Internal Resistance Based Assessment Model for the Degradation of Li-Ion Battery Pack

2020 ◽  
Author(s):  
Iffandya Popy Wulandari ◽  
Min-Chun Pan

Abstract As one pioneer means for energy storage, Li-ion battery packs have a complex and critical issue about degradation monitoring and remaining useful life estimation. It induces challenges on condition characterization of Li-ion battery packs such as internal resistance (IR). The IR is an essential parameter of a Li-ion battery pack, relating to the energy efficiency, power performance, degradation, and physical life of the li-ion battery pack. This study aims to obtain reliable IR through applying an evaluation test that acquires data such as voltage, current, and temperature provided by the battery management system (BMS). Additionally, this paper proposes an approach to predict the degradation of Li-ion battery pack using support vector regression (SVR) with RBF kernel. The modeling approach using the relationship between internal resistance, different SOC levels 20%–100%, and cycle at the beginning of life 1 cycle until cycle 500. The data-driven method is used here to achieve battery life prediction.based on internal resistance behavior in every period using supervised machine learning, SVR. Our experiment result shows that the internal resistance was increasing non-linear, approximately 0.24%, and it happened if the cycle rise until 500 cycles. Besides, using SVR algorithm, the quality of the fitting was evaluated using coefficient determination R2, and the score is 0.96. In the proposed modeling process of the battery pack, the value of MSE is 0.000035.

Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 356 ◽  
Author(s):  
Sung-Tae Ko ◽  
Jaehyung Lee ◽  
Jung-Hoon Ahn ◽  
Byoung Kuk Lee

In this paper, an innovative modeling approach for Li-ion battery packs is proposed by considering intrinsic cell unbalances and packaging elements. The proposed modeling method shows that the accurate battery pack model can be achieved if the overall influences of intrinsic cell unbalances and packaging elements are taken account. Concurrently, the proposed method takes a practical model structure, resulting in the reduction of computational burden in a battery management system. Furthermore, because the proposed method utilizes cell information without a manufactured battery pack, it can be helpful to design optimal battery packs. The proposed method is verified through simulation and experimental results of the Li-ion battery pack along with the battery cycler. In three test profiles, the mean absolute percentage errors and root mean square errors of the proposed pack model do not exceed 0.5% and 0.07 V, respectively.


2019 ◽  
Vol 18 (2) ◽  
pp. 49-56
Author(s):  
Md. Nahian Al Subri Ivan ◽  
Sujit Devnath ◽  
Rethwan Faiz ◽  
Kazi Firoz Ahmed

To infer and predict the reliability of the remaining useful life of a lithium-ion (Li-ion) battery is very significant in the sectors associated with power source proficiency. As an energy source of electric vehicles (EV), Li-ion battery is getting attention due to its lighter weight and capability of storing higher energy. Problems with the reliability arises while li-ion batteries of higher voltages are required. As in this case several li-ion cells areconnected in series and failure of one cell may cause the failure of the whole battery pack. In this paper, Firstly, the capacity degradation of li-ion cells after each cycle is observed and secondly with the help of MATLAB 2016 a mathematical model is developed using Weibull Probability Distribution and Exponential Distribution to find the reliability of different types of cell configurations of a non-redundant li-ion battery pack. The mathematical model shows that the parallel-series configuration of cells is more reliable than the series configuration of cells. The mathematical model also shows that if the discharge rate (C-rate) remains constant; there could be an optimum number for increasing the cells in the parallel module of a parallel-series onfiguration of cells of a non-redundant li-ion battery pack; after which only increasing the number of cells in parallel module doesn’t increase the reliability of the whole battery pack significantly. 


