scholarly journals A Novel Active Cell Balancing Circuit and Charging Strategy in Lithium Battery Pack

Energies ◽  
2019 ◽  
Vol 12 (23) ◽  
pp. 4473 ◽  
Author(s):  
Shing-Lih Wu ◽  
Hung-Cheng Chen ◽  
Chih-Hsuan Chien
Keyword(s):  
Lithium Battery ◽  
Cell Voltage ◽  
Active Cell ◽  
Battery Pack ◽  
Battery Cell ◽  
Voltage Difference ◽  
Third Stage ◽  
Maximum Cell ◽  
Cell Balancing ◽  
Battery Cells

A novel, active cell balancing circuit and charging strategy in lithium battery pack is proposed in this paper. The active cell balancing circuit mainly consists of a battery voltage measurement circuit and switch control circuit. First, all individual cell voltages are measured by an MSP430 microcontroller equipped with an isolation circuit and a filter circuit. Then, the maximum cell voltage difference is calculated by subtracting the minimum cell voltage from the maximum cell voltage. When the maximum cell voltage difference exceeds 0.05 V, the balancing action starts to carry on. The MSP430 microcontroller output controls signals to close the switches corresponding to the battery cell with the maximum voltage. At this time, the balancing charge power performs a balancing charge for other batteries, except for the one that is switched on. In addition, a three-stage balancing charge strategy is also proposed in this paper to achieve the goal of speedy charging with balancing action. In the first stage, a 0.5 C balancing current is used to perform pre-balanced charging on all battery cells until the maximum cell voltage difference is less than 0.05 V, which is required for entry to the second stage of charging. In the second stage, constant current charging of 1 C, coupled with 0.2 C balancing current charging is carried out, until the maximum battery cell voltage reaches 4.2 V, which is required for entry into the third stage of charging. In the third stage, a constant voltage charging is coupled with 0.2 C balancing current charging, until the maximum battery cell voltage reaches 4.25 V, which is required to complete the balancing charge. The imbalance of power between the battery cells during battery pack charging, which reduces battery charging efficiency and battery life, is thus effectively improved. In this paper, a six-cells-in-series and two-in parallel lithium battery pack is used to perform a balancing charge test. Test results show that the battery cells in the battery pack are capable of quickly completing a balancing charge under different initial voltages, the maximum voltage difference is reduced to within the range of 0.05 V, and the total time required for each balancing charge is approximately 3600 s.

scholarly journals A ΔSOC-based equalization strategy applied to industry

2020 ◽  
Author(s):  
Maonan Wang ◽  
Chun Chang ◽  
Feng Ji
Keyword(s):  
Open Circuit ◽  
Battery Pack ◽  
Battery Management System ◽  
Battery Management ◽  
Battery Cell ◽  
New Strategy ◽  
The Difference ◽  
Relative Errors ◽  
The Relationship ◽  
Battery Cells

Abstract The voltage-based equalization strategy is widely used in the industry because the voltage (U) of the battery cell is very easy to obtain, but it is difficult to provide an accurate parameter for the battery management system (BMS). This study proposes a new equalization strategy, which is based on the difference between the state of charge (SOC) of any two battery cells in the battery pack, that is, a ΔSOC-based equalization strategy. The new strategy is not only as simple as the voltage-based equalization strategy, but it can also provide an accurate parameter for the BMS. Simply put, using the relationship between the open circuit voltage and the SOC of the battery pack, the proposed strategy can convert the difference between the voltage of the battery cells into ΔSOC, which renders a good performance. Additionally, the required parameters are all from the BMS, and no additional calculation is required, which makes the strategy as simple as the voltage-based balancing strategy. The four experiments show that the relative errors of ΔSOC estimated by the ΔSOC-based equalization strategy are 0.37%, 0.39%, 0.1% and 0.17%, and thereby demonstrate that the ΔSOC-based equalization strategy proposed in this study shows promise in replacing the voltage-based equalization strategy within the industry to obtain better performance.

scholarly journals Run to Failure: Aging of Commercial Battery Cells beyond Their End of Life

Energies ◽  
2020 ◽  
Vol 13 (8) ◽  
pp. 1858
Author(s):  
Andreas Ziegler ◽  
David Oeser ◽  
Thiemo Hein ◽  
Daniel Montesinos-Miracle ◽  
Ansgar Ackva
Keyword(s):  
Computed Tomography ◽  
Single Cells ◽  
Lithium Ion ◽  
Constant Load ◽  
Internal Resistance ◽  
Battery Pack ◽  
X Rays ◽  
Battery Cell ◽  
Jelly Roll ◽  
Battery Cells

The aim of this work is to age commercial battery cells far beyond their expected lifetime. There is a gap in the literature regarding run to failure tests of lithium-ion batteries that this work intends to address. Therefore, twenty new Samsung ICR18650-26F cells were aged as a battery pack in a run to failure test. Aging took place with a constant load current and a constant charge current to accelerate capacity decrease. Important aging parameters such as capacity and internal resistance were measured at each cycle to monitor their development. The end of the test was initiated by the explosion of a single battery cell, after which the battery pack was disassembled and all parameters of the still intact single cells were measured. The distribution of all measured capacities and internal resistances is displayed graphically. This clearly shows the influence of the exploded cell on the cells in its immediate vicinity. Selected cells from this area of the battery were subjected to computed tomography (CT) to detect internal defects. The X-rays taken with computed tomography showed clear damage within the jelly roll, as well as the triggered safety mechanisms.

scholarly journals Research on Key Technologies for Improving the Electro catalytic Performance and Physical Properties of Lithium Batteries in Electric Vehicles

