Driving pressure decoded:Precision strategies in adult respiratory distress syndrome management

Mechanical ventilation(MV)is an important strategy for improving the survival of patients with respiratory failure.However,MV is associated with aggravation of lung injury,with ventilator-induced lung injury(VILI)becoming a major concern.Thus,ventilation protection strategies have been developed to minimize complications from MV,with the goal of relieving excessive breathing workload,improving gas exchange,and minimizing VILI.By opting for lower tidal volumes,clinicians seek to strike a balance between providing adequate ventilation to support gas exchange and preventing overdistension of the alveoli,which can contribute to lung injury.Additionally,other factors play a role in optimizing lung protection during MV,including adequate positive end-expiratory pressure levels,to maintain alveolar recruitment and prevent atelectasis as well as careful consideration of plateau pressures to avoid excessive stress on the lung parenchyma.

Study on Steering Control Strategy for High-Speed Tracked Vehicle with Hydrostatic Drive

Steering control strategy for high-speed tracked vehicle with hydrostatic drive is designed based on analyzing the fundamental steering theories of the hydrostatic drive tracked vehicle. The strategy is completed by the cooperation between integrated steering control unit and pump ＆ motor displacement controller. The steering simulation is conducted by using Simulink of Matlab. It is indicated that this steering control strategy can reduce the average vehicle speed automatically to achieve the driver＇s expected steering radius exactly in the case of en- suring not exceeding the system pressure threshold and no sideslip.

Mode switching control strategy of dual motors coupled driving on electric vehicles

Based on analyzing the structure and working principle on electric vehicles （EVs） with dual motors coupled by planetarY gears, the control strategy of mode switching was proposed. The power interruption problem on EVs with automatic mechanical transmission （AMT） shifting was resolved. Based on the speed-torque characteristics of the planetary gears and the principle of the auxiliary motor＇ s zero speed braking, control features of mode switching were introduced. The mode shifting between the main motor mode and dual motors coupled driving were studied. Matlab/Simulink was adopted as a platform to develop the simulation model of EVs with dual motors drive system and 3 gears AMT. Simulation results demonstrated that the power interruption of dual motors drive system was solved during mode switching. The power requirements of EVs were satisfied, too.

Realizing high-performance organic solar cells through precise control of HOMO driving force based on ternary alloy strategy

A good deal of studies have proven that effective exciton dissociation and fast hole transport can operate efficiently in non-fullerene organic photovoltaics(OPVs)despite nearly zero driving force.Even so,whether such a phenomenon is universal and how small the driving force can realize the best photovoltaic performance still require a thorough understanding.Herein,despite the zero driving force based on PM6:F8IC system,a maximum short-circuit current(J_(sc))of 23.0 mA/cm^(2) and high power conversion efficiency(PCE)of 12.2%can still be achieved.Due to the continuously adjustable energy levels can be realized in organic semiconducting alloys including F8IC:IT-4F and F8IC:Y6,the suitable third components can play the role of energy level regulator.Therefore,the HOMO energy level offset(DEHOMO(D A))from zero to 0.07 and 0.06 eV is accomplished in the optimized IT-4F and Y6 ternary devices.Consequently,both ternary devices achieved substantially increased PCE of 13.8%and Jsc of 24.4 and 25.2 mA/cm^(2),respectively.Besides,pseudo-planar heterojunction(PPHJ)devices based on alloyed acceptors through sequential spin-coating method further improve the photovoltaic performance.Our work puts forward the concept of energy level regulator and prove that the ternary alloy strategy has unique advantages and huge research potential in continuously adjusting the driving force.

