scholarly journals Prognostics for State of Health of Lithium-Ion Batteries Based on Gaussian Process Regression

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Di Zhou ◽  
Hongtao Yin ◽  
Ping Fu ◽  
Xianhua Song ◽  
Wenbin Lu ◽  
...  
Keyword(s):  
Gaussian Process ◽  
Lithium Ion Battery ◽  
Gaussian Process Regression ◽  
Lithium Ion ◽  
Practical Significance ◽  
Accurate Estimation ◽  
State Of Health ◽  
Li Ion Batteries ◽  
Li Ion ◽  
Qualitative Measure

Accurate estimation and prediction of the lithium-ion (Li-ion) batteries’ performance has important theoretical and practical significance to make better use of lithium-ion battery and to avoid unnecessary losses. State of health (SOH) estimation is used as a qualitative measure of the capability of a lithium-ion battery to store and deliver energy in a system. To evaluate and predict the SOH of batteries, the Gaussian process regression with neural network (GPRNN) as its variance function is proposed. Experimental results confirm that the proposed method can be effectively applied to Li-ion battery monitoring and prognostics by quantitative comparison with basic GPR, combination LGPFR, combination QGPFR, and the multiscale GPR (SMK-GPR, P-MGPR, and SE-MGPR). The criteria of RMSE and MAPE of the proposed three models are reduced significantly compared to those of other existing methods.

Human-knowledge-augmented Gaussian Process Regression for State-of-Health Prediction of Lithium-ion Batteries with Charging Curves

2021 ◽  
pp. 1-10
Author(s):  
Quan Zhou ◽  
Chongming Wang ◽  
Zeyu Sun ◽  
Ji Li ◽  
Huw Williams ◽  
...  
Keyword(s):  
Gaussian Process ◽  
Lithium Ion Batteries ◽  
Gaussian Process Regression ◽  
Lithium Ion ◽  
Learning Performance ◽  
Transport Systems ◽  
State Of Health ◽  
Human Knowledge ◽  
Voltage Profile ◽  
Inference System

Abstract Lithium-ion batteries have been widely used in renewable energy storage and electrified transport systems, and State-of-Health (SoH) prediction is critical for safe and reliable operation of the lithium-ion batteries. Following the standard routine which predicts battery SoH based on charging curves, a human-knowledge-augmented Gaussian process regression (HAGPR) model is newly proposed for SoH prediction by incorporating two promising artificial intelligence techniques, i.e., the Gaussian process regression (GPR) and the adaptive neural fuzzy inference system (ANFIS). Based on human knowledge on voltage profile during battery degradation, a ANFIS is developed for feature extraction that helps improve machine learning performance and reduce the need of physical testing. Then, the ANFIS is integrated with a GPR model to enable SoH prediction with the extracted feature from battery aging test data. With a conventional GPR model as the baseline, a comparison study is conducted to demonstrate the advantage and robustness of the proposed HAGPR model. It indicates that the proposed HAGPR model can reduce at least 12% root mean square error with 31.8% less battery aging testing compared to the GPR model.

scholarly journals Designing of Lithium - Ion Battery Pack Rechargeable on a Hybrid System with Battery Management System (BMS) for DC Loads of Low Power Applications – A Prototype Model

2021 ◽  
Vol 2089 (1) ◽  
pp. 012017
Author(s):  
Ramu Bhukya ◽  
Praveen Kumar Nalli ◽  
Kalyan Sagar Kadali ◽  
Mahendra Chand Bade
Keyword(s):  
Lithium Ion Battery ◽  
Management System ◽  
Short Circuit ◽  
Lithium Ion ◽  
Battery Pack ◽  
Prototype Model ◽  
Battery Management System ◽  
Battery Management ◽  
Li Ion Batteries ◽  
Li Ion

Abstract Now a days, Li-ion batteries are quite possibly the most exceptional battery-powered batteries; these are drawing in much consideration from recent many years. M Whittingham first proposed lithium-ion battery technology in the 1970s, using titanium sulphide for the cathode and lithium metal for the anode. Li-ion batteries are the force to be reckoned with for the advanced electronic upset in this cutting-edge versatile society, solely utilized in cell phones and PC computers. A battery is a Pack of cells organized in an arrangement/equal association so the voltage can be raised to the craving levels. Lithium-ion batteries, which are completely utilised in portable gadgets & electric vehicles, are the driving force behind the digital technological revolution in today’s mobile societies. In order to protect and maintain voltage and current of the battery with in safe limit Battery Management System (BMS) should be used. BMS provides thermal management to the battery, safeguarding it against over and under temperature and also during short circuit conditions. The battery pack is designed with series and parallel connected cells of 3.7v to produce 12v. The charging and releasing levels of the battery pack is indicated by interfacing the Arduino microcontroller. The entire equipment is placed in a fiber glass case (looks like aquarium) in order to protect the battery from external hazards to design an efficient Lithium-ion battery by using Battery Management System (BMS). We give the supply to the battery from solar panel and in the absence of this, from a regular AC supply.

