Development of advanced anion exchange membrane from the view of the performance of water electrolysis cell

Green hydrogen produced by water electrolysis combined with renewable energy is a promising alternative to fossil fuels due to its high energy density with zero-carbon emissions.Among water electrolysis technologies,the anion exchange membrane(AEM) water electrolysis has gained intensive attention and is considered as the next-generation emerging technology due to its potential advantages,such as the use of low-cost non-noble metal catalysts,the relatively mature stack assembly process,etc.However,the AEM water electrolyzer is still in the early development stage of the kW-level stack,which is mainly attributed to severe performance decay caused by the core component,i.e.,AEM.Here,the review comprehensively presents the recent progress of advanced AEM from the view of the performance of water electrolysis cells.Herein,fundamental principles and critical components of AEM water electrolyzers are introduced,and work conditions of AEM water electrolyzers and AEM performance improvement strategies are discussed.The challenges and perspectives are also analyzed.

Recent advances and future prospects on Ni_(3)S_(2)-Based electrocatalysts for efficient alkaline water electrolysis

Green hydrogen(H_(2))produced by renewable energy powered alkaline water electrolysis is a promising alternative to fossil fuels due to its high energy density with zero-carbon emissions.However,efficient and economic H_(2) production by alkaline water electrolysis is hindered by the sluggish hydrogen evolution reaction(HER)and oxygen evolution reaction(OER).Therefore,it is imperative to design and fabricate high-active and low-cost non-precious metal catalysts to improve the HER and OER performance,which affects the energy efficiency of alkaline water electrolysis.Ni_(3)S_(2) with the heazlewoodite structure is a potential electrocatalyst with near-metal conductivity due to the Ni–Ni metal network.Here,the review comprehensively presents the recent progress of Ni_(3)S_(2)-based electrocatalysts for alkaline water electrocatalysis.Herein,the HER and OER mechanisms,performance evaluation criteria,preparation methods,and strategies for performance improvement of Ni_(3)S_(2)-based electrocatalysts are discussed.The challenges and perspectives are also analyzed.

Thermal safety boundary of lithium-ion battery at different state of charge

Thermal runaway(TR)is a critical issue hindering the large-scale application of lithium-ion batteries(LIBs).Understanding the thermal safety behavior of LIBs at the cell and module level under different state of charges(SOCs)has significant implications for reinforcing the thermal safety design of the lithium-ion battery module.This study first investigates the thermal safety boundary(TSB)correspondence at the cells and modules level under the guidance of a newly proposed concept,safe electric quantity boundary(SEQB).A reasonable thermal runaway propagation(TRP)judgment indicator,peak heat transfer power(PHTP),is proposed to predict whether TRP occurs.Moreover,a validated 3D model is used to quantitatively clarify the TSB at different SOCs from the perspective of PHTP,TR trigger temperature,SOC,and the full cycle life.Besides,three different TRP transfer modes are discovered.The interconversion relationship of three different TRP modes is investigated from the perspective of PHTP.This paper explores the TSB of LIBs under different SOCs at both cell and module levels for the first time,which has great significance in guiding the thermal safety design of battery systems.

Thermal characteristic evolution of lithium-ion batteries during the whole lifecycle

This work extensively investigates the thermal characteristic evolution of lithium-ion batteries under different degradation paths,and the evolution mechanism through multi-angle characterization is revealed.Under different degradation paths,the evolution trend of temperature rise rate remains unchanged with respect to depth of discharge during the adiabatic discharge process,albeit to varying degrees of alteration.The temperature rise rate changes significantly with aging during the adiabatic discharge process under low-temperature cycling and high-rate cycling paths.The total heat generation rate,irreversible heat generation rate,and reversible heat generation rate exhibit similar evolution behavior with aging under different degradation paths.The interval range of endothermic process of reversible electrochemical reactions increases and the contribution of irreversible heat to the total heat increases with aging.To further standardize the assessment of different degradation paths on the thermal characteristics,this work introduces the innovative concept of“Ampere-hour temperature rise”.In low-temperature cycling and high-rate cycling paths,the ampere-hour temperature rise increases significantly with aging,particularly accentuated with higher discharge rates.Conversely,in high-temperature cycling and high-temperature storage paths,the ampere-hour temperature rise remains relatively stable during the initial stages of aging,yet undergoes a notable increase in the later stages of aging.The multi-angle characterization reveals distinct thermal evolution behavior under different degradation paths primarily attributed to different behavior changes of severe side reactions,such as lithium plating.The findings provide crucial insights for the safe utilization and management of lithium–ion batteries throughout the whole lifecycle.