Energies ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 2212
Author(s):  
Hien Vu ◽  
Donghwa Shin

Lithium-ion batteries exhibit significant performance degradation such as power/energy capacity loss and life cycle reduction in low-temperature conditions. Hence, the Li-ion battery pack is heated before usage to enhance its performance and lifetime. Recently, many internal heating methods have been proposed to provide fast and efficient pre-heating. However, the proposed methods only consider a combination of unit cells while the internal heating should be implemented for multiple groups within a battery pack. In this study, we investigated the possibility of timing control to simultaneously obtain balanced temperature and state of charge (SOC) between each cell by considering geometrical and thermal characteristics of the battery pack. The proposed method schedules the order and timing of the charge/discharge period for geometrical groups in a battery pack during internal pre-heating. We performed a pack-level simulation with realistic electro-thermal parameters of the unit battery cells by using the mutual pulse heating strategy for multi-layer geometry to acquire the highest heating efficiency. The simulation results for heating from −30 ∘ C to 10 ∘ C indicated that a balanced temperature-SOC status can be achieved via the proposed method. The temperature difference can be decreased to 0.38 ∘ C and 0.19% of the SOC difference in a heating range of 40 ∘ C with only a maximum SOC loss of 2.71% at the end of pre-heating.


Author(s):  
Haoting Wang ◽  
Ning Liu ◽  
Lin Ma

Abstract This paper reports the development of a two-dimensional two states (2D2S) model for the analysis of thermal behaviors of Li-ion battery packs and its experimental validation. This development was motivated by the need to fill a niche in our current modeling capabilities: the need to analyze 2D temperature (T) distributions in large-scale battery packs in real time. Past models were predominately developed to either provide detailed T information with high computational cost or provide real-time analysis but only 1D lumped T information. However, the capability to model 2D T field in real time is desirable in many applications ranging from the optimal design of cooling strategies to onboard monitoring and control. Therefore, this work developed a new approach to provide this desired capability. The key innovations in our new approach involved modeling the whole battery pack as a complete thermal-fluid network and at the same time calculating only two states (surface and core T) for each cell. Modeling the whole pack as a complete network captured the interactions between cells and enabled the accurate resolution of the 2D T distribution. Limiting the calculation to only the surface and core T controlled the computational cost at a manageable level and rendered the model suitable for packs at large scale with many cells.


2015 ◽  
Vol 159 ◽  
pp. 285-297 ◽  
Author(s):  
Meru A. Patil ◽  
Piyush Tagade ◽  
Krishnan S. Hariharan ◽  
Subramanya M. Kolake ◽  
Taewon Song ◽  
...  

Author(s):  
Divya Chalise ◽  
Krishna Shah ◽  
Ravi Prasher ◽  
Ankur Jain

Thermal management of Li-ion battery packs is a critical technological challenge that directly impacts safety and performance. Removal of heat generated in individual Li-ion cells into the ambient is a considerably complicated problem involving multiple heat transfer modes. This paper develops an iterative analytical technique to model conjugate heat transfer in coolant-based thermal management of a Li-ion battery pack. Solutions for the governing energy conservation equations for thermal conduction and convection are derived and coupled with each other in an iterative fashion to determine the final temperature distribution. The analytical model is used to investigate the dependence of the temperature field on various geometrical and material parameters. This work shows that the coolant flowrate required for effective cooling can be reduced significantly by improving the thermal conductivity of individual Li-ion cells. Further, this work helps understand key thermal–electrochemical trade-offs in the design of thermal management for Li-ion battery packs, such as the trade-off between temperature rise and energy storage density in the battery pack.


The green energy evolution initiated the use of electric and hybrid electric vehicles at present on roads. These vehicles extensively use different types of batteries and among them lithium ion batteries are prominent. The Li-ion battery pack constitutes number of Li-ion battery cells connected in series and parallel configuration. This battery bank needs a suitable battery management system for its efficient operation. This paper presents a novel battery management system to monitor and control the battery current, voltage, state of charge and most importantly the cell temperature. The detail BMS scheme for Li-ion battery pack is presented and simulation is carried out to validate its performance with a driving cycle of electric car.


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