Design of a thermal management system for a battery pack in an electric vehicle using Dymola

As the world moves toward more green and efficient means of modes of transport, electric vehicles are the most suitable and ideal choice to fulfill this requirement. Rapid developments in the field of battery technology are the main reason for their progress, but thermal management in such systems has been an area of concern for a long time. The work undertaken is to design and develop a battery management system (BMS) with a specific focus on the thermal behavior of the battery pack with varying vehicle loads as well as environmental conditions. To design an efficient BMS, one needs to model the battery behavior covering the thermal as well as electrical aspects of the battery. Apart from the battery model, a mathematical model of the electrical vehicle to mimic the various road load conditions for battery also needs to be modeled. Depending on the need for cooling based on battery behavior, the cooling circuit is modeled for the battery pack used. The entire study has been carried out using Dymola, a mathematical modeling software.     

楼宇型分布式能源系统设备容量和运行策略优化研究

设备容量优化和运行策略优化是分布式能源系统设计，运行的关键问题。为实现分布式能源系统的经济效益，能效水平和环境效益最大化，针对楼宇型分布式能源系统建立了相对普适化的物理模型和数学模型，以粒子群优化算法和线性规划相结合，采用两阶段优化方法计算系统的最优容量配置，并给出运行策略。以某写字楼的分布式能源系统为例，得到最优的系统设备容量和全年逐时运行策略，并采用遍历法验证计算结果的准确性。优化的分布式能源系统与传统供能系统相比，费用年值降低7.79%，年总能耗降低24.18%，污染物排放量减少了62.77 %。     

Fault tolerant system based on non-integers order observers: Application in a heat exchanger

This work presents a fault-tolerant (FT) scheme based on the application of non-integer order observers also called fractional observers, the case of study is a double pipe countercurrent heat exchanger (HE). The aim of the FT is to detect sensors faults as soon as possible, and to provide a healthy signal in order to replace the faulty sensor signal by the fractional observer estimation. To develop the FT scheme a bank of high gain fractional order observers (HGFOO) is proposed. The Riemann-Liouville (RL) fractional derivative definition is used to solve each fractional observer. Experimental measures from a HE were used to test the performance of the fractional observers and the control scheme. The results show the robustness of the proposed observers.     

Design and control of coaxial switching system for ion cyclotron wave resonance heating system of EAST

Ion cyclotron wave resonance heating system(ICRH) which is one of the most important auxiliary system in EAST provides conditions for heating the plasma. In order to make the whole transmission network of ICRH form the required state, the coaxial switching system was developed, which mainly consists of 11 same coaxial switches. Each coaxial switch has a controller with an RS485 communication interface and is able to switch between two states. All controllers are integrated to an RS485 hub which connects to the computer. A master computer software is developed to control the coaxial switching system so as to achieve the state needs of ICRH. Moreover, several rounds of experiments show that the coaxial switching system operates reliably. The coaxial switching system has already been applied to normal use currently.     

Deployment of a cloud pipeline for real-time visual inspection using fast streaming high-definition images

We investigate the challenges of building an end-to-end cloud pipeline for real-time intelligent visual inspection system for use in automotive manufacturing. Current methods of visual detection in automotive assembly are highly labor intensive, and thus prone to errors. An automated process is sought that can operate within the real-time constraints of the assembly line and can reduce errors. Components of the cloud pipeline include capture of a large set of high-definition images from a camera setup at the assembly location, transfer and storage of the images as needed, execution of object detection, and notification to a human operator when a fault is detected. The end-to-end execution must complete within a fixed time frame before the next car arrives in the assembly line. In this article, we report the design, development, and experimental evaluation of the tradeoffs of performance, accuracy, and scalability for a cloud system.     

Design of delayed reconfigurable manufacturing system based on part family grouping and machine selection

To improve the convertibility of reconfigurable manufacturing system (RMS), the concept of delayed reconfigurable manufacturing system (D-RMS) was proposed. RMS and D-RMS are both constructed around part family. However, D-RMS may suffer from ultra-long system problem with unacceptable idle machines using generic RMS part families. Besides, considering the complex basic system structure of D-RMS, machine selection of D-RMS should be addressed, including dedicated machine, flexible machine, and reconfigurable machine. Therefore, a system design method for D-RMS based on part family grouping and machine selection is proposed. Firstly, a part family grouping method is proposed for D-RMS that groups the parts with more former common operations into the same part family. The concept of longest relative position common operation subsequence (LPCS) is proposed. The similarity coefficient among the parts is calculated based on LPCS. The reciprocal value of the operation position of LPCS is adopted as the characteristic value. The average linkage clustering (ALC) algorithm is used to cluster the parts. Secondly, a machine selection method is proposed to complete the system design of D-RMS, including machine selection rules and the dividing point decision model. Finally, a case study is given to implement and verify the proposed system design method for D-RMS. The results show that the proposed system design method is effective, which can group parts with more former common operations into the same part family and select appropriate machine types.     

