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.

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.

Real-Time Co-optimization of Gear Shifting and Engine Torque for Predictive Cruise Control of Heavy-Duty Trucks

Fuel consumption is one of the main concerns for heavy-duty trucks.Predictive cruise control(PCC)provides an intriguing opportunity to reduce fuel consumption by using the upcoming road information.In this study,a real-time implementable PCC,which simultaneously optimizes engine torque and gear shifting,is proposed for heavy-duty trucks.To minimize fuel consumption,the problem of the PCC is formulated as a nonlinear model predictive control(MPC),in which the upcoming road elevation information is used.Finding the solution of the nonlinear MPC is time consuming;thus,a real-time implementable solver is developed based on Pontryagin’s maximum principle and indirect shooting method.Dynamic programming(DP)algorithm,as a global optimization algorithm,is used as a performance benchmark for the proposed solver.Simulation,hardware-in-the-loop and real-truck experiments are conducted to verify the performance of the proposed controller.The results demonstrate that the MPC-based solution performs nearly as well as the DP-based solution,with less than 1%deviation for testing roads.Moreover,the proposed co-optimization controller is implementable in a real-truck,and the proposed MPC-based PCC algorithm achieves a fuel-saving rate of 7.9%without compromising the truck’s travel time.

Flow and sound fields of scaled high-speed trains with different coach numbers running in long tunnel

Segregated incompressible large eddy simulation and acoustic perturbation equations were used to obtain the flow field and sound field of 1:25 scale trains with three,six and eight coaches in a long tunnel,and the aerodynamic results were verified by wind tunnel test with the same scale two-coach train model.Time-averaged drag coefficients of the head coach of three trains are similar,but at the tail coach of the multi-group trains it is much larger than that of the three-coach train.The eight-coach train presents the largest increment from the head coach to the tail coach in the standard deviation(STD)of aerodynamic force coefficients:0.0110 for drag coefficient(Cd),0.0198 for lift coefficient(Cl)and 0.0371 for side coef-ficient(Cs).Total sound pressure level at the bottom of multi-group trains presents a significant streamwise increase,which is different from the three-coach train.Tunnel walls affect the acoustic distribution at the bottom,only after the coach number reaches a certain value,and the streamwise increase in the sound pressure fluctuation of multi-group trains is strengthened by coach number.Fourier transform of the turbulent and sound pressures presents that coach number has little influence on the peak frequencies,but increases the sound pressure level values at the tail bogie cavities.Furthermore,different from the turbulent pressure,the first two sound pressure proper orthogonal decomposition(POD)modes in the bogie cavities contain 90%of the total energy,and the spatial distributions indicate that the acoustic distributions in the head and tail bogies are not related to coach number.

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.

A Combined Reinforcement Learning and Model Predictive Control for Car-Following Maneuver of Autonomous Vehicles

Model predictive control is widely used in the design of autonomous driving algorithms.However,its parameters are sensitive to dynamically varying driving conditions,making it difficult to be implemented into practice.As a result,this study presents a self-learning algorithm based on reinforcement learning to tune a model predictive controller.Specifically,the proposed algorithm is used to extract features of dynamic traffic scenes and adjust the weight coefficients of the model predictive controller.In this method,a risk threshold model is proposed to classify the risk level of the scenes based on the scene features,and aid in the design of the reinforcement learning reward function and ultimately improve the adaptability of the model predictive controller to real-world scenarios.The proposed algorithm is compared to a pure model predictive controller in car-following case.According to the results,the proposed method enables autonomous vehicles to adjust the priority of performance indices reasonably in different scenarios according to risk variations,showing a good scenario adaptability with safety guaranteed.

