2014 IEEE Conference and Expo Transportation Electrification Asia-Pacific (ITEC Asia-Pacific) 2014
DOI: 10.1109/itec-ap.2014.6941260
View full text |Buy / Rent full text
|
Sign up to set email alerts
|

Abstract: This paper proposed a novel approach to state-ofcharge (SoC) estimation of the lithium-ion batteries (LiBs) used in electric vehicles (EVs) based on the extended Kalman filtering (EKF). An improved lumped parameter model was developed for describing the dynamic behavior of the LiBs with an optimized open circuit voltage. This improved approach can reduces model error effectively. Other model parameters were identified via the genetic algorithm (GA) to optimizes the polarization time constant. Experimental and … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
6
0

Year Published

2017
2017
2020
2020

Publication Types

Select...
3

Relationship

0
3

Authors

Journals

citations
Cited by 7 publications
(6 citation statements)
references
References 17 publications
(19 reference statements)
0
6
0
Order By: Relevance
“…The formula using identified diffusion capacitance was derived to determine the SOH of a Li-ion battery. The GA fused with some other model-based estimation methods was used to estimate the SOC [155,[167][168][169][170][171]. The GA was also utilized in tuning of the fading KF to further improve the estimation of the SOC for a Li-ion battery [126].…”
Section: Reference Mae (%)mentioning
confidence: 99%
“…The formula using identified diffusion capacitance was derived to determine the SOH of a Li-ion battery. The GA fused with some other model-based estimation methods was used to estimate the SOC [155,[167][168][169][170][171]. The GA was also utilized in tuning of the fading KF to further improve the estimation of the SOC for a Li-ion battery [126].…”
Section: Reference Mae (%)mentioning
confidence: 99%
“…Figure 4 shows the 2 curve fitting models: 1RC network and 2RC network. In Figure 4, the 1RC network and the 2RC network indicate the one resistance plus first-order RC [9] and the one resistance plus second-order RC [10]- [12], respectively. In this paper, we select the 2RC network for the cell modeling of the lithiumion battery as a tradeoff between model complexity and RMSE performance.…”
Section: Temperature-dependent Ecmmentioning
confidence: 99%
“…In addition, some practical ECMs are based on the resistance-capacitance (RC) networks. Such ECM types include one resistance plus first-order RC [9], one resistance plus second-order RC [10]- [12], and one resistance plus third-order RC [13], [14]. For the lithium-ion battery in the electrified vehicle, a temperature-dependent ECM is required.…”
Section: Introductionmentioning
confidence: 99%
“…The approaches presented in [59,146] use a GA to identify time constant and other parameters of the battery model (fractional order and EIS-based model [59], and Thevenin ECM [146]). Despite these proposals utilizing a UKF-based SoC and EKF-based SoC estimation, respectively, the model parameter estimation using the GA is crucial, and accounts for the high accuracy of the methods.…”
Section: Apply Crossover In the Populationmentioning
confidence: 99%
“…In [112], OCV is calculated based on a Thevenin ECM, and then, by using it, SoC is estimated through a fading KF where the fading factors that optimize the KF are calculated by the means of a GA. GA is used as an optimization technique to estimate different states of the battery. The approaches presented in [59,146] use a GA to identify time constant and other parameters of the battery model (fractional order and EIS-based model [59], and Thevenin ECM [146]). Despite these proposals utilizing a UKF-based SoC and EKF-based SoC estimation, respectively, the model parameter estimation using the GA is crucial, and accounts for the high accuracy of the methods.…”
Section: Apply Crossover In the Populationmentioning
confidence: 99%