Automobile Transportation Logistics Supply Chain Management Strategy

To enhance the management level and quality of the automobile transportation logistics supply chain and promote innovation and development in automobile transportation logistics enterprises,it is essential to strengthen the construction of the automobile transportation logistics supply chain management model.This can be achieved through the gradual improvement of the automobile transportation logistics management process,ensuring that the management of the automobile transportation logistics supply chain proceeds in an orderly manner.The aim is to improve automobile transportation and logistics service levels while meeting the changing market supply needs.This will enable automobile transportation and logistics enterprises to maintain steady economic benefits and enhance their core competitiveness in the market.Therefore,this paper has conducted a comprehensive exploration and research on managing the automobile transportation logistics supply chain.Corresponding management strategies are proposed as a starting point to achieve the aforementioned goals.

Bottom-up holistic carrier management strategy induced synergistically by multiple chemical bonds to minimize energy losses for efficient and stable perovskite solar cells

The defects from electron transport layer,perovskite layer and their interface would result in carrier nonradiative recombination losses.Poor buried interfacial contact is detrimental to charge extraction and device stability.Here,we report a bottom-up holistic carrier management strategy induced synergistically by multiple chemical bonds to minimize bulk and interfacial energy losses for high-performance perovskite photovoltaics.4-trifluoromethyl-benzamidine hydrochloride(TBHCl)containing–CF_(3),amidine cation and Cl^(-)is in advance incorporated into SnO_(2)colloid solution to realize bottom-up modification.The synergistic effect of multiple functional groups and multiple-bond-induced chemical interaction are revealed theoretically and experimentally.F and Cl^(-)can passivate oxygen vacancy and/or undercoordinated Sn^(4+)defects by coordinating with Sn^(4+).The F can suppress cation migration and modulate crystallization via hydrogen bond with FA^(+),and can passivate lead defects by coordinating with Pb^(2+).The–NH_(2)–C=NH^(+)_(2)and Cl^(-)can passivate cation and anion vacancy defects through ionic bonds with perovskites,respectively.Through TBHCl modification,the suppression of agglomeration of SnO_(2)nanoparticles,bulk and interfacial defect passivation,and release of tensile strains of perovskite films are demonstrated,which resulted in a PCE enhancement from 21.28%to 23.40%and improved stability.With post-treatment,the efficiency is further improved to 23.63%.

ENERGY MANAGEMENT STRATEGY FOR PARALLEL HYBRID ELECTRIC VEHICLES

Energy management strategy (EMS) is the core of the real-time controlalgorithm of the hybrid electric vehicle (HEV). A novel EMS using the logic threshold approach withincorporation of a stand-by optimization algorithm is proposed. The aim of it is to minimize theengine fuel consumption and maintain the battery state of charge (SOC) in its operation range, whilesatisfying the vehicle performance and drivability requirements. The hybrid powertrain bench testis carried out to collect data of the engine, motor and battery pack, which are used in the EMS tocontrol the powertrain. Computer simulation model of the HEV is established in the MATLAB/Simulinkenvironment according to the bench test results. Simulation results are presented for behaviors ofthe engine, motor and battery. The proposed EMS is implemented for a real parallel hybrid carcontrol system and validated by vehicle field tests.

Application of the interventional limb raising management strategy(ILRMS) at radial vascular access sites in coronary angiography and percutaneous coronary intervention:A randomized trial

Purpose:To compare the effectiveness of the interventional limb raising management strategy(ILRMS)to elastic bandage compression at radial vascular access sites following coronary angiographies(CAGs)and percutaneous coronary interventions(PCIs).Methods:Patients with ischemic coronary heart disease whose condition was stable over three months were enrolled in this clinical study(n=590;aged 25e80).All participants had just undergone CAG and PCI.Patients were randomized into either the ILRMS group(n=360)or standard post-intervention care with an elastic bandage(n=230).Overall comfort and wrist pain was assessed and the degree of index finger swelling and oxygen saturation was measured on the affected arm.All variables were measured prior to postintervention treatment and again at six hours after CAG and PCI.Results:We found that patients receiving ILRMS had significantly lower wrist pain scores and swelling around the index finger compared to the elastic bandage group(p<0.05).Oxygen saturation of the index finger was not statistically significant(p>0.05).We also found that 19.57%of the elastic bandage patients were comfortable,while ILRMS patients were significantly more comfortable(93.06%;p<0.05).Conclusions:We find that ILRMS alleviates swelling and pain of the wrist more effectively than current practices and improves the degree of overall comfort of patients who undergo CAG and PCI.

