scholarly journals Critical Review of Ageing Mechanisms and State of Health Estimation Methods for Battery Performance

Author(s):  
K. Saqli ◽  
H. Bouchareb ◽  
M. Oudghiri ◽  
N. K. M’Sirdi
2016 ◽  
Vol 56 ◽  
pp. 572-587 ◽  
Author(s):  
M. Berecibar ◽  
I. Gandiaga ◽  
I. Villarreal ◽  
N. Omar ◽  
J. Van Mierlo ◽  
...  

2019 ◽  
Vol 18 (4) ◽  
pp. 611-619
Author(s):  
Stefano Camatarri

After several decades of debate on the so-called protest vote, the extant literature in this field is still far from consistent in conceptualization and analytical perspectives. Yet, at a time of increasing democratic stress, it becomes crucial for political studies to take stock of current research on this topic and assess its general state of health. In the light of this, aim of the present contribution is to piece together the puzzle of analytical perspectives from which scholars and pundits have approached the matter over the years. First, this article will do so at a conceptual level, disentangling different conceptualizations of protest voting. In parallel, it will do so at the technical and empirical level, categorizing both operationalization strategies and findings into alternative strands of research. As a last step, it will summarize the still open issues, organizing them within a unified platform and identifying possible lines of development for future research.


2020 ◽  
Vol 9 (2) ◽  
pp. 185-196
Author(s):  
Liu Fang ◽  
◽  
Liu Xinyi ◽  
Su Weixing ◽  
Chen Hanning ◽  
...  

To realize a fast and high-precision online state-of-health (SOH) estimation of lithium-ion (Li-Ion) battery, this article proposes a novel SOH estimation method. This method consists of a new SOH model and parameters identification method based on an improved genetic algorithm (Improved-GA). The new SOH model combines the equivalent circuit model (ECM) and the data-driven model. The advantages lie in keeping the physical meaning of the ECM while improving its dynamic characteristics and accuracy. The improved-GA can effectively avoid falling into a local optimal problem and improve the convergence speed and search accuracy. So the advantages of the SOH estimation method proposed in this article are that it only relies on battery management systems (BMS) monitoring data and removes many assumptions in some other traditional ECM-based SOH estimation methods, so it is closer to the actual needs for electric vehicle (EV). By comparing with the traditional ECM-based SOH estimation method, the algorithm proposed in this article has higher accuracy, fewer identification parameters, and lower computational complexity.


2020 ◽  
Vol 11 (4) ◽  
pp. 66
Author(s):  
Nassim Noura ◽  
Loïc Boulon ◽  
Samir Jemeï

To cope with the new transportation challenges and to ensure the safety and durability of electric vehicles and hybrid electric vehicles, high performance and reliable battery health management systems are required. The Battery State of Health (SOH) provides critical information about its performances, its lifetime and allows a better energy management in hybrid systems. Several research studies have provided different methods that estimate the battery SOH. Yet, not all these methods meet the requirement of automotive real-time applications. The real time estimation of battery SOH is important regarding battery fault diagnosis. Moreover, being able to estimate the SOH in real time ensure an accurate State of Charge and State of Power estimation for the battery, which are critical states in hybrid applications. This study provides a review of the main battery SOH estimation methods, enlightening their main advantages and pointing out their limitations in terms of real time automotive compatibility and especially hybrid electric applications. Experimental validation of an online and on-board suited SOH estimation method using model-based adaptive filtering is conducted to demonstrate its real-time feasibility and accuracy.


Author(s):  
Suhak Lee ◽  
Jason B. Siegel ◽  
Anna G. Stefanopoulou ◽  
Jang-Woo Lee ◽  
Tae-Kyung Lee

It is essential to understand the state-of-health (SOH) of the individual electrode to avoid accelerating degradation of Li-ion battery. Electrode SOH can be quantified based on estimating the capacity and the utilization range of each electrode. Here, we introduce two methods: i) voltage fitting (VF) and ii) peak alignment (PA), and compare their ability to estimate the electrode SOH parameters. Both methods assume the half-cell open-circuit potentials (OCPs) are invariant functions of the stoichio-metric states with the cell aging, which can make the accuracy of the electrode parameter estimation vulnerable to degradation that would cause changes in the half-cell OCP curves. This hypothesis is verified experimentally by applying the two methods to aged cells cycled at high temperature. A discernible misalignment of the peaks is observed in the differential voltage curve from the VF method indicating the estimation result is incorrect, even though it reconstructs the OCV with the small error and estimates the cell capacity accurately. Therefore, it is seen that the lower voltage error and the accurate cell capacity estimate do not necessarily promise a better estimation accuracy for the electrode SOH parameters.


2019 ◽  
Vol 22 (6) ◽  
pp. 1449-1479 ◽  
Author(s):  
YaNan Wang ◽  
YangQuan Chen ◽  
XiaoZhong Liao

Abstract This paper presents a state-of-art survey of the research on fractional-order (FO) modeling with parameter identification, and FO estimation methods for state of charge (SOC), state of health (SOH), and remaining usage life (RUL) of lithium-ion batteries (LIBs) mainly in recent five years. FO electrochemical models and six different types of FO equivalent circuit models (ECMs) are introduced in detail. Then, the corresponding tuning algorithm for parameters of these FO models are also provided in brief. Moreover, FO estimation methods for SOC are listed and analyzed, mainly including FO observers, and FO Kalman filters (FO-KFs). SOH and RUL estimation is another vital aspect for LIBs ageing and degradation monitoring, thus FO estimation methods proposed in recent research within five years are all listed. Finally, some suggestions that may be helpful for further research are proposed in conclusion.


2021 ◽  
pp. 255-311
Author(s):  
Shunli Wang ◽  
Yongcun Fan ◽  
Daniel-Ioan Stroe ◽  
Carlos Fernandez ◽  
Chunmei Yu ◽  
...  

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