Enhanced Deep Reinforcement Learning Strategy for Energy Management in Plug-in Hybrid Electric Vehicles with Entropy Regularization and Prioritized Experience Replay

Plug-in Hybrid Electric Vehicles(PHEVs)represent an innovative breed of transportation,harnessing diverse power sources for enhanced performance.Energy management strategies(EMSs)that coordinate and control different energy sources is a critical component of PHEV control technology,directly impacting overall vehicle performance.This study proposes an improved deep reinforcement learning(DRL)-based EMSthat optimizes realtime energy allocation and coordinates the operation of multiple power sources.Conventional DRL algorithms struggle to effectively explore all possible state-action combinations within high-dimensional state and action spaces.They often fail to strike an optimal balance between exploration and exploitation,and their assumption of a static environment limits their ability to adapt to changing conditions.Moreover,these algorithms suffer from low sample efficiency.Collectively,these factors contribute to convergence difficulties,low learning efficiency,and instability.To address these challenges,the Deep Deterministic Policy Gradient(DDPG)algorithm is enhanced using entropy regularization and a summation tree-based Prioritized Experience Replay(PER)method,aiming to improve exploration performance and learning efficiency from experience samples.Additionally,the correspondingMarkovDecision Process(MDP)is established.Finally,an EMSbased on the improvedDRLmodel is presented.Comparative simulation experiments are conducted against rule-based,optimization-based,andDRL-based EMSs.The proposed strategy exhibitsminimal deviation fromthe optimal solution obtained by the dynamic programming(DP)strategy that requires global information.In the typical driving scenarios based onWorld Light Vehicle Test Cycle(WLTC)and New European Driving Cycle(NEDC),the proposed method achieved a fuel consumption of 2698.65 g and an Equivalent Fuel Consumption(EFC)of 2696.77 g.Compared to the DP strategy baseline,the proposed method improved the fuel efficiency variances(FEV)by 18.13%,15.1%,and 8.37%over the Deep QNetwork(DQN),Double DRL(DDRL),and original DDPG methods,respectively.The observational outcomes demonstrate that the proposed EMS based on improved DRL framework possesses good real-time performance,stability,and reliability,effectively optimizing vehicle economy and fuel consumption.

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.

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.

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%.

Overview of the immunological mechanisms in hepatitis B virus reactivation:Implications for disease progression and management strategies

Hepatitis B virus(HBV)reactivation is a clinically significant challenge in disease management.This review explores the immunological mechanisms underlying HBV reactivation,emphasizing disease progression and management.It delves into host immune responses and reactivation’s delicate balance,spanning innate and adaptive immunity.Viral factors’disruption of this balance,as are interac-tions between viral antigens,immune cells,cytokine networks,and immune checkpoint pathways,are examined.Notably,the roles of T cells,natural killer cells,and antigen-presenting cells are discussed,highlighting their influence on disease progression.HBV reactivation’s impact on disease severity,hepatic flares,liver fibrosis progression,and hepatocellular carcinoma is detailed.Management strategies,including anti-viral and immunomodulatory approaches,are critically analyzed.The role of prophylactic anti-viral therapy during immunosuppressive treatments is explored alongside novel immunotherapeutic interventions to restore immune control and prevent reactivation.In conclusion,this compre-hensive review furnishes a holistic view of the immunological mechanisms that propel HBV reactivation.With a dedicated focus on understanding its implic-ations for disease progression and the prospects of efficient management stra-tegies,this article contributes significantly to the knowledge base.The more profound insights into the intricate interactions between viral elements and the immune system will inform evidence-based approaches,ultimately enhancing disease management and elevating patient outcomes.The dynamic landscape of management strategies is critically scrutinized,spanning anti-viral and immunomodulatory approaches.The role of prophylactic anti-viral therapy in preventing reactivation during immunosuppressive treatments and the potential of innovative immunotherapeutic interventions to restore immune control and proactively deter reactivation.