Genetic-fuzzy HEV control strategy based on driving cycle recognition

A genetic-fuzzy HEV control strategy based on driving cycle recognition （DCR） was built. Six driving cycles were selected to represent different traffic conditions e.g. freeway, urban, suburb. A neural algorithm was used for traffic condition recognition based on ten parameters of each driving cycle. The DCR was utilized for optimization of the HEV control parameters using a genetic-fuzzy approach. A fuzzy logic controller （FLC） was designed to be intelligent to manage the engine to work in the vicinity of its optimal condition. The fuzzy membership function parameters were optimized using the genetic algorithm （GA） for each driving cycle. The result is that the DCR_ fuzzy controller can reduce the fuel consumption by 1. 9%, higher than only CYC _ HWFET optimized fuzzy （0.2%） or CYC _ WVUSUB optimized fuzzy （0.7%）. The DCR_ fuzzy method can get the better result than only optimizing one cycle on the complex real traffic conditions.

A Driving Strategy Model of Self-Driving Cars

The self-driving cars are highly developed and about to meet the market, but the driving strategies and corresponding behaviors with others still need to be tested. In this paper, based on its characteristics and behaviors of manual-driving vehicles, we propose the driving strategies of manual-driving cars as well as self-driving cars. And we use the cellular automaton to simulate the traffic reality under different conditions, and to evaluate the efficiency of a road when self-driving cars are put into use. This research can be a reference by traffic planning and vehicles performance test, and further research can be designed in a model which can calculate the efficiency of a road when the percentage of self-driving cars are different.

Dynamic model and driving strategy of corporate social responsibility

Corporate social responsibility is the inevitable requirement for the survival and development of enterprises in modern society,as well as the basic guarantee for the sustainable development of economy and society.In order to analyze the driving factors of corporate social responsibility from both internal and external aspects,the dynamic model of corporate social responsibility was constructed,and the driving strategies of corporate social responsibility were also suggested.The driving factors of corporate social responsibility include not only the external constraints of policies,regulations and stakeholders,but also the internal requirements of the sustainable development of enterprises.Only when the external driving force is transformed into the spontaneous and conscious responsibility behavior of the enterprise,can the enterprise achieve its due effect.Moreover,in order to better fulfill the social responsibility,enterprise should build a management system of social responsibility,enhance the awareness of social responsibility,and promote the effective implementation of social responsibility projects.The relevant department should strengthen the all-round supervision of corporate social responsibility,and further improve the policies,laws and regulations related to social responsibility.Enterprises should strengthen communication with stakeholders,actively disclose social responsibility information,and constantly improve social responsibility behavior.By implementing social responsibility,enterprise can improve its business environment,enhance corporate brand image and core competitiveness,and promote the sustainable development of economy and society.

Optimization and implementation strategy of ESCO driving force in the development of energy-saving transformation market of existing buildings

The development of the existing building energy-saving transformation market is inseparable from the internal driving force of ESCO.Giving full play to the driving role of ESCO scientifically is the internal requirement to promote the healthy and orderly operation of the existing building energy-saving transformation market.This paper summarizes the practical experience of developing ESCO driving force operation in foreign existing building energy-saving transformation market,analyzes the bottleneck of developing ESCO driving force operation in China’s existing building energy-saving transformation market,and puts forward useful practical enlightenment based on the comparison between home and abroad;According to the optimization principle of ESCO driving force operation in the development of existing building energy-saving transformation market,the optimization design framework of ESCO driving force is proposed,and the implementation strategy of ESCO driving force optimization in the development of existing building energy-saving transformation market is planned.In order to optimize and improve the effectiveness of the operation and development of the energy-saving transformation market of existing buildings with the internal driving force of ESCO.

The Driving Strategy of Online Ideological and Political Class in Universities Based on SWOT Analysis

The epidemic provided practical opportunities for online classes and also tested its drawbacks. To analyze the internal strengths (S) and weaknesses (W) as well as the external opportunities (O) and threats (T) of the online ideological and political class with SWOT theory, based on which to explore targeted solutions, is a “symptomatic” approach to improving the quality of the online ideological and political class. The analysis results are as follows: S includes “not limited by time and space”, “comprehensive teaching monitoring data”, “diverse and innovative interactive forms”, and “abundant high-quality teaching resources”. W refers to “increased difficulty in classroom control”, “teachers’ psychological pressure caused by online teaching”, and “limited by hardware conditions”. O means the opportunity provided by the modernization of ideological and political education and epidemics. T indicates external threats, such as limitations from the network and the severe impact of wrong values on the internet. The driving strategy for above case could be “upgrading of online teaching platforms”, “building a teaching team skilled in information technology teaching”, “improving hardware facilities” and “joining forces to confront value crisis”.