Research on the impact of high-temperature aging on the thermal safety of lithium-ion batteries

Understanding the thermal safety evolution of lithium-ion batteries during high-temperature usage conditions bears significant implications for enhancing the safety management of aging batteries.This work investigates the thermal safety evolution mechanism of lithium-ion batteries during high-temperature aging.Similarities arise in the thermal safety evolution and degradation mechanisms for lithium-ion batteries undergoing cyclic aging and calendar aging.Employing multi-angle characterization analysis,the intricate mechanism governing the thermal safety evolution of lithium-ion batteries during high-temperature aging is clarified.Specifically,lithium plating serves as the pivotal factor contributing to the reduction in the self-heating initial temperature.Additionally,the crystal structure of the cathode induced by the dissolution of transition metals and the reductive gas generated during aging attacking the crystal structure of the cathode lead to a decrease in thermal runaway triggering temperature.Furthermore,the loss of active materials and active lithium during aging contributes to a decline in both the maximum temperature and the maximum temperature rise rate,ultimately indicating a decrease in the thermal hazards of aging batteries.

An empirical model for high energy density lithium-(ion)batteries with ultra-thick electrodes

Increasing the electrode thickness is a significant method to decrease the weight and volume ratio of the inactive components for high energy density of the devices.In this contribution,we extracted a repeating unit in the configurations and establish the empirical energy density model based on some assumptions.In this model,the effects of the electrode thickness on the energy density for lithium-ion batteries(LIBs),lithium metal batteries(LMBs),and anode-free lithium batteries(ALBs)are evaluated quantitively with the current parameters of the batteries.The results demonstrate that the structure evolutions from LIBs,LMBs to ALBs with the reduction of the anode weight contribution,the energy density can be well improved exactly.While the increase of the thickness of the electrode provide another route to furthe r enhance the energydensity by decreasing the weight contribution of inactive materials;meanwhile the effects for ALBs are higher than LMBs and LIBs due to the higher weight ratio of inactive materials.This empirical energy density model is also applied into the practical system and provide intuitional results to guide the battery design for higher energy density.

Deep learning enhanced lithium-ion battery nonlinear fading prognosis

With the assistance of artificial intelligence,advanced health prognosis technique plays a critical role in the lithium-ion(Li-ion) batteries management system.However,conventional data-driven early aging prediction exhibited dramatic drawbacks,i.e.,volatile capacity nonlinear fading trajectories create obstacles to the accurate multistep ahead prediction due to the complex working conditions of batteries.Herein,a novel deep learning model is proposed to achieve a universal and accurate Li-ion battery aging prognosis.Two battery datasets with various electrode types and cycling conditions are developed to validate the proposed approaches.Knee-point probability(KPP),extracted from the capacity loss curve,is first proposed to detect knee points and improve state-of-health(SOH) predictive accuracy,especially during periods of rapid capacity decline.Using one-cycle data of partial raw voltage as the model input,the SOH and KPP can be simultaneously predicted at multistep ahead,whereas the conventional method showed worse accuracy.Furthermore,to explore the underlying characteristics among various degradation tendencies,an online model update strategy is developed by leveraging the adversarial adaptationinduced transfer learning technique.This work gains new sights into the comprehensive Li-ion battery management and prognosis framework through decomposing capacity degradation trajectories and adversarial learning on the unlabeled samples.

Dynamic friction modelling and parameter identification for electromagnetic valve actuator

A new modified LuGre friction model is presented for electromagnetic valve actuator system.The modification to the traditional LuGre friction model is made by adding an acceleration-dependent part and a nonlinear continuous switch function.The proposed new friction model solves the implementation problems with the traditional LuGre model at high speeds.An improved artificial fish swarm algorithm(IAFSA)method which combines the chaotic search and Gauss mutation operator into traditional artificial fish swarm algorithm is used to identify the parameters in the proposed modified LuGre friction model.The steady state response experiments and dynamic friction experiments are implemented to validate the effectiveness of IAFSA algorithm.The comparisons between the measured dynamic friction forces and the ones simulated with the established mathematic friction model at different frequencies and magnitudes demonstrate that the proposed modified LuGre friction model can give accurate simulation about the dynamic friction characteristics existing in the electromagnetic valve actuator system.The presented modelling and parameter identification methods are applicable for many other high-speed mechanical systems with friction.