基于现场监测与数值模拟的浅层采空区稳定性分析

隐患采空区是目前影响露天开采矿山安全生产的主要危害源之一。随着台阶开采的不断剥离,露天开采境界内各台阶与地下空区群的隔离层厚度越来越薄,随时有可能发生采空区顶板坍塌事故。考虑到露天矿采空区地质赋存条件和围岩稳固性等特征,以弓长岭露天铁矿浅层采空区为工程背景,运用现场监测和数值模拟相结合的手段综合分析了浅层采空区的稳定性。将液体静力水准地表沉降监测系统的监测数据与FLAC数值模拟结果对比,调整蠕变参数使得数值模拟的蠕变速率与现场监测结果一致,而后据此进行未来结果的预测。最终根据地表沉降数据确定的蠕变参数取值为A=1.0×10^-12、m=1.75、n=0.35。研究表明:静力水准测点地表最大沉降位移为-9.8 mm,蠕变计算结果顶板最大垂直位移约20.4 mm,应力最大值约25 MPa,综合分析显示该采空区较稳定。上述研究提供了一种基于采空区现场监测数据的数值模拟蠕变分析方法,可为类似矿山采空区稳定性分析提供借鉴。     

Modeling and analysis for multilayered complex communication network of satellite navigation system

This study is extended to construct the network model, the node model, and the link model of complex communication network for satellite navigation system (CCN‐SNS) based on the hierarchical architecture. Firstly, a method called snapshots was proposed to describe the dynamic topology for CCN‐SNS; secondly, another method was put forward to model the different nodes of the CCN‐SNS; thirdly, the different links between every two different nodes were modeled. Therefore, based on the OPNET tools, a simulation for the CCN‐SNS, which contains the models that proposed earlier used to analyze the navigation accuracy and network transmission performance, was performed.     

轧机垂直系统动力学参数辨识

 针对轧机垂直系统动力学参数可信度不足等问题，提出一种基于实测数据的改进粒子群算法辨识轧机垂直系统动力学参数的方法。首先,将轧机垂直系统刚度和阻尼考虑成达芬振子和范德波尔振子，构建轧机垂直系统非线性动力学模型，并对粒子群算法进行改进；然后，通过数值仿真算例辨识得到系统在感染噪声和不含噪声时的动力学参数，验证了该算法的有效性；最后，以现场某轧机垂直系统为研究对象，基于现场实测数据，应用该算法进行辨识，得到了轧机垂直系统动力学参数估计，通过实测位移、速度和加速度信号分别与辨识后的位移、速度和加速度信号进行对比，证明该方法辨识轧机垂直系统动力学参数结果可靠，具有一定的工程应用价值。     

Modeling task completion time of in-vehicle information systems while driving with keystroke level modeling

The use of touchscreen-based in-vehicle information systems (IVIS) is increasing. To ensure safe driving, it is important to evaluate IVIS task performance during driving situations. Therefore, we proposed a model to assess the task completion time (TCT) of IVIS tasks while driving using a keystroke-level modeling (KLM) technique. The basic assumptions and heuristic rules of driver behaviors were considered. In addition, based on the characteristics of visual and manual IVIS interactions, we determined the basic unit operators (i.e., visual, manual, and mental operators). User experiments were conducted to determine the individual execution times of unit tasks and to measure the TCT of IVIS tasks while driving. Based on the heuristic rules for model development and individual task execution times, we derive a predictive model for the TCT of IVIS tasks. We used a regression analysis to validate the modeling procedure, showing that the observed TCT was found to have a strong positive correlation with the predicted time from the modeling process. The findings showed that the task completion time needed to perform a secondary task in a driving context can be predicted by KLM. This study provides meaningful insights into the design of touchscreen-based IVIS to enhance driving safety.