scholarly journals Design and Development of Hardware to Analyze and Categorize the Condition of Batteries With the Aim of Enabling Their Re-Use

Author(s):  
Andrew Wilson ◽  
Qing Wang

Abstract This paper covers the design and implementation of an accurate, yet flexible test system for Lithium-Ion batteries. The system makes use of linear charge and discharge circuitry to ensure a low noise control, and can support the simultaneous and independent testing of six cells. The system is controlled and data collected by specialist MatLab© software with a user-friendly GUI. Experimental data is processed within the same environment to obtain the desired information. The system makes use of Full Cycle Coulomb Counting and Pulsed DC Load Analysis to obtain estimates for the State of Health (SoH) and State of Charge (SoC) of various cells, and to examine the effect of different use cases on cell performance through repeated testing.

Author(s):  
Onyemaobi Bethram Chibuzo ◽  
Dauda Olorunkemi Isiaka

- This work is concerned with the development of a browser for computer based examination platforms. It focused on trends and mostly used browsers for online computer based examination and carried out a critical review of the browsers used for current computer based test system employed in Nigeria Universities. An alternative application to provide solutions to the current challenges identified in the existing system was then developed. The new application was designed using the Extreme programming methodology and implemented using Microsoft Visual Basic on a Windows 7 system. We created user-friendly interfaces driven by the Visual Basic codes. The application has amongst other features, disabled access to control box of the browser window and the Alt + F4 button as shortcut in closing browsers


Machines ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 1
Author(s):  
Jing Wang ◽  
Zhihua Wan ◽  
Zhurong Dong ◽  
Zhengguo Li

The harmonic reducer, with its advantages of high precision, low noise, light weight, and high speed ratio, has been widely used in aerospace solar wing deployment mechanisms, antenna pointing mechanisms, robot joints, and other precision transmission fields. Accurately predicting the performance of the harmonic reducer under various application conditions is of great significance to the high reliability and long life of the harmonic reducer. In this paper, a set of automatic harmonic reducer performance test systems is designed. By using the CANOpen bus interface to control the servo motor as the drive motor, through accurately controlling the motor speed and rotation angle, collecting the angle, torque, and current in real time, the life cycle test of space harmonic reducer was carried out in high vacuum and low temperature environment on the ground. Then, the collected data were automatically analyzed and calculated. The test data of the transmission accuracy, backlash, and transmission efficiency of the space harmonic reducer were obtained. It is proven by experiments that the performance data of the harmonic reducer in space work can be more accurately obtained by using the test system mentioned in this paper, which is convenient for further research on related lubricating materials.


Author(s):  
Meng Wei ◽  
Min Ye ◽  
Jia Bo Li ◽  
Qiao Wang ◽  
Xin Xin Xu

State of charge (SOC) of the lithium-ion batteries is one of the key parameters of the battery management system, which the performance of SOC estimation guarantees energy management efficiency and endurance mileage of electric vehicles. However, accurate SOC estimation is a difficult problem owing to complex chemical reactions and nonlinear battery characteristics. In this paper, the method of the dynamic neural network is used to estimate the SOC of the lithium-ion batteries, which is improved based on the classic close-loop nonlinear auto-regressive models with exogenous input neural network (NARXNN) model, and the open-loop NARXNN model considering expected output is proposed. Since the input delay, feedback delay, and hidden layer of the dynamic neural network are usually selected by empirically, which affects the estimation performance of the dynamic neural network. To cover this weakness, sine cosine algorithm (SCA) is used for global optimal dynamic neural network parameters. Then, the experimental results are verified to obtain the effectiveness and robustness of the proposed method under different conditions. Finally, the dynamic neural network based on SCA is compared with unscented Kalman filter (UKF), back propagation neural network based on particle swarm optimization (BPNN-PSO), least-squares support vector machine (LS-SVM), and Gaussian process regression (GPR), the results show that the proposed dynamic neural network based on SCA is superior to other methods.


Polymers ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 1971
Author(s):  
Lihua Ye ◽  
Muhammad Muzamal Ashfaq ◽  
Aiping Shi ◽  
Syyed Adnan Raheel Shah ◽  
Yefan Shi

In this research, the aim relates to the material characterization of high-energy lithium-ion pouch cells. The development of appropriate model cell behavior is intended to simulate two scenarios: the first is mechanical deformation during a crash and the second is an internal short circuit in lithium-ion cells during the actual effect scenarios. The punch test has been used as a benchmark to analyze the effects of different state of charge conditions on high-energy lithium-ion battery cells. This article explores the impact of three separate factors on the outcomes of mechanical punch indentation experiments. The first parameter analyzed was the degree of prediction brought about by experiments on high-energy cells with two different states of charge (greater and lesser), with four different sizes of indentation punch, from the cell’s reaction during the indentation effects on electrolyte. Second, the results of the loading position, middle versus side, are measured at quasi-static speeds. The third parameter was the effect on an electrolyte with a different state of charge. The repeatability of the experiments on punch loading was the last test function analyzed. The test results of a greater than 10% state of charge and less than 10% state of charge were compared to further refine and validate this modeling method. The different loading scenarios analyzed in this study also showed great predictability in the load-displacement reaction and the onset short circuit. A theoretical model of the cell was modified for use in comprehensive mechanical deformation. The overall conclusion found that the loading initiating the cell’s electrical short circuit is not instantaneously instigated and it is subsequently used to process the development of a precise and practical computational model that will reduce the chances of the internal short course during the crash.


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