Electrochemical Model-Based State of Charge and Capacity Estimation for a Composite Electrode Lithium-Ion Battery

Bartlett, Alexander; Marcicki, James; Onori, Simona; Rizzoni, Giorgio; Yang, Xiaoling; Miller, Ted

doi:10.1109/tcst.2015.2446947

Cited by 129 publications

(88 citation statements)

References 32 publications

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“…The approaches presented in [89][90][91][92] specifically develop EChMs for SoC estimation. Zou et al in [89] propose a model composed of four submodels that capture the electrochemical, thermal, electrical, and aging dynamics in a set of partial differential equations.…”

Section: Model-based Estimation Methodsmentioning

confidence: 99%

“…As one of the outputs of the full model is the SoC, it can be directly estimated by solving the system equations. Barlett et al in [90] present a reduced-order electrochemical model for different Li ion chemistries that are used in dual-nonlinear observers (KF, fixed interval Kalman smoother and particle filter), to estimate the cell SoC and loss of cyclable lithium over time. The research presented in [91] described an EChM where a set of discretized equations are used to estimate the SoC directly, and then SoC is compared with an approach where the EChM is written as a linearly spatially interconnected system.…”

Section: Model-based Estimation Methodsmentioning

confidence: 99%

“…Due to the electrochemical and thermal models of the batteries being highly nonlinear, EKF is used for estimating its parameters, followed by SoC [45,80,90]. The EKF method is also used in combination with CC and/or OCV, as proposed in [11,45,50,103].…”

Section: Real Batterymentioning

confidence: 99%

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SoC Estimation for Lithium-ion Batteries: Review and Future Challenges

2017

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Abstract:Energy storage emerged as a top concern for the modern cities, and the choice of the lithium-ion chemistry battery technology as an effective solution for storage applications proved to be a highly efficient option. State of charge (SoC) represents the available battery capacity and is one of the most important states that need to be monitored to optimize the performance and extend the lifetime of batteries. This review summarizes the methods for SoC estimation for lithium-ion batteries (LiBs). The SoC estimation methods are presented focusing on the description of the techniques and the elaboration of their weaknesses for the use in on-line battery management systems (BMS) applications. SoC estimation is a challenging task hindered by considerable changes in battery characteristics over its lifetime due to aging and to the distinct nonlinear behavior. This has led scholars to propose different methods that clearly raised the challenge of establishing a relationship between the accuracy and robustness of the methods, and their low complexity to be implemented. This paper publishes an exhaustive review of the works presented during the last five years, where the tendency of the estimation techniques has been oriented toward a mixture of probabilistic techniques and some artificial intelligence.

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Section: Model-based Estimation Methodsmentioning

confidence: 99%

Section: Model-based Estimation Methodsmentioning

confidence: 99%

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SoC Estimation for Lithium-ion Batteries: Review and Future Challenges

2017

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“…Battery electric models mainly include electrochemical model [6][7][8][9], reduced-order model [10][11][12][13], equivalent circuit model [14][15][16][17] and data-driven model [18][19][20]. For electrochemical model, Rahman et al [6] claimed that the battery electrochemical model should have the abilities to capture the spatiotemporal dynamics of battery concentration, the electrode potential for each phase and the BulterVolmer kinetic to control intercalation reaction.…”

Section: Battery Electric Modelmentioning

confidence: 99%

A brief review on key technologies in the battery management system of electric vehicles

et al. 2018

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Batteries have been widely applied in many high-power applications, such as electric vehicles (EVs) and hybrid electric vehicles, where a suitable battery management system (BMS) is vital in ensuring safe and reliable operation of batteries. This paper aims to give a brief review on several key technologies of BMS, including battery modelling, state estimation and battery charging. First, popular battery types used in EVs are surveyed, followed by the introduction of key technologies used in BMS. Various battery models, including the electric model, thermal model and coupled electro-thermal model are reviewed. Then, battery state estimations for the state of charge, state of health and internal temperature are comprehensively surveyed. Finally, several key and traditional battery charging approaches with associated optimization methods are discussed.

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“…This rather slow growth is due to numerous causes, among which certainly a higher cost of EVs, the uncertainty of the state of charge (SOC), and state of health estimation (SOH) of the EVs' batteries [1] but above all the problems related to the power production. In fact, in Italy, the power production is exclusively from fossil source, since Italy has renounced to the power production from nuclear sources since 2011.…”

Section: Introductionmentioning

confidence: 99%

Innovative mini-hydro device for the recharge of electric vehicles in urban areas

Balacco

Binetti

Caporaletti

et al. 2018

Int J Energy Environ Eng

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The aim of the present study is to evaluate the technical and economic feasibility of supplying recharge points for Electric Vehicles converting water pressure in excess into electric energy from a water distribution network. A real water distribution network was analyzed, by designing a power station consisting of three components: a Pump-as-Turbine, an ad hoc generator, and a control system. The last one controls the flow rate trend at the inlet of the Pump-as-Turbine to regulate the rotational speed corresponding to the optimal range of efficiency. Energy produced permits to supply a recharging point for Electric Vehicles on site with the aim to convert water pressure generally dissipated and, consequently, lost into a renewable energy and to reduce power grid congestion. The economic analysis confirms the convenience of the proposed power station, and overall, a comparable cost with pressure reduction valve devices normally adopted to control pressure pattern and leakages of a water distribution network.

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Electrochemical Model-Based State of Charge and Capacity Estimation for a Composite Electrode Lithium-Ion Battery

Cited by 129 publications

References 32 publications

SoC Estimation for Lithium-ion Batteries: Review and Future Challenges

SoC Estimation for Lithium-ion Batteries: Review and Future Challenges

A brief review on key technologies in the battery management system of electric vehicles

Innovative mini-hydro device for the recharge of electric vehicles in urban areas

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