Evolutionary Decision-Making and Planning for Autonomous Driving Based on Safe and Rational Exploration and Exploitation

Decision-making and motion planning are extremely important in autonomous driving to ensure safe driving in a real-world environment.This study proposes an online evolutionary decision-making and motion planning framework for autonomous driving based on a hybrid data-and model-driven method.First,a data-driven decision-making module based on deep reinforcement learning(DRL)is developed to pursue a rational driving performance as much as possible.Then,model predictive control(MPC)is employed to execute both longitudinal and lateral motion planning tasks.Multiple constraints are defined according to the vehicle’s physical limit to meet the driving task requirements.Finally,two principles of safety and rationality for the self-evolution of autonomous driving are proposed.A motion envelope is established and embedded into a rational exploration and exploitation scheme,which filters out unreasonable experiences by masking unsafe actions so as to collect high-quality training data for the DRL agent.Experiments with a high-fidelity vehicle model and MATLAB/Simulink co-simulation environment are conducted,and the results show that the proposed online-evolution framework is able to generate safer,more rational,and more efficient driving action in a real-world environment.

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.

Multi-level intelligence empowering lithium-ion batteries

With the significant and widespread application of lithium-ion batteries,there is a growing demand for improved performances of lithium-ion batteries.The intricate degradation throughout the whole lifecycle profoundly impacts the safety,durability,and reliability of lithium-ion batteries.To ensure the long-term,safe,and efficient operation of lithium-ion batteries in various fields,there is a pressing need for enhanced battery intelligence that can withstand extreme events.This work reviews the current status of intelligent battery technology from three perspectives:intelligent response,intelligent sensing,and intelligent management.The intelligent response of battery materials forms the foundation for battery stability,the intelligent sensing of multi-dimensional signals is essential for battery management,and the intelligent management ensures the long-term stable operation of lithium-ion batteries.The critical challenges encountered in the development of intelligent battery technology from each perspective are thoroughly analyzed,and potential solutions are proposed,aiming to facilitate the rapid development of intelligent battery technologies.

Comparative Study of Trajectory Tracking Control for Automated Vehicles via Model Predictive Control and Robust H-infinity State Feedback Control

A comparative study of model predictive control(MPC)schemes and robust Hstate feedback control(RSC)method for trajectory tracking is proposed in this paper.The main objective of this paper is to compare MPC and RSC controllers’performance in tracking predefined trajectory under different scenarios.MPC controller is designed based on the simple longitudinal-yaw-lateral motions of a single-track vehicle with a linear tire,which is an approximation of the more realistic model of a vehicle with double-track motion with a non-linear tire mode.RSC is designed on the basis of the same method as adopted for the MPC controller to achieve a fair comparison.Then,three test cases are built in CarSim-Simulink joint platform.Specifically,the verification test is used to test the tracking accuracy of MPC and RSC controller under well road conditions.Besides,the double lane change test with low road adhesion is designed to find the maximum velocity that both controllers can carry out while guaranteeing stability.Furthermore,an extreme curve test is built where the road adhesion changes suddenly,in order to test the performance of both controllers under extreme conditions.Finally,the advantages and disadvantages of MPC and RSC under different scenarios are also discussed.

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.

Performance Analysis and Improvement of Flat Torque Converters Using DOE Method

Automotive torque converters have recently been designed with an increasingly narrower profile for the purpose of achieving a smaller axial size and reducing weight. Design of experiment(DOE) and computational fluid dynamics(CFD) techniques are applied to improve the performance of a flat torque converter. Four torque converters with different flatness ratios(0.204, 0.186, 0.172, and 0.158) are designed and simulated first to investigate the effects of flatness ratio on their overall performance, including efficiency, torque ratio, and impeller torque factor. The simulation results show that the overall performance tends to deteriorate as the flatness ratio decreases. Then a parametric study covering six geometric parameters, namely, inlet and outlet angles of impeller, turbine, and stator is carried out. The results demonstrate that the inlet and outlet angles play an important role in determining the performance characteristics of a torque converter. Furthermore, the relative importance of the six design parameters is investigated using DOE method for each response(stall torque ratio and peak efficiency). The turbine outlet angle is found to exert the greatest influence on both responses. After DOE analysis, an optimized design for the flat torque converter geometry is obtained. Compared to the conventional product, the width of the optimized flat torque converter torus is reduced by about 20% while the values of stall torque ratio and peak efficiency are only decreased by 0.4% and 1.7%, respectively.The proposed new optimization strategy based on DOE method together with desirability function approach can be used for performance enhancement in the design process of flat torque converters.