DEVELOPMENT OF THE ENERGY MANAGEMENT STRATEGY FOR PARALLEL HYBRID ELECTRIC URBAN BUSES

A novel parallel hybrid electrical urban bus （PHEUB） configuration consisting of an extra one-way clutch and an automatic mechanical transmission （AMT） is taken as the study subject. An energy management strategy combining a logic threshold approach and an instantaneous optimization algorithm is proposed for the investigated PHEUB. The objective of the energy management strategy is to achieve acceptable vehicle performance and drivability requirements while simultaneously maximizing the engine fuel consumption and maintaining the battery state of charge in its operation range at all times. Under the environment of Matlab/Simulink, a computer simulation model for the PHEUB is constructed by using the model building method combining theoretical analysis and bench test data. Simulation and experiment results for China Typical Bus Driving Schedule at Urban District （CTBDS_UD） are obtained, and the results indicate that the proposed control strategy not only controls the hybrid system efficiently but also improves the fuel economy significantly.

Integral evaluation of operating quality and the deciding of management strategy in productive coal mines

According to overall mean square root of weighted deviation, presented an evaluation model of geology-technique-social conditions with a significant index system for the estimation of operating quality in productive coal mines. In the given example, the evaluation result is used to decide management strategy of coal mine, which plays a guiding role in the production.

Integrated management strategy for improving the grain yield and nitrogen-use efficiency of winter wheat

Understanding of how combinations of agronomic options can be used to improve the grain yield and nitrogen use efficiency（NUE） of winter wheat is limited. A three-year experiment involving four integrated management strategies was conducted from 2013 to 2015 in Tai＇an, Shandong Province, China, to evaluate changes in grain yield and NUE. The integrated management treatments were as follows： current practice（T1）; improvement of current practice（T2）; high-yield management（T3）, which aimed to maximize grain yield regardless of the cost of resource inputs; and integrated soil and crop system management（T4） with a higher seeding rate, delayed sowing date, and optimized nutrient management. Seeding rates increased by 75 seeds m^-2 with each treatment from T1（225 seeds m^-2） to T4（450 seeds m^-2）. The sowing dates were delayed from T1（5 th Oct.） to T2 and T3（8 th Oct.）, and to T4 treatment（12 th Oct.）. T1, T2, T3, and T4 received 315, 210, 315, and 240 kg N ha^-1, 120, 90, 210 and 120 kg P2O5 ha^-1, 30, 75, 90, and 45 kg K2O ha^-1, respectively. The ratio of basal application to topdressing for T1, T2, T3, and T4 was 6：4, 5：5, 4：6, and 4：6, respectively, with the N topdressing applied at regreening for T1 and at jointing stage for T2, T3, and T4. The P fertilizers in all treatments were applied as basal fertilizer. The K fertilizer for T1 and T2 was applied as basal fertilizer while the ratio of basal application to topdressing（at jointing stage） of K fertilizer for both T3 and T4 was 6：4. T1, T2, T3, and T4 were irrigated five, four, four and three times, respectively. Treatment T3 produced the highest grain yield among all treatments over three years and the average yield was 9 277.96 kg ha^-1. Grain yield averaged across three years with the T4 treatment（8 892.93 kg ha^-1） was 95.85% of that with T3 and was 21.72 and 6.10% higher than that with T1（7 305.95 kg ha^-1） and T2（8 381.41 kg ha^-1）, respectively. Treatment T2 produced the highest NUE of all the integrated treatments. The NUE with T4 was 95.36% of that with T2 and was 51.91 and 25.62% higher than that with T1 and T3, respectively. The N uptake efficiency（UPE） averaged across three years with T4 was 50.75 and 16.62% higher than that with T1and T3, respectively. The N utilization efficiency（UTE） averaged across three years with T4 was 7.74% higher than that with T3. The increased UPE with T4 compared with T3 could be attributed mostly to the lower available N in T4, while the increased UTE with T4 was mainly due to the highest N harvest index and low grain N concentration, which consequently led to improved NUE. The net profit for T4 was the highest among four treatments and was 174.94, 22.27, and 28.10% higher than that for T1, T2, and T3, respectively. Therefore, the T4 treatment should be a recommendable management strategy to obtain high grain yield, high NUE, and high economic benefits in the target region, although further improvements of NUE are required.

Simulation research of energy management strategy for dual mode plug-in hybrid electrical vehicles

In this paper, a plug-in hybrid electrical vehicle(PHEV) is taken as the research object, and its dynamic performance and economic performance are taken as the research goals. Battery charge-sustaining(CS) period is divided into power mode and economy mode. Energy management strategy designing methods of power mode and economy mode are proposed. Maximum velocity, acceleration performance and fuel consumption are simulated during the CS period in the AVL CRUISE simulation environment. The simulation results indicate that the maximum velocity and acceleration time of the power mode are better than those in the economy mode. Fuel consumption of the economy mode is better than that in the power mode. Fuel consumption of PHEV during the CS period is further improved by using the methods proposed in this paper, and this is meaningful for research and development of PHEV.

