scholarly journals Understanding non-linearity in electrochemical systems using multisine-based non-linear characterization

2021 ◽  
pp. 014233122110459
Author(s):  
Chuanxin Fan ◽  
Thomas R.B. Grandjean ◽  
Kieran O’Regan ◽  
Emma Kendrick ◽  
Widanalage D. Widanage
Keyword(s):  
Charge Transfer ◽  
Lithium Ion Battery ◽  
Linear Response ◽  
Lithium Ion ◽  
Voltage Response ◽  
Model Parameters ◽  
Sensitive Parameter ◽  
Electrochemical Processes ◽  
Significant Difference ◽  
Non Linear

Background: With the development of advanced characterization techniques, lithium-ion battery non-linearities have recently gained increased attention which can benefit battery health diagnosis and ageing mechanism identification. In comparison to conventional single sine wave-based methods, the multisine-based non-linear characterization method has the advantage of capturing the dynamic voltage response within a short testing duration, and therefore has further development potential for on-board applications. However, understanding lithium-ion battery electrochemical processes that contribute to battery non-linearities is still unclear. Methods: In this paper, the sensitivity of the Doyle–Fuller–Newman model parameters are analysed in the frequency domain to investigate the electrochemical processes that contribute to the non-linear dynamics of the voltage response. To begin with, the non-linearities of the Doyle–Fuller–Newman model with validated parameters are characterized and compared to experimental data from a commercial cell. This demonstrated a significant difference between the mathematical model and the non-linearities determined experimentally. Then, a global sensitivity analysis is applied to determine the most sensitive parameter contributing to battery non-linearities. Finally, the appropriate value of the most sensitive parameter which results in the closest non-linear response to the commercial battery is estimated through minimizing the root mean square error. Results: The results show that the charge transfer coefficient is the most sensitive parameter contributing to battery non-linearities among the Doyle–Fuller–Newman model parameters. The non-linear response of the Doyle–Fuller–Newman model is validated with good agreement with the experimental results, when the Butler–Volmer kinetic is asymmetrical due to the unequal anodic and cathodic charge transfer coefficients.

A Temperature Dependent, Single Particle, Lithium Ion Cell Model Including Electrolyte Diffusion

2014 ◽  
Vol 137 (1) ◽  
Author(s):  
Tanvir R. Tanim ◽  
Christopher D. Rahn ◽  
Chao-Yang Wang
Keyword(s):  
Single Particle ◽  
Lithium Ion ◽  
Particle Model ◽  
Voltage Response ◽  
Model Parameters ◽  
Battery Management System ◽  
Temperature Dependent ◽  
Lithium Ion Cell ◽  
Pulse Charge ◽  
Wide Range

Low-order, explicit models of lithium ion cells are critical for real-time battery management system (BMS) applications. This paper presents a seventh-order, electrolyte enhanced single particle model (ESPM) with electrolyte diffusion and temperature dependent parameters (ESPM-T). The impedance transfer function coefficients are explicit in terms of the model parameters, simplifying the implementation of temperature dependence. The ESPM-T model is compared with a commercially available finite volume based model and results show accurate matching of pulse responses over a wide range of temperature (T) and C-rates (I). The voltage response to 30 s pulse charge–discharge current inputs is within 5% of the commercial code for 25 °C<T<50 °C at I≤12.5C and -10 °C<T<50°C at I≤1C for a graphite/nickel cobalt manganese (NCM) lithium ion cell.

Model Identification of Power Lithium-Ion Battery Based on Laplace Transform

2014 ◽  
Vol 953-954 ◽  
pp. 775-779
Author(s):  
En Guang Hou ◽  
Xin Qiao ◽  
Guang Min Liu
Keyword(s):  
Laplace Transform ◽  
Lithium Ion Battery ◽  
Equivalent Circuit ◽  
Least Squares Method ◽  
Equivalent Circuit Model ◽  
Lithium Ion ◽  
Second Order ◽  
Equivalent Model ◽  
Model Parameters ◽  
Test Model

In allusion to nonlinear characteristic of power lithium-ion battery, presented a method for identifying of power lithium-ion battery based on Laplace transform. First, analyzed the characteristics of the equivalent circuit model of power lithium-ion battery, determined the model of second-order RC equivalent circuit; Second, established equation of second-order RC equivalent circuit and conducted a Laplace transform; Third,using the massive data of charge-discharge test,model parameters was identified by least-squares method; Simulation results show that the method can effectively identify the equivalent model parameters, and model parameters small error.