The effect of single-horn glaze ice on the vortex structures in the wake of a horizontal axis wind turbine

The present study experimentally investigated the effect of a simulated single-horn glaze ice accreted on ro- tor blades on the vortex structures in the wake of a hori- zontal axis wind turbine by using the stereoscopic particle image velocimetry （Stereo-PIV） technique. During the ex- periments, four horizontal axis wind turbine models were tested, and both ＂free-run＂ and ＂phase-locked＂ Stereo-PIV measurements were carried out. Based on the ＂free-run＂ measurements, it was found that because of the simulated single-horn glaze ice, the shape, vorticity, and trajectory of tip vortices were changed significantly, and less kinetic en- ergy of the airflow could be harvested by the wind turbine. In addition, the ＂phase-locked＂ results indicated that the pres- ence of simulated single-horn glaze ice resulted in a dramatic reduction of the vorticity peak of the tip vortices. Moreover, as the length of the glaze ice increased, both root and tip vortex gaps were found to increase accordingly.

Performance Optimization of Torque Converters Based on Modified 1D Flow Model

A methodology for performance optimization of torque converters is put forward based on the one-dimensional (1D) flow model. It is found that the inaccuracy of 1D flow model for predicting hydraulic performance at the low speed ratio is mainly caused by the separation phenomenon at the stator cascade which is induced by large flow impinging at the pressure side of the stator blades. A semi-empirical separation model is presented and incorporated to the original 1D flow model. It is illustrated that the improved model is able to predict the circumferential velocity components accurately, which can be applied to performance optimization. Then, the Pareto front is obtained by using the genetic algorithm (GA) in order to inspect the coupled relationship among stalling impeller torque capacity, stalling torque ratio and efficiency. The efficiency is maximized on the premise that a target stalling impeller torque capacity and torque ratio are achieved. Finally, the optimized result is verified by the computational fluid dynamics(CFD) simulation, which indicates that the maximal efficiency is increased by 0.96%.

Design and optimization of exhaust gas aftertreatment system for a heavy-duty diesel engine

Diesel engines meeting the latest emission regulations must be equipped with exhaust gas aftertreatment system,including diesel oxidation catalysts(DOC),diesel particulate filters(DPF),and selective catalytic reduction(SCR).However,before the final integration of the aftertreatment system(DOC+DPF+SCR)and the diesel engine,a reasonable structural optimization of the catalytic converters and a large number of bench calibration tests must be completed,involving large costs and long development cycles.The design and optimization of the exhaust gas aftertreatment system for a heavy-duty diesel engine was proposed in this paper.Firstly,one-dimensional(1D)and threedimensional(3D)computational models of the exhaust gas aftertreatment system accounting for the structural parameters of the catalytic converters were established.Then based on the calibrated models,the effects of the converter’s structural parameters on their main performance indicators,including the conversion of various exhaust pollutants and the temperatures and pressure drops of the converters,were studied.Finally,the optimal design scheme was obtained.The temperature distribution of the solid substrates and pressure distributions of the catalytic converters were studied based on the 3D model.The method proposed in this paper has guiding significance for the optimization of diesel engine aftertreatment systems.

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.