2021 ◽  
Vol 2083 (2) ◽  
pp. 022071
Author(s):  
Qingyuan Fang
Keyword(s):  
Temperature Field ◽  
Heat Generation ◽  
Lithium Battery ◽  
Heat Dissipation ◽  
Lithium Ion ◽  
Catalytic Performance ◽  
Performance Model ◽  
Battery Pack ◽  
Discharge Process ◽  
Battery Cell

Abstract Aiming at the uneven heat generation in various parts of the electric vehicle lithium battery pack during the discharge process, the heat generation mechanism is studied, and the lithium battery catalytic performance model is established to obtain the current density and heat generation rate distribution law of the lithium battery cell on the cell. The thermal model can simulate the thermal behavior of the battery under application conditions. Study the laws of battery heat production, heat transfer, and heat dissipation, and calculate the temperature changes inside and on the battery and the temperature field information in real time to provide a basis for the design and optimization of the battery and battery pack thermal management system. The simulation results show that the established model can predict the heating distribution and temperature field of the internal layered structure of the lithium-ion battery, which is helpful for the subsequent analysis of key influencing factors.

scholarly journals Lifetime and Aging Degradation Prognostics for Lithium-ion Battery Packs Based on a Cell to Pack Method

2022 ◽  
Vol 35 (1) ◽  
Author(s):  
Yunhong Che ◽  
Zhongwei Deng ◽  
Xiaolin Tang ◽  
Xianke Lin ◽  
Xianghong Nie ◽  
...  
Keyword(s):  
Deep Learning ◽  
Lithium Ion ◽  
Fine Tuning ◽  
Battery Pack ◽  
Discharge Process ◽  
Prediction Errors ◽  
Target Domain ◽  
Battery Cell ◽  
Battery Packs ◽  
Battery Cells

AbstractAging diagnosis of batteries is essential to ensure that the energy storage systems operate within a safe region. This paper proposes a novel cell to pack health and lifetime prognostics method based on the combination of transferred deep learning and Gaussian process regression. General health indicators are extracted from the partial discharge process. The sequential degradation model of the health indicator is developed based on a deep learning framework and is migrated for the battery pack degradation prediction. The future degraded capacities of both battery pack and each battery cell are probabilistically predicted to provide a comprehensive lifetime prognostic. Besides, only a few separate battery cells in the source domain and early data of battery packs in the target domain are needed for model construction. Experimental results show that the lifetime prediction errors are less than 25 cycles for the battery pack, even with only 50 cycles for model fine-tuning, which can save about 90% time for the aging experiment. Thus, it largely reduces the time and labor for battery pack investigation. The predicted capacity trends of the battery cells connected in the battery pack accurately reflect the actual degradation of each battery cell, which can reveal the weakest cell for maintenance in advance.

scholarly journals Environmental testing for reliable battery management system in electric vehicle

2020 ◽  
Vol 1517 (1) ◽  
pp. 012025
Author(s):  
J Raharjo ◽  
A Wikarta ◽  
I Sidharta ◽  
M N Yuniarto ◽  
M I Firdaus ◽  
...  
Keyword(s):  
Management System ◽  
Cell Voltage ◽  
Temperature Cycling ◽  
Battery Pack ◽  
Battery Management System ◽  
Battery Management ◽  
Environmental Testing ◽  
The Difference ◽  
Main Component ◽  
Battery Cells

Abstract The Battery management system (BMS) is a main component in the battery pack system for electric vehicles (EV). The function of BMS is to monitor battery cells such as; cell voltage, cell temperature, and current in the battery pack. Moreover BMS also able to balance the voltage of the cells so the difference in voltage of the cells can be minimized. By having many of these functions, BMS can identify battery health based on these parameters. With such an important function, in this paper, BMS was tested to determine its reliability. The standard testing for BMS reliability is the Environment test. In the environment test, some things that are conducted in the environment test are initial temperature cycling. From the environment, the test can be generated information to assess the quality of the BMS following its function. Furthermore, it can reduce the cost to inspect every battery cells in the packs. With the environment test as a basis for BMS reliability tester, hopefully, good quality is obtained. Future development in BMS reliability testing can also be conducted to improve reliability.

scholarly journals Review of Battery Cell Balancing Methodologies for Optimizing Battery Pack Performance in Electric Vehicles

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 129335-129352 ◽  
Author(s):  
Zachary Bosire Omariba ◽  
Lijun Zhang ◽  
Dongbai Sun
Keyword(s):  
Electric Vehicles ◽  
Battery Pack ◽  
Battery Cell ◽  
Cell Balancing

Maximizing Battery Life and Usable Capacity With Battery Management System in Electric Vehicles

2017 ◽  
Author(s):  
Zoltán Szeli ◽  
Gábor Szakállas ◽  
Ferenc Szauter
Keyword(s):  
Electric Vehicles ◽  
Management System ◽  
Active Cell ◽  
Battery Pack ◽  
Research Centre ◽  
Battery Life ◽  
Battery Management System ◽  
Battery Management ◽  
Cost Weight ◽  
Cell Balancing

In terms of the electric vehicles is an important issue of sizing a battery pack. The designer must take account of parameters such as cost, weight and durability. We can optimize these parameters with the help of a battery management system with integrated active cell balancing function. The article describes the development of a battery management system that developed by the Research Centre of Vehicle Industry at Széchenyi István University, Győr, Hungary.

scholarly journals Improving of Active Cell Balancing by Equalizing the Cell Energy Instead of the Cell Voltage

2010 ◽  
Vol 4 (2) ◽  
pp. 400-404 ◽  
Author(s):  
Markus Einhorn ◽  
Fiorentino Valerio Conte ◽  
Juergen Fleig
Keyword(s):  
Cell Voltage ◽  
Active Cell ◽  
Cell Energy ◽  
Cell Balancing
Sign in / Sign up

Export Citation Format

Share Document