基于GT-drive的整车控制策略研究

将国内某款乘用车改装成插电式混合动力汽车(PHEV),对其中整车控制策略进行研究设计.根据不同工况控制需求,设计出整车唤醒、动力控制、制动能量回收等策略.应用仿真软件GTdrive进行仿真分析.结果表明,设计的控制策略满足车辆设计指标,以电为主的控制策略下油耗为3.92L·(100km)^(-1),相比较原车型节油48.5%.同时在FTP75工况模拟运行中,很好的实现能量在发动机和电机之间的分配.

Strategy to control crawling vehicles with automated mechanical transmission

In order to move vehicles with automated mechanical transmission （AMT） a little bit of distance, such as reversing into or moving in a garage, a control strategy for crawling vehicles was proposed. Based on the dynamic analysis of vehicle starting process and requirements of crawl driv- ing for the vehicle, a control strategy of the clutch was designed. The strategy increased the.slipping friction torque first and then decreased it, in order to realize the crawl driving. The speed increased by the engagement of the clutch, and then the clutch turned to disengage to the half disengage point, when the speed met the requirements. Based on the control strategy, a control software was de- signed. In the end, the software was tested on a vehicle with AMT. The lowest steady vehicle speed was reduced to 40% of the original value, which was set in the control strategy.

Simulation of automobile fuel consumption and emissions for various driver's manual shifting habits

The effects of different habits of the drivers on gear shifting strategies for manual powertrain were investigated. For the realization of simulation, the shifting habits of the drivers were conducted in the Advisor software to investigate and compare the emission rates. Simulation was developed based on the optimal gear shifting strategy and criteria and was validated both in fuel economy and emissions by analyzing the results in the various driving cycle and driving styles. To explore an optimal gear shifting strategy with best fuel economy and lowest emission for a manual transmission, a strategy was designed with a highest possible gear criterion as long as the torque requirement can be satisfied. Based on two different criteria, namely the engine working conditions and the driver's intention, the governing parameters in decision making for gear shifting of manual transmission in conventional engine were discussed. It is also shown that the optimum gear shifting strategy is based on that both the engine state and the driver's intention eliminates unnecessary shiftings that are present when the intention is overlooked. The optimum shifting habit and the best driving cycle in terms of minimum emissions and fuel consumption were proposed.

A Digital Phase Locked Loop Speed Control of Three Phase Induction Motor Drive: Performances Analysis

This paper deals with performance analysis and implementation of a three phase inverter fed induction motor (IM) drive system. The closed loop control scheme of the drive utilizes the Digital Phase Locked Loop (DPLL). The DPLL is safely implemented all around the well known integrated circuit DPLL 4046. An ex-perimental verification is carried out on one kw scalar controlled IM system drives for a wide range of speeds and loads appliance. This presents a simple and high performance solution for industrial applications.

Slow driving control of tracked vehicles with automated mechanical transmission based on fuzzy logic

In order to move tracked vehicles at an extremely slowspeed with automated mechanical transmission（ AMT）,slowdriving function was added in the original system. The principle and requirement of slowdriving function were analyzed. Based on analysis of slow driving characteristic,identification of slowdriving condition and fuzzy control algorithm,a control strategy of the clutch was designed. In order to realize slowdriving,the clutch was controlled in a slipping mode as manual driving. The vehicle speed was increased to a required speed and kept in a small range by engaging or disengaging the clutch to the approximate half engagement point. Based on the control strategy,a control software was designed and tested on a tracked vehicle with AMT. The test results showthat the control of the clutch with the slowdriving function was smoother than that with original systemand the vehicle speed was slower and steadier.