Research on System Control and Energy Management Strategy of Flux-Modulated Compound-Structure Permanent Magnet Synchronous Machine

The flux-modulated compound-structure permanent magnet synchronous machine (CS-PMSM), composed of a brushless double rotor machine (DRM) and a conventional permanent magnet synchronous machine (PMSM), is a power split device for plug-in hybrid electric vehicles. In this paper, its operating principle and mathematical model are introduced. A modified current controller with decoupled state feedback is proposed and verified. The system control strategy is simulated in Matlab, and the feasibility of the control system is proven. To improve fuel economy, an energy management strategy based on fuzzy logic controller is proposed and evaluated by the Urban Dynamometer Driving Schedule (UDDS) drive cycle. The results show that the total energy consumption is similar to that of Prius 2012.

A Preliminary Study on the Management Strategy of University Personnel Files based on Artificial Intelligence Technology

In order to improve the management strategy for personnel files in colleges and universities,simplify the complex process of file management,and improve file management security and content preservation of the files.This paper elaborates on the application of Artificial Intelligence(AI)technology in university personnel file management through theoretical analysis based on the understanding of Al technology.

Energy management strategy based on dynamic programming with durability extension for fuel cell hybrid tramway

This paper proposes an energy management strategy for a fuel cell(FC)hybrid power system based on dynamic programming and state machine strategy,which takes into account the durability of the FC and the hydrogen consumption of the system.The strategy first uses the principle of dynamic programming to solve the optimal power distribution between the FC and supercapacitor(SC),and then uses the optimization results of dynamic programming to update the threshold values in each state of the finite state machine to realize real-time management of the output power of the FC and SC.An FC/SC hybrid tramway simulation platform is established based on RTLAB real-time simulator.The compared results verify that the proposed EMS can improve the durability of the FC,increase its working time in the high-efficiency range,effectively reduce the hydrogen consumption,and keep the state of charge in an ideal range.

ZTE 's WCDMA Radio Resource Management Strategy

WCDMA Radio Resource Management (RRM) controls the allocation and usage of all radio resources. The purpose of RRM is to have optimal coverage and capacity while ensuring the QoS. RRM directly affects the system performance. As the soul of system control, it includes power control, handoff control, load control, admission control, code allocation, etc. This paper introduces the RRM strategy of ZTE's WCDMA equipment.

THE GRASSLAND RESOURCES OF CHINA AND ITS MANAGEMENT STRATEGY

The total area of grassland in the world is about 50 million km^2, accounting for 33.5% of the total land area (Lieth, 1975). The permanent grassland used by mankind is 33.04 million km^2, accounting for 25.3% of the total land area (FAO,1990). Grassland can provide feed for herbivore and produce high-quality food,clothing,medicines and industrial materials for man.On the other hand,it also plays an important role in the fertility of the soil,the conservation of water, the improvement of the environment and maintaining the ecological balance of the Earth’s surface.

Resistance Selection of Tetranychus cinnabarinus to Three Acaricides and Its Management Strategy

The effects of retarding resistance evolution of mixing and sequencing acaricides were studied based on the resistance selection of three acaricides to Tetranychus cinnabarinus in the laboratory. Tetrany-chus cinnabarinus was continuously selected with fenpropathrin, abamectin and pyridaban for 28, 30 and 31 generations, respectively, and resistance factor increased to 65.6, 7.2 and 1.2 time, accordingly. Results of cross-resistance determination suggested that there were no cross-resistance existed among the three acaricides. Analysis of resistance selection and estimation of realized heritability (h2) of resistance to three single and two mixed acaricides showed that a mixture of fenpropathrin+abamectin would slow resistance development compared with a sequence of fenpropathrin followed by abamectin while the mixture of pyridaben+abamectin and the sequence of pyridaben followed by abamectin would effectively retard resistance evolution.

Cost-Based Research on Energy Management Strategy of Electric Vehicles Using Hybird Energy Storage System

This paper uses the minimization and weighted sum of battery capacity loss and energy consumption under driving cycles as objective functions to improve the economy of Electric Vehicles(EVs)with an hybrid energy storage system composed of power batteries and ultracapacitors.Furthermore,Dynamic Programming(DP)is employed to determine the objective function values under different weight coefficients,the comprehensive cost consisting of battery aging and power consumption costs,and the relationship between the hybrid power distribution.We also evaluate the real-time fuzzy Energy Management Strategy(EMS),fuzzy control strategies,and a strategy based on DP using the World Light vehicle Test Procedure(WLTP)driving cycle and a synthesis driving cycle derived from New European Driving Cycle(NEDC),WLTP,and Urban Dynamometer Driving Schedule(UDDS)as examples.Then,the proposed strategy is compared with the fuzzy control strategy and the strategy based on DP.Compared with fuzzy energy management strategy(namely FZY-EMS),the proposed EMS reduces the battery capacity loss and system energy consumption.The results demonstrate the effectiveness of the proposed EMS in improving EV economy.