Effects of thermal activation conditions on the microstructure regulation of corncob-derived activated carbon for hydrogen storage

Activated carbons derived from corncob （CACs） were prepared by pyrolysis carbonization and KOH activation. Through modifying activation conditions, samples with large pore volume and ultrahigh BET specific surface area could be obtained. The sample achieved the highest hydrogen uptake capacity of 5.80 wt% at 40 bar and -196℃ The as-obtained samples were characterized by N2-sorption, transmission electron microscopy （TEM） and scanning electron microscopy （SEM）. Besides, thermogravimetric analysis was also employed to investigate the activation behavior of CACs. Detailed investigation on the activation parameters reveals that moderate activation temperature and heating rate are favorable for preparing CACs with high surface area, large pore volume and optimal pore size distribution. Meanwhile, the micropore volume between 0.65 nm and 0.85 nm along with BET surface area and total pore volume has great effects on hydrogen uptake capacities. The present results indicate that CACs are the most promising materials for hydrogen storage application.

Recursive Least Square Vehicle Mass Estimation Based on Acceleration Partition

Vehicle mass is an important parameter in vehicle dynamics control systems. Although many algorithms have been developed for the estimation of mass, none of them have yet taken into account the different types of resistance that occur under different conditions. This paper proposes a vehicle mass estimator. The estimator incorporates road gradient information in the longitudinal accelerometer signal, and it removes the road grade from the longitudinal dynamics of the vehicle. Then, two different recursive least square method （RLSM） schemes are proposed to estimate the driving resistance and the mass independently based on the acceleration partition under different conditions. A 6 DOF dynamic model of four In-wheel Motor Vehicle is built to assist in the design of the algorithm and in the setting of the parameters. The acceleration limits are determined to not only reduce the estimated error but also ensure enough data for the resistance estimation and mass estimation in some critical situations. The modification of the algorithm is also discussed to improve the result of the mass estimation. Experiment data on asphalt road, plastic runway, and gravel road and on sloping roads are used to validate the estimation algorithm. The adaptability of the algorithm is improved by using data collected under several critical operating conditions. The experimental results show the error of the estimation process to be within 2.6%, which indicates that the algorithm can estimate mass with great accuracy regardless of the road surface and gradient changes and that it may be valuable in engineering applications. This paper proposes a recursive least square vehicle mass estimation method based on acceleration partition.

Method of Electric Powertrain Matching for Battery-powered Electric Cars

The current match method of electric powertrain still makes use of longitudinal dynamics, which can’t realize maximum capacity for on-board energy storage unit and can’t reach lowest equivalent fuel consumption as well. Another match method focuses on improving available space considering reasonable layout of vehicle to enlarge rated energy capacity for on-board energy storage unit, which can keep the longitudinal dynamics performance almost unchanged but can’t reach lowest fuel consumption. Considering the characteristics of driving motor, method of electric powertrain matching utilizing conventional longitudinal dynamics for driving system and cut-and-try method for energy storage system is proposed for passenger cars converted from traditional ones. Through combining the utilization of vehicle space which contributes to the on-board energy amount, vehicle longitudinal performance requirements, vehicle equivalent fuel consumption level, passive safety requirements and maximum driving range requirement together, a comprehensive optimal match method of electric powertrain for battery-powered electric vehicle is raised. In simulation, the vehicle model and match method is built in Matlab/simulink, and the Environmental Protection Agency (EPA) Urban Dynamometer Driving Schedule (UDDS) is chosen as a test condition. The simulation results show that 2.62% of regenerative energy and 2% of energy storage efficiency are increased relative to the traditional method. The research conclusions provide theoretical and practical solutions for electric powertrain matching for modern battery-powered electric vehicles especially for those converted from traditional ones, and further enhance dynamics of electric vehicles.

Preparation and Performance of Hollow Spherical Li4Ti5O12 Doped by Mg^2+

The microstructure and performance of Li4Ti5O12 doped by Mg prepared by hydrothermal method and solid phase method were investigated. Lithium dihydrate, magnesium acetate and tetrabutyl titanate were used as the main raw materials. This study reveals that Mg^2+ has influences on the spherical structure, crystal development of Li4Ti5O12 and the electrochemical performances. The hollow spherical structure is composed of nano-sheet structure and the nano-sheet structure can be affected by the Mg^2+ content. For Li4-xMgxTi5 O12, the sheet structure can be refined with the increment of Mg^2+ content when x value is 0-0.1 and coarsen with the increment of Mg^2+ content when x value is 0.1-0.2. The hollow spherical Li4Ti5O12 powders prepared by hydrothermal method have better performance. The optimal Mgdoped amount of hydrothermal method is 0.1. At 0.1 C, the first discharge capacity of Li3.9Mg0.1Ti5O12 prepared through hydrothermal method at 0.1 C and 10 cycles is 182 and 178 mA hg^-1, respectively.

