An adaptive sliding mode observer based near-optimal OER tracking control approach for PEMFC under dynamic operation condition

Tracking control of oxygen excess ratio (OER) is crucial for dynamic performance and operating efficiency of the proton exchange membrane fuel cell (PEMFC). OER tracking errors and overshoots under dynamic load limit the PEMFC output power performance, and also could lead oxygen starvation which seriously affect the life of PEMFC. To solve this problem, an adaptive sliding mode observer based near-optimal OER tracking control approach is proposed in this paper. According to real time load demand, a dynamic OER optimization strategy is designed to obtain an optimal OER. A nonlinear system model based near-optimal controller is designed to minimize the OER tracking error under variable operation condition of PEMFC. An adaptive sliding mode observer is utilized to estimate the uncertain parameters of the PEMFC air supply system and update parameters in near-optimal controller. The proposed control approach is implemented in OER tracking experiments based on air supply system of a 5 kW PEMFC test platform. The experiment results are analyzed and demonstrate the efficacy of the proposed control approach under load changes, external disturbances and parameter uncertainties of PEFMC system.     

Shared human–robot path following control of an unmanned ground vehicle

This paper considers the shared path following control of an unmanned ground vehicle by a single person. A passive measure of human intent is used to blend the human and machine inputs in a mixed initiative approach. The blending law is combined with saturated super-twisting sliding mode speed and heading controllers, so that exogenous disturbances can be counteracted via equivalent control. It is proven that when the proposed blending law is used, the combined control signals from both the human and automatic controller respect the actuator magnitude constraints of the machine. To demonstrate the approach, shared control experiments are performed using an unmanned ground vehicle, which follows a lawn mower pattern shaped path.     

机械合金化FeS/Cu复合材料的摩擦磨损性能

以FeS和CuSn8Ni1粉末为原料，利用机械合金化技术和粉末冶金技术制备了FeS/Cu复合材料，探讨了不同载荷情况下所制备的FeS/Cu复合材料的摩擦学性能及润滑膜与转移膜特征。结果表明：机械合金化提高了FeS与铜合金基体界面结合性能，进而提高了材料减摩耐磨性能；当载荷较小时，摩擦副表面接触不稳定，复合转移膜不连续，摩擦因数波动大；载荷较大时，复合转移膜易破损，材料的减摩耐磨性能变差；当载荷为150 N时，载荷适宜，材料表面软化，复合转移膜更加完整，摩擦因数较小。     

转载溜槽衬板磨损预测的DEM仿真方法

针对EDEM自动划分网格较稀疏问题,采用Hypermesh划分仿真模型网格,利用Herz-Mindlin接触理论的Archard磨损模型对转载溜槽磨损问题进行仿真,在网格单元上提取出漏斗和溜管衬板的接触能量和磨损量,分析了磨损量与接触能量的关系。假设转载溜槽衬板磨损深度为物料与溜槽衬板的使用时间为线性函数,根据现场衬板磨损量的测量值,将衬板的磨损系数关系的看作隐式的单变量方程,应用EDEM软件的仿真结果求解出磨损系数的标定值。分析了漏斗和溜管的磨损机理。该方法可用于转载溜槽的磨损预测。     

磁悬浮控制力矩陀螺高速转子的高精度位置控制

在受到陀螺效应、动框架效应等影响后产生的磁力非线性问题是磁悬浮控制力矩陀螺(MSCMG)高速转子位置精度下降的主要因素。为解决以上问题,提高转子位置精度,本文分析了转子所受磁力的特性,建立了转子系统非线性动力学模型,提出了神经网络滑模控制方法。设计滑模控制律,采用径向基函数神经网络逼近控制律中的非线性模型,自适应算法根据误差在线调整神经网络的权值,同时可以保证整个系统的稳定性。仿真和实验结果表明,所提出方法的转子位置精度达到99%,稳态误差为0.000 2 mm。神经网络滑模控制可以实现MSCMG转子系统的高精度位置控制。     

刮板输送机中板仿生耐磨优化试验研究

刮板输送机中板磨损失效已成为输送机运行故障的主要原因之一，为了提高中板耐磨性，基于蜣螂非光滑单元进行了仿生中板设计，以磨损量为响应值，进行了单因素和响应面法优化试验。根据响应面法试验结果得到的因素显著性影响顺序（从高至低）依次为：径向距离，深径比，直径，节距角。基于试验结果建立了磨损量与因素的回归预测模型，经试验对比发现，预测模型与真实试验的相对误差为3.2%。在特定工况（煤散料粒度为6~8 mm、载荷为20 N、刮板链速为0.65 m/s及试验时长为6 600 s）下，当深径比为1.41、直径为0.69 mm、节距角为6.55°和径向距离为4.66 mm时，磨损量最小，仿生中板的耐磨性提高了12.6%。分析其耐磨机理发现，与光滑板相比，仿生板的磨粒磨损及黏着磨损较轻。凹坑分布可破坏持续切削中板表面的煤粒运动状态。中板的仿生优化可为今后刮板输送机的设计提供一定参考。     

水泥窑余热发电系统用耐磨材料的研制与应用

本研究针对水泥窑余热发电系统的工作条件,根据耐磨材料的损毁机理,采用高铝矾土、煅烧氧化铝粉、黏土、硅微粉等为原料,以磷酸二氢铝为结合剂,以铝酸钙水泥为促硬剂,通过添加掩蔽剂和优化配料工艺,制备了水泥窑余热发电系统用耐磨材料,并对不同处理温度对耐磨材料的性能影响进行了分析。结果表明增强骨料与基质的结合能力有利于耐磨性的提高,磷酸及磷酸盐与氧化铝之间会随着温度的升高生成不同的磷酸铝相,都能够起到结合作用,比采用水泥结合更有利于提高材料在不同温度下的强度和耐磨性。使用结果表明,制备的耐磨材料施工性能优良,凝结硬化时间适当,强度高,抗冲刷性能好,在水泥窑余热发电系统中取得了良好的使用效果。     

Φ177mm PQF无缝管连轧机前横移系统改进

对鞍钢股份无缝钢管厂连轧机前毛管坯横移装置存在的设计缺陷进行了分析,并提出改进方案,将原横移装置由高架轨道横移机构及上下升降链传动装置,改进为地面轨道横移系统及同步旋转臂实现取管、放管过程。实施后消除了生产故障,缩短了轧制周期,降低生产成本。     

The effects of surface-modified graphene nanoplatelets on the sliding wear properties of basalt fibers-reinforced epoxy composites

Possessing unique designs and properties absent in conventional materials, nanocomposites have made a remarkable imprint in science and technology. This is particularly true regarding the polymer matrix composites when they are further reinforced with nanoparticles. In this study, the effects of different weight percentages (0, 0.1, 0.2, 0.3, 0.4, and 0.5) of surface-modified graphene nanoplatelets (GNPs) on the microhardness and wear properties of basalt fibers/epoxy composites were investigated. The GNPs were surface modified by silane, and the composites were made by the hand lay-up method. The wear tests were conducted under two different loads of 20 and 40 N. The best wear properties were achieved at 0.3 wt % GNPs as a result of the GNPs' self-lubrication property and the formation of a stable transfer/lubricating film at the pin and disk interface. Moreover, the friction coefficient was lower at the higher normal load of 40 N. The microscopic studies by FESEM and SEM showed that the presence of GNPs up to 0.3 wt % led to the stability of the transfer/lubricating film by enhancing the adhesion of the basalt fibers to the epoxy resin. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47986.