A reliability-based design concept for lithium-ion battery pack in electric vehicles

Liu, Zhitao; Tan, Cher-Ming; Feng, Linrun

doi:10.1016/j.ress.2014.10.010

Cited by 70 publications

(22 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…After the acquisition of the charge-discharge data of a cell, we analyzed the discharge curve using the ECBE model to calculate the maximum capacity of the cell (Q m ). Experimental SoH was computed for the batteries tested for various cycles using Equation 2 [8,16,24] using the maximum capacity of the batteries after the first cycle (Q max (fresh)) and after aging (Q max (aged)).…”

Section: Semi-empirical Capacity Fading Modelmentioning

confidence: 99%

“…Later we employed the Levenberg-Marquart fitting algorithm (LMA) to provide an accurate estimate of the local minima. The semi-empirical model used in this work is described by Equation (3) [16]. Parameters (k1, k2, k3) in the model can be extracted by substituting SoH obtained using Equation (2) from 3 different cycles into Equation (3).…”

Section: Ecbe Modelmentioning

confidence: 99%

“…While the ECBE model is accurate and comprehensive, the required computation time to obtain the values of the model parameters is excessive and renders its unsuitability for in-situ SoH estimation. In this work, a semi-empirical capacity fading model [16] is investigated to determine the SoH of the cells under cycle aging test. This model can describe the cell's degradation behavior due to discharge rate, temperature, and cycle numbers.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Semi-Empirical Capacity Fading Model for SoH Estimation of Li-Ion Batteries

et al. 2019

View full text Add to dashboard Cite

A fast and accurate capacity estimation method for lithium-ion batteries is developed. This method applies our developed semi-empirical model to a discharge curve of a lithium-ion battery for the determination of its maximum stored charge capacity after each discharge cycle. This model provides an accurate state-of-health (SoH) estimation with a difference of less than 2.22% when compared with the electrochemistry-based electrical (ECBE) SoH calculation. The model parameters derived from a lithium-ion battery can also be applied to other cells in the same pack with less than 2.5% difference from the complex ECBE model, showing the extendibility of the model. The parameters (k1, k2, and k3) calculated in the work can also be used to study the changes in battery internal structure, such as capacity losses at normal conditions, as well as cycling at high temperatures. The time for estimation after each discharge cycle is only 5 s, making it is suitable for on-line in-situ estimation.

show abstract

Section: Semi-empirical Capacity Fading Modelmentioning

confidence: 99%

Section: Ecbe Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Semi-Empirical Capacity Fading Model for SoH Estimation of Li-Ion Batteries

et al. 2019

View full text Add to dashboard Cite

show abstract

“…The second is to ensure the reliability of vehicles, which is achieved by increasing the reliability of their main parts: traction energy source and traction motor, by controlling the technical level and condition at all stages of the life cycle [6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Determining the Quality of Electric Motors by Vibro-Diagnostic Characteristics

Arhun¹,

Migal²,

Hnatov³

et al. 2018

EAI Endorsed Transactions on Energy Web

View full text Add to dashboard Cite

Experimental studies of vibrations of asynchronous electric motors (EMs) of the electric bus traction electric drive are carried out in the paper. The presented studies are based on generalization of the diagnostic features of vibration characteristics and statistics concerning the limiting values of vibration parameters of EMs and their dependence on the technical condition. The analysis of the obtained results allowed us to determine the permissible vibration levels of EMs in the frequency range from 5 Hz to 10 kHz. The method of diagnosing EMs traction electric drive according to the indicators of vibration levels is developed, which allows to evaluate their technical condition. The values of the permissible vibrational accelerations of the electric bus EMs are determined, which enable to estimate their technical level. This method allowed to develop classes of evaluation of the EMs technical condition by the level of their vibration, which makes possible to predict their resource.

show abstract

“…These methodologies are based on methods such as Petri nets, FMEA, Markov Chains and fault trees. In a recent article [Zhitao Liu et al, 2014], a method on the design and analysis of lithium-ion (Li-ion) battery pack from the reliability perspective is presented. The analysis is based on the degradation of the battery pack, which is related to the cells configuration in the battery pack and the state of health (SoH) of all the Li-ion cells in the pack.…”

Section: Reliability Designmentioning

confidence: 99%

An overall methodology for reliability prediction of mechatronic systems design with industrial application

Habchi

Barthod

2016

Reliability Engineering & System Safety

View full text Add to dashboard Cite

International audienceWe propose in this paper an overall ten-step methodology dedicated to the analysis and quantification of reliability during the design phase of a mechatronic system, considered as a complex system. The ten steps of the methodology are detailed according to the downward side of the V-development cycle usually used for the design of complex systems. Two main phases of analysis are complementary and cover the ten steps, qualitative analysis and quantitative analysis. The qualitative phase proposes to analyze the functional and dysfunctional behavior of the system and then determine its different failure modes and degradation states, based on external and internal functional analysis, organic and physical implementation, and dependencies between components, with consideration of customer specifications and mission profile. The quantitative phase is used to calculate the reliability of the system and its components, based on the qualitative behavior patterns, and considering data gathering and processing and reliability targets. Systemic approach is used to calculate the reliability of the system taking into account: the different technologies of a mechatronic system (mechanics, electronics, electrical ...), dependencies and interactions between components and external influencing factors. To validate the methodology, the ten steps are applied to an industrial system, the smart actuator of Pack'Aero Company

show abstract

A reliability-based design concept for lithium-ion battery pack in electric vehicles

Cited by 70 publications

References 29 publications

Semi-Empirical Capacity Fading Model for SoH Estimation of Li-Ion Batteries

Semi-Empirical Capacity Fading Model for SoH Estimation of Li-Ion Batteries

Determining the Quality of Electric Motors by Vibro-Diagnostic Characteristics

An overall methodology for reliability prediction of mechatronic systems design with industrial application

Contact Info

Product

Resources

About