Pore size effects of nanoporous carbons with ultra-high surface area on high-pressure hydrogen storage

In this work, the morphologies and pore structures of a series of corncob-derived activated carbons and zeolite templated carbon with ultrahigh surface area were carefully investigated by SEM, HRTEM and N2-sorption characterization technologies. The high-pressure hydrogen uptake performance was analyzed using standard Pressure-Composition-Temperature apparatus in order to study the pore size effects on hydrogen uptake. These as-obtained porous carbons showed different characteristics of pore size distribution as well as specific surface area. The results indicate that the most effective pores for adsorbing hydrogen depended on the storage pressure. These ultramicropores （0.65-0.85 nm） could be the most effective pores on excess H2 uptake at 1 bar, however, micropores （0.85-2 nm） would play a more important role in excess H2 uptake at higher pressure at 77 K. At room temperature, pore size effects on H2 uptake capacity were very weak. Both specific surface area and total pore volume play more important roles than pore size for H2 uptake at room temperature, which was clearly different from that at 77 K. For applications in future, the corncob-derived activated carbons can be more available than zeolite templated carbons at 77 K. Element doping enhanced hydrogen uptake could be main research direction for improving H2 uptake capacity at room temperature.

NO adsorption and temperature programmed desorption on K_2CO_3 modified activated carbons

Fuel cell stacks as the automotive power source can be severely poisoned by a trace amount of NOx in atmosphere,which makes it necessary to provide clean air for fuel cell vehicles.In this work,activating commercial activated carbons with K2CO3 for the large enhancement of NO capture was studied.K2CO3 modified activated carbons(K2CO3 ACs)were prepared by impregnating activate carbons in K2CO3 solution under ultrasound treatment,followed by temperature programmed baking at 800 oC.The dynamic NO flow tests on K2CO3 ACs at room temperature indicated that NO adsorption capacity reached the maximum(96 mg/g)when K2CO3 loading was 19.5 wt%,which corresponded to a specific surface area of 1196.1 m2/g and total pore volume of 0.70 cm3/g.The ten-fold enhancement of NO adsorption on K2CO3 ACs compared to the unimpregnated activated carbon was mainly attributed to the formation of potassium nitrite,which was confirmed by FTIR and temperature programmed desorption measurements.Regeneration tests of NO adsorption on the optimum sample revealed that 76%of the NO adsorption capacity could be remained after the fourth cycle.

SnO_2/corncob-derived activated carbon nanohybrid as an anode material for lithium-ion batteries

A facile synthesis of Sn O2/corncob-derived activated carbon（CAC） composite was proposed,and the CAC used here has high specific surface area（over 3000 m2/g） and ample oxygen-containing functional groups.The microstructures and morphology as well as electrochemical performance of the Sn O2/CAC composites were investigated by X-ray diffraction,scanning electron microscopy,transmission electron microscopy and relevant electrochemical characterization. The results show that the mass ratios of Sn O2 to CAC have a significant effect on the structures and properties of the composites. The sample with 34% Sn O2 delivered a capacity of 879.8 m Ah/g in the first reversible cycle and maintained at 634.0 m Ah/g（72.1% retention of the initial reversible capacity） after 100 cycles at a current density of 200 m A/g. After 60 cycles at different specific currents from 200 to 2000 m A/g,the reversible specific capacity was still maintained at 632.8 m Ah/g at a current density of 200 m A/g. These results indicate that SnO 2/CAC can be a desirable alternative anode material for lithium ion batteries.

