scholarly journals Discharge curve-based formation of retired power batteries for secondary use

2021 ◽  
Author(s):  
Ziyu Xiao ◽  
Siqi Wu
Keyword(s):  
Clustering Algorithm ◽  
Group Formation ◽  
Time Integration ◽  
Internal Resistance ◽  
Open Circuit ◽  
Secondary Use ◽  
Time Integration Method ◽  
Batch Testing ◽  
Remaining Capacity ◽  
Dynamic Time

Abstract To address the problem of optional group formation in the process of retired power batteries for secondary use, a detection method based on the ampere-time integration method is used for batch testing of retired power batteries. The dynamic time-bending dynamic time warping distance between different batteries is calculated by comparing the discharge curves during the testing process. Combining the remaining capacity, open circuit voltage and internal resistance of the battery as a common battery classification condition, each condition is normalised and a density canopy + K-means clustering algorithm is applied to regroup the retired power batteries. This method improves the regrouping technique for the retired batteries and improves the performance of the regrouped battery modules in terms of capacity and consistency.

scholarly journals An Improved Time Integration Method Based on Galerkin Weak Form with Controllable Numerical Dissipation

2021 ◽  
Vol 11 (4) ◽  
pp. 1932
Author(s):  
Weixuan Wang ◽  
Qinyan Xing ◽  
Qinghao Yang
Keyword(s):  
High Frequency ◽  
Integration Method ◽  
Time Integration ◽  
Low Frequency ◽  
Weak Form ◽  
High Accuracy ◽  
Numerical Dissipation ◽  
Frequency Range ◽  
Time Integration Method ◽  
Numerical Damping

Based on the newly proposed generalized Galerkin weak form (GGW) method, a two-step time integration method with controllable numerical dissipation is presented. In the first sub-step, the GGW method is used, and in the second sub-step, a new parameter is introduced by using the idea of a trapezoidal integral. According to the numerical analysis, it can be concluded that this method is unconditionally stable and its numerical damping is controllable with the change in introduced parameters. Compared with the GGW method, this two-step scheme avoids the fast numerical dissipation in a low-frequency range. To highlight the performance of the proposed method, some numerical problems are presented and illustrated which show that this method possesses superior accuracy, stability and efficiency compared with conventional trapezoidal rule, the Wilson method, and the Bathe method. High accuracy in a low-frequency range and controllable numerical dissipation in a high-frequency range are both the merits of the method.

scholarly journals An Efficient Leader Node Selection for Movable Nodes in WSN using PSO Technique

2019 ◽  
Vol 8 (6) ◽  
pp. 5072-5078
Keyword(s):  
Energy Efficient ◽  
Network Performance ◽  
Clustering Algorithm ◽  
Group Formation ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Delivery Ratio ◽  
Efficient Prediction ◽  
The Stability ◽  
Effective Group

Wireless Sensor Networks (WSN) is a group of sensor devices, which are used to sense the surroundings. The network performance is still an issue in the WSN and an efficient protocol is introduced such as LEACH. To improve the stability, LEACH with fuzzy descriptors is used in preceding research. However the existing has drawback with effective group formation in heterogeneous WSN and also it is not achieved the Super Leader Node (SLH). To overcome the above mentioned issues, the proposed system enhances the approach which is used for increasing the energy consumption, packet delivery ratio, and bandwidth and network lifetime. The proposed paper contains three phases such as grouping formation, Leader Node (LN) selection, SLN selection with three main objectives:(i) to acquire Energy-Efficient Prediction Clustering Algorithm (EEPCA) in heterogeneous WSN for grouping formation (ii)To design Low Energy Adaptive Clustering Hierarchy- Expected Residual Energy (LEACH-ERE) protocol for LN selection.(iii)To optimize the SCH selection by Particle Swarm Optimization (PSO) based fuzzy approach. The clustering formation is done by Energy-Efficient Prediction Clustering Algorithm (EEPCA) in heterogeneous WSN. It is used to calculate the sensor nodes which have shortest distance between each node. The LEACH-ERE protocol was proposed to form a Leader Node (LN) and all the nodes has to communicate with sink through LN only. New SLN is elected based on distance from the sink and battery power of the node.

scholarly journals Impact of difference between explicit and implicit second-order time integration schemes on isotropic/anisotropic steady incompressible turbulence field

2021 ◽  
Vol 2090 (1) ◽  
pp. 012145
Author(s):  
Ryuma Honda ◽  
Hiroki Suzuki ◽  
Shinsuke Mochizuki
Keyword(s):  
Kinetic Energy ◽  
Energy Conservation ◽  
Integration Method ◽  
Time Integration ◽  
Second Order ◽  
Implicit Time ◽  
Explicit Time Integration ◽  
Time Integration Method ◽  
Implicit Time Integration ◽  
Time Integration Methods

Abstract This study presents the impact of the difference between the implicit and explicit time integration methods on a steady turbulent flow field. In contrast to the explicit time integration method, the implicit time integration method may produce significant kinetic energy conservation error because the widely used spatial difference method for discretizing the governing equations is explicit with respect to time. In this study, the second-order Crank-Nicolson method is used as the implicit time integration method, and the fourth-order Runge-Kutta, second-order Runge-Kutta and second-order Adams-Bashforth methods are used as explicit time integration methods. In the present study, both isotropic and anisotropic steady turbulent fields are analyzed with two values of the Reynolds number. The turbulent kinetic energy in the steady turbulent field is hardly affected by the kinetic energy conservation error. The rms values of static pressure fluctuation are significantly sensitive to the kinetic energy conservation error. These results are examined by varying the time increment value. These results are also discussed by visualizing the large scale turbulent vortex structure.

Time integration method to determine the characteristic parameter of a light extinctiometer

1993 ◽  
Vol 15 (1) ◽  
pp. 42-48 ◽  
Author(s):  
J. H. Geng ◽  
A. van de Ven ◽  
F. Zhang ◽  
H. Grönig
Keyword(s):  
Integration Method ◽  
Time Integration ◽  
Characteristic Parameter ◽  
Time Integration Method
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