Factors affecting farmers'choice to adopt risk management strategies:The application of multivariate and multinomial probit models

This study investigates the factors that impact farmers'adoption of risk management strategies(RMS)in Pakistan during times of uncertainty.The study examines farmers'adoption of RMS using both multinomial probit(MNP)and multivariate probit(MVP).Data were collected from 382 farmers sampled from four districts in KhyberPakhtunkhwa(KP)province of Pakistan via a multistage sampling technique.This study utilizes the MNP model,considering the assumption of Independence of Irrelevant Alternatives(IIA)and incorporating correlated error terms.The objective is to understand farmers'behavior in risky situations and determine if there is heterogeneity.Results are compared with the MVP model to assess robustness and gain deeper understanding of farmers'decisionmaking processes.The research findings reveal that our results are robust,and farmers behave homogeneously in various RMS scenarios.Farmers adopt RMS individually or in combination to mitigate the adverse effects of natural calamities on their livelihood.The risk-averse farmers,who perceive weather-related risks as a threat,access credits and information,and have farms close to a river are more likely to adopt RMS,irrespective of the format of the strategies available.Moreover,the predicted probabilities and correlation of the RMS and RM categories have strengthened our model estimation.These findings provide insights into the behavior of farmers in adopting RMS which are helpful for policymakers and stakeholders in developing strategies to mitigate the impacts of natural calamities on farmers.

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.

Ibrutinib and atrial fibrillation:An in-depth review of clinical implications and management strategies

Ibrutinib,a targeted therapy for B-cell malignancies,has shown remarkable efficacy in treating various hematologic cancers.However,its clinical use has raised concerns regarding cardiovascular complications,notably atrial fibrillation(AF).This comprehensive review critically evaluates the association between ibrutinib and AF by examining incidence,risk factors,mechanistic links,and management strategies.Through an extensive analysis of original research articles,this review elucidates the complex interplay between ibrutinib’s therapeutic benefits and cardiovascular risks.Moreover,it highlights the need for personalized treatment approaches,vigilant monitoring,and interdisciplinary collaboration to optimize patient outcomes and safety in the context of ibrutinib therapy.The review provides a valuable resource for healthcare professionals aiming to navigate the intricacies of ibrutinib’s therapeutic landscape while prioritizing patient well-being.

A Predictive Energy Management Strategies for Mining Dump Trucks

The plug-in hybrid vehicles(PHEV)technology can effectively address the issues of poor dynamics and higher energy consumption commonly found in traditional mining dump trucks.Meanwhile,plug-in hybrid electric trucks can achieve excellent fuel economy through efficient energy management strategies(EMS).Therefore,a series hybrid system is constructed based on a 100-ton mining dump truck in this paper.And inspired by the dynamic programming(DP)algorithm,a predictive equivalent consumption minimization strategy(P-ECMS)based on the DP optimization result is proposed.Based on the optimal control manifold and the SOC reference trajectory obtained by the DP algorithm,the P-ECMS strategy performs real-time stage parameter optimization to obtain the optimal equivalent factor(EF).Finally,applying the equivalent consumption minimization strategy(ECMS)realizes real-time control.The simulation results show that the equivalent fuel consumption of the P-ECMS strategy under the experimentally collected mining cycle conditions is 150.8 L/100 km,which is 10.9%less than that of the common CDCS strategy(169.3 L/100 km),and achieves 99.47%of the fuel saving effect of the DP strategy(150 L/100 km).

Analysis of International Cooperation Management Strategies of Enterprises under the Background of the“Belt and Road”

With the deepening of the“Belt and Road”initiative,Chinese enterprises are facing unprecedented opportunities and challenges for international cooperation.This paper mainly analyzes the current situation,existing problems,and coping strategies of enterprise international cooperation management in the context of the“Belt and Road”.This article expounds on the importance of the“Belt and Road”initiative for international cooperation of enterprises and analyzes the key links of international cooperation management of enterprises from the aspects of internationalization strategy,cross-cultural management,risk prevention and control,and resource integration.Finally,combined with the case,this paper puts forward the management strategies and suggestions that enterprises should adopt in international cooperation,to provide a useful reference for Chinese enterprises in international cooperation in the construction of the“Belt and Road.”

Impact of skin sensitivity mechanisms on sebum secretion: Management strategies for oily sensitive skin

Recent epidemiological surveys based on Baumann's classification have revealed a notable rise in the prevalence of oily sensitive skin.The development of oily sensitive skin is primarily linked to the abnormal function of sebaceous glands.The function of sebaceous glands is regulated by several factors,including inflammatory mediators,neurotransmitters,and endocrine signals.Sensitive skin,particularly oily sensitive skin,is prone to local inflammation,which in turn disrupts the normal functioning of sebaceous glands.This creates a loop wherein increased oil production exacerbates sensitivity,while heightened sensitivity further stimulates sebum secretion,perpetuating a vicious cycle.This article summarizes our understanding of the four primary mechanisms underlying skin sensitivity and their impact on sebaceous gland activity.Accordingly,it proposes management strategies for oily sensitive skin and seeks to guide the development of skin care regimens for this skin type.

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.

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.

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.

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.

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.