Gold Catalysts Supported on Crystalline Fe_2O_3 and CeO_2/Fe_2O_3 for Low-temperature CO Oxidation

High active and stable gold catalysts supported on crystalline Fe203 and CeO2/Fe2O3 were prepared via the deposition-precipitation method. The catalyst with a Au load of 1.0% calcined at 180 ℃ showed a CO conversion of 100% at -8.9℃, while Au/CeO2/Fe2O3 converted CO completely at -16.1 ℃. Even having been calcined at 500 ℃, Au/Fe2O3 still exhibited significant catalytic activity, achieving full conversion of CO at 61.6℃. The catalyst with a low Au load of 0.5% could convert CO completely at room temperature and kept the activity unchanged for at least 150 h. N2 adsorption-desorption measurements show that the crystalline supports possessed a high specific surface area of about 200 m2/g. Characterizations of X-ray diffraction and transmission electron microscopy indicate that gold species were highly dispersed as nano or sub-nano particles on the supports. Even after the catalyst was calcined at 500 ℃, the Au particles remained in a nano-size of about 6--10 nm. X-ray photoelectron spectra reveal that the supported Au existed in metallic state Au0. The modification of Au/Fe2O3 by CeO2 proved to be beneficial to the inhibition of crystallization of Fe2O3 and the stabilization of gold particles in dispersed state, consequently promoting catalytic activity.

Chaos Synchronization of Uncertain Lorenz System via Single State Variable Feedback

This paper treats the problem of chaos synchronization for uncertain Lorenz system via single state variable information of the master system. By the Lyapunov stability theory and adaptive technique, the derived controller is featured as follows: 1) only single state variable information of the master system is needed;2) chaos synchronization can also be achieved even if the perturbation is occurred in some parameters of the master chaotic system. Finally, the effectiveness of the proposed controllers is also illustrated by the simulations as well as rigorous mathematical proofs.

Co-estimation of state-of-charge and state-of-temperature for large-format lithium-ion batteries based on a novel electrothermal model

The safe and efficient operation of the electric vehicle significantly depends on the accurate state-of-charge(SOC)and state-of-temperature(SOT)of Lithium-ion(Li-ion)batteries.Given the influence of cross-interference between the two states indicated above,this study establishs a co-estimation framework of battery SOC and SOT.This framwork is based on an innovative electrothermal model and adaptive estimation algorithms.The first-order RC electric model and an innovative thermal model are components of the electrothermal model.Specifically,the thermal model includes two lumped-mass thermal submodels for two tabs and a two-dimensional(2-D)thermal resistance network(TRN)submodel for the main battery body,capable of capturing the detailed thermodynamics of large-format Li-ion batteries.Moreover,the proposed thermal model strikes an acceptable compromise between the estimation fidelity and computational complexity by representing the heat transfer processes by the thermal resistances.Besides,the adaptive estimation algorithms are composed of an adaptive unscented Kalman filter(AUKF)and an adaptive Kalman filter(AKF),which adaptively update the state and noise covariances.Regarding the estimation results,the mean absolute errors(MAEs)of SOC and SOT estimation are controlled within 1%and 0.4°C at two temperatures,indicating that the co-estimation method yields superior prediction performance in a wide temperature range of 5–35°C.

Constructing an unbalanced structure toward high working voltage for improving energy density of non-aqueous carbon-based electrochemical capacitors

The energy density of non-aqueous carbon-based electrochemical capacitors(cEC)is mainly determined by the specific capacitance and operational voltage range.In this study,we propose to construct an unbalanced structure to make full use of stable voltage range for improving energy density.The stable voltage range is firstly carefully explored using cyclic voltammetry.Then an unbalanced carbon-based electrochemical capacitor(ucEC)is constructed with an optimized positive electrode to negative electrode weight ratio and voltage range.Its electrochemical performance is comprehensively investigated,including energy density,power density as well as cycle life.The ucEC is capable to deliver an improved energy density up to 64.9 Wh/kg(1.4 times as high as a general cEC)without sacrificing the power density and cycle life.The electrode properties after cycling are also analyzed,illustrating the change of electrode potential caused by unbalanced structure.The proposed structure demonstrates a great potential for improving the energy density at little cost of electrode design and cell configuration.

Real-time energy-efficient anticipative driving control of connected and automated hybrid electric vehicles

In this paper,we propose a real-time energy-efficient anticipative driving control strategy for connected and automated hybrid electric vehicles(HEVs).Considering the inherent complexities brought about by the velocity profile optimization and energy management control,a hierarchical control architecture in the model predictive control(MPC)framework is developed for real-time implementation.In the higher level controller,a novel velocity optimization problem is proposed to realize safe and energy-efficient anticipative driving.The real-time control actions are derived through a computationally efficient algorithm.In the lower level controller,an explicit solution of the optimal torque split ratio and gear shift schedule is introduced for following the optimal velocity profile obtained from the higher level controller.The comparative simulation results demonstrate that the proposed strategy can achieve approximately 13%fuel consumption saving compared with a benchmark strategy.