Real time power management strategy for fuel cell hybrid electric bus based on Lyapunov stability theorem

The fuel cell/battery durability and hybrid system stability are major considerations for the power management of fuel cell hybrid electric bus (FCHEB) operating on complicated driving conditions. In this paper, a real time nonlinear adaptive control (NAC) with stability analyze is formulated for power management of FCHEB. Firstly, the mathematical model of hybrid power system is analyzed, which is established for control-oriented design. Furthermore, the NAC-based strategy with quadratic Lyapunov function is set up to guarantee the stability of closed-loop power system, and the power split between fuel cell and battery is controlled with the durability consideration. Finally, two real-time power management strategies, state machine control (SMC) and fuzzy logic control (FLC), are implemented to evaluate the performance of NAC-based strategy, and the simulation results suggest that the guaranteed stability of NAC-based strategy can efficiently prolong fuel cell/battery lifespan and provide better fuel consumption economy for FCHEB.     

高面板坝全寿命周期变形控制方法及应用

高面板坝的变形对面板的安全运行有着特别重要的影响，国内外已建的高面板坝工程中，因坝体变形大导致防渗面板挤压破损，坝体渗漏量大的实例较多，不得不降低水库水位进行修复处理，造成较大的经济损失乃至给大坝的长期运行留下安全隐患。通过发生挤压破损的实例分析，发现变形控制缺乏系统性是发生面板挤压破损的主要因素，为预防面板破损，系统提出了“控制坝体总变形，转化有害变形，适应纵向变形”的坝体变形控制方法，并在使用软硬岩混合料筑坝的董箐面板堆石坝中得到的应用，取得了良好效果，该工程运行至今达十余年，未见面板有挤压破损迹象，该方法对建设200 m以上乃至300 m级超高面板坝具有重要借鉴意义。     

A high-throughput chaotic advection microreactor for preparation of uniform and aggregated barium sulfate nanoparticles

A high-throughput (105.5 g/h) passive four-stage asymmetric oscillating feedback microreactor using chaotic mixing mechanism was developed to prepare aggregated Barium sulfate (BaSO₄) particles of high primary nanoparticle size uniformity. Three-dimensional unsteady simulations showed that chaotic mixing could be induced by three unique secondary flows (i.e., vortex, recirculation, and oscillation), and the fluid oscillation mechanism was examined in detail. Simulations and Villermaux–Dushman experiments indicate that almost complete mixing down to molecular level can be achieved and the prepared BaSO₄ nanoparticles were with narrow primary particle size distribution (PSD) having geometric standard deviation, σ_g, less than 1.43 when the total volumetric flow rate Q_total was larger than 10 ml/min. By selecting Q_total and reactant concentrations, average primary particle size can be controlled from 23 to 109 nm as determined by microscopy. An average size of 26 nm with narrow primary PSD (σ_g = 1.22) could be achieved at Q_total of 160 ml/min.     

Optical properties and radiation stability of SiO2/ZnO composite pigment prepared by co-sintering method

Thermal control coatings (TCCs) are an essential part of the thermal control systems in the spacecraft. Solar absorptance and emittance are the key performance parameters of TCCs. To develop an ultra-low solar absorption and stable inorganic TCCs for surface radiator, different TCCs were prepared by co-sintering ZnO and SiO₂ nanoparticles to form Zn₂SiO₄/SiO₂ pigment in this work, and the optical properties and radiation stability were systematically studied. It is found that the coating based on composite pigment has high reflectivity in the ultraviolet band and excellent optical performance possessing the low solar absorption of 0.06. In addition, the Zn₂SiO₄/SiO₂ coating demonstrates the highest proton and electron radiation stability because that SiO₂ between Zn₂SiO₄ particles acts as the relaxation center of the defects caused by radiation.     

Comprehensive numerical investigations on the thermal performance of heat recirculating micro combustor with pin fins for micro-thermal voltaic system applications

Aiming at improving the relatively low energy output and energy conversion efficiency of the micro-thermal voltaic (MTPV) system, an innovative heat recirculating micro combustor with pin fins is designed. The effects of pin fins arrangement, hydrogen/air equivalent ratio on the energy output and performance of CHMC, HMCP and HMCI are compared and investigated. The result shows that when the V_in is 6 m/s and Φ is 1.0, the emitter power of CHMC is 72.76W, and that of HCMP and HCMI micro combustor are 75.99W and 76.35W. and the emitter efficiency of CHMC, HCMP and HCMI is 41.93%, 43.26% and 44.01%. HMCI has better energy output capability compared with CHMC and HMCP. Even though, HMCI brings a higher pressure drop, it is within the acceptable range. When the V_in is 6 m/s, the pressure drop from the pin fins only accounts for 26.4% of the total pressure drop for HMCI. Through the study of equivalent ratio, it is found that HMCI has good adaptability in different equivalent ratio range. This work provides new ideas for the development of MTPV system in the future.     

浅析深孔爆破施工技术与成本控制的关系

以工程实践为基础,对深孔爆破的成本控制与施工方法、技术的关系进行了探讨。在不规则地形的情况下,有必要通过浅孔爆破进行平台的修正和根底的处理,使深孔台阶爆破处于良性循环中。把握好布孔、验孔、根底处理等主要工艺过程以及防止拒爆,是确保爆破安全、提高爆破质量和有效地控制成本的关键。     

计算机通信及网络远程控制技术的应用与可靠性探究

随着社会的进步和发展,计算机网络通信技术已被应用到实际生活、生产的各个方面,对人们的生活、生产等产生了深刻的影响。为此,文章就计算机通信及网络远程控制技术在实际生活中的应用问题进行了探究,旨在借助先进科技促进社会实现更优质发展。     

关于多功能液压支架拖运车的电控系统设计

本文简介多功能液压支架拖运车的电控系统,包括电控箱的设计和主要电气元件的性能和选择依据。此电控系统能够一般电控系统的各种功能和保护,而且能够通过摄像头做到操作盲区和使用遥控器进行远程控制,从而提高液压支架的拖运效率、降低劳动强度和提高安全保障。     

Convolutional Neural Network Auto Encoder Channel Estimation Algorithm in MIMO-OFDM System

Higher transmission rate is one of the technological features of prominently used wireless communication namely Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO–OFDM). One among an effective solution for channel estimation in wireless communication system, specifically in different environments is Deep Learning (DL) method. This research greatly utilizes channel estimator on the basis of Convolutional Neural Network Auto Encoder (CNNAE) classifier for MIMO-OFDM systems. A CNNAE classifier is one among Deep Learning (DL) algorithm, in which video signal is fed as input by allotting significant learnable weights and biases in various aspects/objects for video signal and capable of differentiating from one another. Improved performances are achieved by using CNNAE based channel estimation, in which extension is done for channel selection as well as achieve enhanced performances numerically, when compared with conventional estimators in quite a lot of scenarios. Considering reduction in number of parameters involved and re-usability of weights, CNNAE based channel estimation is quite suitable and properly fits to the video signal. CNNAE classifier weights updation are done with minimized Signal to Noise Ratio (SNR), Bit Error Rate (BER) and Mean Square Error (MSE).