急倾斜深埋巨厚煤层掘巷冲击地压前兆特征及其灾害防治

随着冲击地压矿井逐渐向深开采,其巷道掘进伴随的冲击显现愈发强烈。针对巷道掘进过程中的冲击地压有效防治问题,以新疆乌东煤矿急倾斜煤层矿井为例,运用微震监测对巷道掘进的冲击地压时空前兆特征加以分析。结合巷道掘进的应力与能量变化数值模拟分析,揭示巷道掘进的冲击地压发生机理,提出急倾斜巨厚煤层巷道冲击地压防治策略,并完成现场工程实践验证。研究结果表明:急倾斜巨厚煤层巷道掘进的冲击地压发生前第2~5天出现微震总能量极低值,或存在至少4 d的能量潜伏期;冲击地压发生前5 d普遍存在3 d以上的最大能量占比高频波动期。冲击地压发生前存在明显缺震现象,发生位置集中分布在距离掘进工作面较近的微震能量极小值区间范围内,或位于微震能量极值区间附近的微震频次极小值区间范围内,且冲击地压事件位于冲击变形能指数较高区域。急倾斜巨厚煤层水平分段综放开采的坚硬覆岩结构不易破断,使得巷道掘进存在上水平采空区两侧“双翼型”应力集中,掘进工作面前方与巷道底部受顶底板岩层相互挤压的应力集中分布且能量积聚显著,随着巷道掘进深度增加其应力集中与能量积聚进一步增强,容易诱发冲击地压等动力灾害。综合分析形成急倾斜巨厚煤层巷道掘进的工作面爆破卸压、巷道钻孔卸压与补强支护、复杂区域架蓬的冲击地压防治策略。结合冲击地压时空前兆异常为及时加强卸压力度提供时机。通过工作面与巷道卸压使得掘进期间未发生单日累计1×105 J以上微震能量,在对支护优化调整与复杂区域重点防护后,巷道掘进日均微震能量降至2.2 kJ,其1 kJ以上微震事件占比下降且巷道断面整体平整。研究结果为急倾斜巨厚煤层巷道安全掘进提供了科学依据。

针对自动驾驶智能模型的攻击与防御

近年来,以深度学习算法为代表的人工智能技术为人类生产生活的方方面面带来了巨大的革新,尤其是在自动驾驶领域,部署着自动驾驶系统的智能汽车已经走进入们的生活,成为了重要的生产力工具.然而,自动驾驶系统中的人工智能模型面临着潜在的安全隐患和风险,这给人民群众生命财产安全带来了严重威胁.本文通过回顾自动驾驶智能模型攻击和防御的相关研究工作,揭示自动驾驶系统在物理世界下面临的安全风险并归纳总结了相应的防御对策.具体来说,本文首先介绍了包含攻击面、攻击能力和攻击目标的自动驾驶系统安全风险模型.其次,面向自动驾驶系统的三个关键功能层——传感器层、感知层和决策层,本文依据受攻击的智能模型和攻击手段归纳、分析了对应的攻击方法以及防御对策,并探讨了现有方法的局限性.最后,本文讨论和展望了自动驾驶智能模型攻击与防御技术面临的难题与挑战,并指出了未来潜在的研究方向和发展趋势.