Research on Innovation Strategy of Supply Chain Management of Agricultural Enterprises Under the Background of Big Data

With the rapid development and widespread application of Big Data technology, the supply chain management of agricultural products enterprises is facing unprecedented reform and challenges. This study takes the perspective of Big Data technology and collects relevant information on the application of supply chain management in 100 agricultural product enterprises through a survey questionnaire. The study found that the use of Big Data can effectively improve the accuracy of demand forecasting, inventory management efficiency, optimize logistics costs, improve supplier management efficiency, enhance the overall level of supply chain management of enterprises, and propose innovative strategies for supply chain management of agricultural products enterprises based on this. Big Data technology brings a new solution for agricultural products enterprises to enhance their supply chain management level, making the supply chain smarter and more efficient.

Analysis of Innovative Paths for Enterprise Marketing Management Development Strategy under the Background of New Media

From the perspective of enterprise marketing strategy planning,innovative research should be conducted based on the current trends in new media.The findings should be applied to practical activities within enterprises to achieve innovation in marketing strategy decision-making in the new media environment.Enterprises should adopt advanced communication transmission technologies and big data processing capabilities to effectively leverage the hidden value and promotional planning advantages of network media platforms.This approach can enhance customer loyalty and increase demand for new products.Enterprises should integrate into the continuously evolving new media landscape,explore their potential business characteristics,and innovate promotional methods.By effectively combining product information with digital media content,companies can ultimately achieve significant increases in corporate interests.

Global Optimization‑Based Energy Management Strategy for Series–Parallel Hybrid Electric Vehicles Using Multi‑objective Optimization Algorithm

The study of series–parallel plug-in hybrid electric vehicles(PHEVs)has become a research hotspot in new energy vehicles.The global optimal Pareto solutions of energy management strategy(EMS)play a crucial role in the development of PHEVs.This paper presents a multi-objective global optimization algorithm for the EMS of PHEVs.The algorithm combines the Radau Pseudospectral Knotting Method(RPKM)and the Nondominated Sorting Genetic Algorithm(NSGA)-II to optimize both energy conservation and battery lifespan under the suburban driving conditions of the New European Driving Cycle.The driving conditions are divided into stages at evident mode switching points and the optimal objectives are computed using RPKM.The RPKM results serve as the fitness values in iteration through the NSGA-II method.The results of the algorithm applied to a PHEV simulation show a 26.74%–53.87%improvement in both objectives after 20 iterations compared to the solutions obtained using only RPKM.The proposed algorithm is evaluated against the weighting dynamic programming and is found to be close to the global optimality,with the added benefits of faster and more uniform solutions.

Hierarchical predictive energy management strategy for fuel cell buses entering bus stops scenario

This paper aims to answer how to use traffic information to design energy management strategies for fuel cell buses in a networked environment.For the buses entering the bus stops scenario,this paper proposes a hierarchical energy management strategy for fuel cell buses,which considers the traffic information near the bus stops.In the upper-level trajectory planning stage,the optimal SOC trajectory under various historical traffic conditions is solved through dynamic planning.The traffic information and the best SOC trajectory are mapped through BiLSTM,which can achieve fast,real-time long-term SOC reference.In the lower-level real-time predictive energy management strategy,the optimal SOC is used as the state reference to guide the predictive energy management of fuel cell buses when entering the bus stops.Simulation results show that compared with the strategy without SOC trajectory reference,the life cost of the proposed strategy is reduced by 13.8%,and the total cost is reduced by 3.61%.The SOC of the proposed strategy is closer to the DP optimal solution.

Reinforcement Learning-Based Energy Management for Hybrid Power Systems:State-of-the-Art Survey,Review,and Perspectives

The new energy vehicle plays a crucial role in green transportation,and the energy management strategy of hybrid power systems is essential for ensuring energy-efficient driving.This paper presents a state-of-the-art survey and review of reinforcement learning-based energy management strategies for hybrid power systems.Additionally,it envisions the outlook for autonomous intelligent hybrid electric vehicles,with reinforcement learning as the foundational technology.First of all,to provide a macro view of historical development,the brief history of deep learning,reinforcement learning,and deep reinforcement learning is presented in the form of a timeline.Then,the comprehensive survey and review are conducted by collecting papers from mainstream academic databases.Enumerating most of the contributions based on three main directions—algorithm innovation,powertrain innovation,and environment innovation—provides an objective review of the research status.Finally,to advance the application of reinforcement learning in autonomous intelligent hybrid electric vehicles,future research plans positioned as“Alpha HEV”are envisioned,integrating Autopilot and energy-saving control.