Influence of PTFE on Electrode Structure for Performance of PEMFC and 10-Cells Stack

Water plays a critical role on the performance, stability and lifetime of proton exchange membrane fuel cells（PEMFCs）. The addition of poly tetrafluoroethylene（PTFE） to the gas diffusion layer, especially, the cathode side, would optimize the transportation of water, electron and gas and thus improve the performance of the fuel cell. But until now, the studies about directly applying the PTFE to the catalyst layer are rarely reported. In this paper, the membrane electrode is fabricated by using directly coating catalyst to the membrane method（CCM） and applying PTFE directly to the cathode electrode catalyst layer. The performance of the single cell is determined by polarization curves and durability tests. Electrochemical impedance spectroscopy（EIS） and scanning electron microscopy（SEM） techniques are used to characterize the electrochemical properties of PEMFC. Also the performance of a 10-cells stack is detected. Combining the performance and the physical-chemistry characterization of PEMFC shows that addition of appropriate content of PTFE to the electrode enhances the performance of the fuel cell, which may be due to the improved water management. Addition of appropriate content of PTFE enhances the interaction between the membrane and the catalyst layer, and bigger pores and highly textured structure form in the MEA, which favors the oxygen mass transfer and protons transfer in the fuel cell. While superfluous addition of PTFE covers the surface of catalysts and hindered the contact of catalyst with Nation, which leads to the reduction of electrochemical active area and the decay of the fuel cell performance. The proposed research would optimize the water management of the fuel cell and thus improve the performance of the fuel cell.

Comparison of Isobaric and Non-isobaric Operations on a Two-Phase Dynamic Model for PEFC Cathode Gas Diffusion Layer

Key words,： Two 1-D dynamical and isothermal models of cathode gas diffusion layer（GDL） with isobaric and non-isobaric operations for polymer electrolyte fuel cells（PEFCs） were developed and implemented in COMSOL Multiphysics v3.5.The artificial diffusion coefficient was introduced as well to make the numerical computation be stable.In the non-isobaric model,the pressure of gas mixture was obtained by summing up the governing equations of gaseous components,instead of Navier-Stoks equation.Comparison of the two models were carried out with the steady-states and dynamical simulations under given conditions.The corresponding analysis based on the simulated results was also given simultaneously.This paper is contributed to finding the differences between the isobaric and non-isobaric operation in the two-phase model of cathode GDL.

Application of Solid Oxide Fuel Cell-Auxiliary Power Unit on Different Trucks in Northeast China

A diesel engine of conventional trucks has a low efficiency under the idling condition,leading to a high cost for heating or cooling in the cab during night. The solution to this problem will have great significance on energy conservation and emission reduction. A new auxiliary power unit of solid oxide fuel cell( SOFCAPU) with high efficiency solves this problem perfectly. Heat pump air conditioner is considered as a promising device for the application of SOFC-APU with a high cooling and heating efficiency. To make a quantitative analysis for the application of SOFC-APU,a model is built in Matlab / Simulink. The diesel engine model and SOFC-APU model are fitted based on some experimental data of SOFC-APU and diesel engine during the idling operation. An analysis of the application of SOFC-APU on different trucks in Northeast China is comprehensively made,including efficiency and emission.

Design of Multi-domain Collaborative Simulation System for Dual Clutch Transmission Based on CAN Bus

A multi-domain collaborative simulation(MDCS) system for dual clutch transmission(DCT) was presented based on controller area network(CAN) bus.An interface card of CAN bus was designed,in which MDCS subsystems were linked as the nodes according to the interface mode of MDCS.A DCT simulation model was established based on Matlab/Simdriveline,whose running process was accurately controlled by the designed control system.The playback system of vehicle state(VPS) was proposed whose input was the road-test data,with a real vehicle test environment for the development of transmission control unit(TCU) being provided.A DCT kinematic system model was set up,and the running status of DCT parts could be displayed in real time.The functions of MDCS were verified based on the extra-urban driving cycle(EUDC) and the vehicle road-test data respectively.The results show the functions of MDCS are accomplished,and the unified supporting platform for the development of TCU is achieved by MDCS.