scholarly journals Charge and Discharge Behaviour of Li-Ion Batteries at Various Temperatures Containing LiCoO2 Nanostructured Cathode Produced by CCSO

2015 ◽  
Vol 15 (4) ◽  
pp. 301 ◽  
Author(s):  
Y.Y. Mamyrbayeva ◽  
R.E. Beissenov ◽  
M.A. Hobosyan ◽  
S.E. Kumekov ◽  
K.S. Martirosyan
Keyword(s):  
Lithium Ion Battery ◽  
Active Material ◽  
Lithium Ion ◽  
Synthetic Approach ◽  
Capacity Fade ◽  
Li Ion Batteries ◽  
Material Loss ◽  
Method Performance ◽  
Battery Capacity ◽  
Li Ion

<p>There are technical barriers for penetration market requesting rechargeable lithium-ion battery packs for portable devices that operate in extreme hot and cold environments. Many portable electronics are used in very cold (-40 °C) environments, and many medical devices need batteries that operate at high temperatures. Conventional Li-ion batteries start to suffer as the temperature drops below 0 °C and the internal impedance of the battery  increases. Battery capacity also reduced during the higher/lower temperatures. The present work describes the laboratory made lithium ion battery behaviour features at different operation temperatures. The pouch-type battery was prepared by exploiting LiCoO<sub>2</sub> cathode material synthesized by novel synthetic approach referred as Carbon Combustion Synthesis of Oxides (CCSO). The main goal of this paper focuses on evaluation of the efficiency of positive electrode produced by CCSO method. Performance studies of battery showed that the capacity fade of pouch type battery increases with increase in temperature. The experimental results demonstrate the dramatic effects on cell self-heating upon electrochemical performance. The study involves an extensive analysis of discharge and charge characteristics of battery at each temperature following 30 cycles. After 10 cycles, the battery cycled at RT and 45 °C showed, the capacity fade of 20% and 25% respectively. The discharge capacity for the battery cycled at 25 °C was found to be higher when compared with the battery cycled at 0 °C and 45 °C. The capacity of the battery also decreases when cycling at low temperatures. It was important time to charge the battery was only 2.5 hours to obtain identical nominal capacity under the charging protocol. The decrease capability of battery cycled at high temperature can be explained with secondary active material loss dominating the other losses.</p>

Diagnostics and Prognostics of Lithium-Ion Batteries

2015 ◽  
Author(s):  
Zhimin Xi ◽  
Rong Jing ◽  
Cheol Lee
Keyword(s):  
Lithium Ion Batteries ◽  
Lithium Ion ◽  
Remaining Useful Life ◽  
State Of Charge ◽  
Data Driven ◽  
State Of Health ◽  
Li Ion Batteries ◽  
Battery State Of Charge ◽  
Li Ion ◽  
Useful Life

This paper investigates recent research on battery diagnostics and prognostics especially for Lithium-ion (Li-ion) batteries. Battery diagnostics focuses on battery models and diagnosis algorithms for battery state of charge (SOC) and state of health (SOH) estimation. Battery prognostics elaborates data-driven prognosis algorithms for predicting the remaining useful life (RUL) of battery SOC and SOH. Readers will learn not only basics but also very recent research developments on battery diagnostics and prognostics.

Improving the electrochemical performance of the LiNi0.5Mn1.5O4spinel by polypyrrole coating as a cathode material for the lithium-ion battery

2015 ◽  
Vol 3 (1) ◽  
pp. 404-411 ◽  
Author(s):  
Xuan-Wen Gao ◽  
Yuan-Fu Deng ◽  
David Wexler ◽  
Guo-Hua Chen ◽  
Shu-Lei Chou ◽  
...  
Keyword(s):  
Elevated Temperature ◽  
Electrochemical Performance ◽  
Cathode Material ◽  
Electrochemical Properties ◽  
Lithium Ion Battery ◽  
Cathode Materials ◽  
Lithium Ion ◽  
Li Ion Batteries ◽  
Li Ion ◽  
Conductive Polypyrrole

Conductive polypyrrole (PPy)-coated LiNi0.5Mn1.5O4(LNMO) composites are applied as cathode materials in Li-ion batteries, and their electrochemical properties are explored at both room and elevated temperature.

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