established within 24 min.

A scheme for designing a second-order sliding-mode (SOSM) observer that estimates critical internal states on the cathode side of a polymer electrolyte membrane (PEM) fuel cell system is presented. A nonlinear, isothermal dynamic model for the cathode side and a membrane electrolyte assembly are first described. A nonlinear observer topology based on an SOSM algorithm is then introduced, and equations for the SOSM observer deduced. Online calculation of the inverse matrix produces numerical errors, so a modified matrix is introduced to eliminate the negative effects of these on the observer. The simulation results indicate that the SOSM observer performs well for the gas partial pressures and air stoichiometry. The estimation results follow the simulated values in the model with relative errors within ± 2% at stable status. Large errors occur during the fast dynamic processes (

One of the key battery performances which can be described as the resistance characteristic is the cell voltage response with dynamic currents, and it requires synchronous cell voltages and current. But due to inevitable network latency in modular battery management system (BMS) with controller area network (CAN), cell voltages and current are usually asynchronous. We firstly analyze the sampling and the storage process of battery signals to study the asynchronous mechanism in BMS. We develop an on-line synchronization method using a “global clock” from the master controller to decrease the time delay as much as possible. And we further propose a model based sync method based on the frequency division equivalent circuit model (FDECM) for the battery pack. The low frequency cell difference model is used to identify cell “resistances difference”, and then the optimal time compensation for cell voltages is obtained when the minimum mean absolute derivative (MAD) value of identified resistance differences is reached according to the low frequency characteristic of cell “resistances difference”. The proposed methods are verified by simulation and experiment. The current and cell voltages in the data logger of BMS can be synchronized when the optimal compensation time is applied respectively for each cell. The data after synchronization can meet the requirements of further data analysis and processing, which is of great significance to enhance and improve the control strategy of BMS.