融合工况预测的燃料电池汽车里程自适应等效氢耗最小控制策略

为有效地提高插电式燃料电池汽车的经济性,实现燃料电池和动力电池的功率最优分配,考虑到行驶工况、电池荷电状态(State of charge,SOC)、等效因子与氢气消耗之间的密切联系,制定融合工况预测的里程自适应等效氢耗最小策略.通过基于误差反向传播的神经网络来实现未来短期车速的预测,分析未来车辆需求功率变化,同时借助全球定位系统规划一条通往目的地的路径,智能交通系统便可获取整个行程的交通流量信息,利用行驶里程和SOC实时动态修正等效消耗最小策略中的等效因子,实现能量管理策略的自适应性.基于MATLAB/Simulink软件,搭建整车仿真模型与传统的能量管理策略进行仿真对比验证.仿真结果表明,采用基于神经网络的工况预测算法能够较好地预测未来短期工况,其预测精度相较于马尔可夫方法提高12.5%,所提出的能量管理策略在城市道路循环工况(UDDS)下的氢气消耗比电量消耗维持(CD/CS)策略下降55.6%.硬件在环试验表明,在市郊循环工况(EUDC)下的氢气消耗比CD/CS策略下降26.8%,仿真验证结果表明了所提出的策略相比于CD/CS策略在氢气消耗方面的优越性能,并通过硬件在环实验验证了所提策略的有效性.

考虑驾驶风格的混合动力汽车强化学习能量管理策略

为了提升混合动力汽车能量管理策略对不同风格驾驶员的适应性,基于深度强化学习和等效燃油消耗最小策略(equivalent consumption minimization strategy,ECMS),提出一种考虑驾驶风格的混合动力汽车能量管理策略。通过实车试验采集驾驶员行驶数据,基于采集数据进行驾驶员驾驶风格的聚类分析,建立驾驶风格识别模型;构建基于强化学习和ECMS的能量管理策略,将驾驶风格系数作为强化学习状态变量,利用多种驾驶风格的组合工况训练深度确定性策略梯度智能体,获取不同工况和驾驶风格下ECMS等效因子,采用ECMS求解最优发动机、电机转矩分配以及变速箱挡位;搭建硬件在环测试平台,并基于实际采集的不同驾驶员驾驶数据构建测试工况,验证所提出控制策略的有效性。研究结果表明,相较于基于规则策略、基于等效因子比例修正的自适应ECMS以及DRL-SAC策略,提出的考虑驾驶风格的强化学习能量管理策略使整车能量消耗分别降低16.35%、11.11%和7.56%,所提控制策略的有效性得到了验证。

周车轨迹预测不确定性智能车避撞策略研究

提出了一种基于周车轨迹预测不确定性的智能汽车避撞策略研究方法。轨迹预测模块,将基于物理的轨迹预测模型和数据驱动模型相结合构建物理引导的轨迹预测模型(PG-LSTM),模型输出关于周车预测轨迹的二维高斯分布参数,以表征驾驶员行为的不确定性;风险评估及避撞策略模块,结合轨迹预测模型的输出结果,提出一个新的风险度量--预测驾驶风险PDR和预测相对驾驶风险指数PRDRI作为评估未来风险的参考指标,建立紧急工况下避撞决策机制。通过Carsim搭建复杂紧急工况场景进行仿真实验。仿真结果表明:所提出的驾驶风险评估模型可以准确地辨识复杂行车场景未来驾驶风险,同时基于驾驶风险所提出的避撞决策机制能够提升智能汽车的避撞安全性。

基于模糊评判决策的天然气驱油藏开发效果评价

注天然气提高采收率有着良好的应用前景,但目前针对天然气驱油藏缺乏相对应的开发效果评价指标体系及标准,无法对开发效果进行正确、客观、科学的评价。根据油田开发行业标准、水驱和CO_(2)混相驱开发效果评价指标体系,筛选出了评价天然气驱油藏开发效果的10项评价指标:采收率提高幅度、换油率、增产倍比、储量动用程度、储量控制程度、压力保持水平、存气率、气油比增长倍数、阶段注采比及注气时机。结合W天然气驱油藏的地质特征、生产动态以及注气开发特点,建立了天然气驱开发效果评价指标体系及评价标准。应用层次分析法、模糊变换原理和最大隶属度原则建立了基于模糊综合评判决策的天然气驱油藏开发效果评价方法,将传统的单指标、定性开发效果评价转化为多因素、定量的开发效果评价。应用实例表明,该天然气驱开发效果评价指标体系及评价方法具有可行性和有效性,对同类型天然气驱油藏开发效果的评价具有一定的指导意义。