State-of-charge Estimation for Lithium-ion Batteries Using a Multi-state Closed-loop Observer

Zhao, Yunlan; Huang, Yun; Liu, Shude; Huirong, Jiao; Wang, Chengzhen

doi:10.6113/jpe.2014.14.5.1038

Cited by 5 publications

(4 citation statements)

References 20 publications

(18 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In general, there is a fractional order aspect of equivalent models for electrochemical systems [14,15,16]. Moreover, the fractional models have been well defined by Fractional Order Calculus (FOC) [17]. Thanks to fractional order calculus, the several dynamic and chemical phenomena of Lithium battery have been perfectly characterized.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Kalman filter Observer for SoC prediction of Lithium cells

Ayadi¹,

Lahiani²,

Derbel³

2017

Adv. sci. technol. eng. syst. j.

View full text Add to dashboard Cite

Section: Introductionmentioning

confidence: 99%

“…The FKF is recursive algorithm and the form of state space (17) has been expressed as discrete form from stochastic theory:…”

Section: Fractional Kalman Filter (Fkf) Observer Designmentioning

confidence: 99%

Kalman filter Observer for SoC prediction of Lithium cells

Ayadi¹,

Lahiani²,

Derbel³

2017

Adv. sci. technol. eng. syst. j.

View full text Add to dashboard Cite

“…Several methods of estimating the SOC and SOH of a battery have been proposed by using coulomb counting, artificial neutron networks (ANNs), fuzzy logic (FL), and extended Kalman filters (EKFs) [2]- [10]. The coulomb counting method can be simply implemented by integrating the battery current over time [11].…”

Section: Introductionmentioning

confidence: 99%

State Estimation Technique for VRLA Batteries for Automotive Applications

Duong¹,

Tran²,

Choi³

et al. 2016

Journal of Power Electronics

View full text Add to dashboard Cite

The state-of-charge (SOC) and state-of-health (SOH) estimation of batteries play important roles in managing batteries for automotive applications. However, an accurate state estimation of a battery is difficult to achieve because of certain factors, such as measurement noise, highly nonlinear characteristics, strong hysteresis phenomenon, and diffusion effect of batteries. In certain vehicular applications, such as idle stop-start systems (ISSs), significant errors in SOC/SOH estimation may lead to a failure in restarting a combustion engine after the shut-off period of the engine when the vehicle is at rest, such as at a traffic light. In this paper, a dual extended Kalman filter algorithm with a dynamic equivalent circuit model of a lead-acid battery is proposed to deal with this problem. The proposed algorithm adopts a battery model by taking into account the hysteresis phenomenon, diffusion effect, and parameter variations for accurate state estimations of the battery. The validity of the proposed algorithm is verified through experiments by using an absorbed glass mat valve-regulated lead-acid battery and a battery sensor cable for commercial ISS vehicles.

show abstract

“…These can be prevented through the implementation of a battery management system (BMS). The BMS monitors the voltage of each cell and protects the battery cells from over-charging and discharging [6][7][8]. Another function of the BMS is the protection from unbalanced cell voltages.…”

Section: Introductionmentioning

confidence: 99%

Cell Balancing Method in Flyback Converter without Cell Selection Switch of Multi-Winding Transformer

Kim¹,

Park²

2016

Journal of Electrical Engineering and Technology

View full text Add to dashboard Cite

-This paper presents a cell balancing method for a single switch flyback converter with a multi-winding transformer. The conventional method using a flyback converter with a multi-winding transformer is simple and easy to control, but the voltage of each secondary winding coil might be non-uniform because of the unequal effective turn-ratio. In particular, it is difficult to control the nonuniform effect using turn-ratios because secondary coil has a limited number of turns. The nonuniform secondary voltages disturb the cell balancing procedure and induce an unbalance in cell voltages. Individual cell control by adding a switch for each cell can reduce the undesirable effect. However, the circuit becomes bulky, resulting in additional loss. The proposed method here uses the conventional flyback converter with an adjustment made to the output filters of the cells, instead of the additional switch. The magnitude of voltage applied to a particular cell can be reduced or increased according to the adjusted filter and the selected switching frequency. An analysis of the conventional converter configuration and the filter design method reveals the possibility of adequate cell balancing control without any additional switch on the secondary side.

show abstract

State-of-charge Estimation for Lithium-ion Batteries Using a Multi-state Closed-loop Observer

Cited by 5 publications

References 20 publications

Kalman filter Observer for SoC prediction of Lithium cells

Kalman filter Observer for SoC prediction of Lithium cells

State Estimation Technique for VRLA Batteries for Automotive Applications

Cell Balancing Method in Flyback Converter without Cell Selection Switch of Multi-Winding Transformer

Contact Info

Product

Resources

About