Modeling and Simulation Research on Lithium-Ion Battery in Electric Vehicles Based on Genetic Algorithm

2014 ◽  
Vol 494-495 ◽  
pp. 246-249
Author(s):  
Cheng Lin ◽  
Xiao Hua Zhang
Keyword(s):  
Genetic Algorithm ◽  
Lithium Ion Battery ◽  
Stress Test ◽  
Lithium Ion ◽  
Model Parameters ◽  
Test Accuracy ◽  
Battery Management System ◽  
Battery Management ◽  
Simulation Research ◽  
Battery Model

Based on the genetic algorithm (GA), a novel type of parameters identification method on battery model was proposed. The battery model parameters were optimized by genetic optimization algorithm and the other parameters were identified through the hybrid pulse power characterization (HPPC) test. Accuracy and efficiency of the battery model were validated with the dynamic stress test (DST). Simulation and experiment results shows that the proposed model of the lithium-ion battery with identified parameters was accurate enough to meet the requirements of the state of charge (SoC) estimation and battery management system.

scholarly journals Advanced Lithium-Ion Battery Model for Power System Performance Analysis

Energies ◽  
2020 ◽  
Vol 13 (10) ◽  
pp. 2411 ◽  
Author(s):  
Szymon Potrykus ◽  
Filip Kutt ◽  
Janusz Nieznański ◽  
Francisco Jesús Fernández Morales
Keyword(s):  
Lithium Ion Battery ◽  
System Performance ◽  
System Development ◽  
Storage System ◽  
Lithium Ion ◽  
Model Parameters ◽  
Diffusion Resistance ◽  
System Modelling ◽  
Battery Management System ◽  
Battery Model

The paper describes a novel approach in battery storage system modelling. Different types of lithium-ion batteries exhibit differences in performance due to the battery anode and cathode materials being the determining factors in the storage system performance. Because of this, the influence of model parameters on the model accuracy can be different for different battery types. These models are used in battery management system development for increasing the accuracy of SoC and SoH estimation. The model proposed in this work is based on Tremblay model of the lithium-ion battery. The novelty of the model lies in the approach used for parameter estimation as a function of battery physical properties. To make the model perform more accurately, the diffusion resistance dependency on the battery current and the Peukert effect were also included in the model. The proposed battery model was validated using laboratory measurements with a LG JP 1.5 lithium-ion battery. Additionally, the proposed model incorporates the influence of the battery charge and discharge current level on battery performance.

scholarly journals Non-linear responses of Rutford Ice Stream, Antarctica, to semi-diurnal and diurnal tidal forcing

2010 ◽  
Vol 56 (195) ◽  
pp. 167-176 ◽  
Author(s):  
Matt A. King ◽  
Tavi Murray ◽  
Andy M. Smith
Keyword(s):  
Shear Stress ◽  
Linear Response ◽  
Small Variation ◽  
Model Parameters ◽  
Similar Response ◽  
Mean Flow ◽  
Tidal Forcing ◽  
Ice Stream ◽  
Non Linear ◽  
Basal Shear

AbstractModulation of the flow of Rutford Ice Stream, Antarctica, has been reported previously at semi-diurnal, diurnal, fortnightly and semi-annual periods. A model that includes non-linear response to tidal forcing has been shown to fit closely observations at fortnightly frequencies. Here we examine that model further and test its fit at a larger set of observed frequencies, including the large semi-annual displacement. We show analytically that, when forced by major tidal terms, the model (using a basal shear stress exponent m = 3) predicts several discrete response periods from 4 hours to 0.5 years. We examine a 1.5 year GPS record from Rutford Ice Stream and find that the model, when forced by a numerical tide model, is able to reproduce the reported semi-annual signal. We confirm that about 5% of the mean flow is due solely to the (m = 3) non-linear response to tidally varying basal shear stress. Our best-fitting set of model parameters is similar to those originally reported using a much shorter data record, although with noticeably improved fit, suggesting these parameters are robust. We find that m ≈ 3 fits the data well, but that m ≈ 2 does not. Furthermore, we find that a small variation in flow over the 18.6 year lunar node tide cycle is expected. Fits to semi-diurnal and diurnal terms remain relatively poor, possibly due to viscoelastic effects that are not included in the model and reduced GPS data quality at some discrete periods. For comparison, we predict the response of Bindschadler Ice Stream and Lambert Glacier and show, given identical model parameters, a similar response pattern but with ∼1–2 orders of magnitude smaller variability; these may still be measurable and hence useful in testing the applicability of this model to other locations.

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