A survey of mathematics-based equivalent-circuit and electrochemical battery models for hybrid and electric vehicle simulation

Seaman, Aden; Dao, Thanh–Son; McPhee, John

doi:10.1016/j.jpowsour.2014.01.057

Cited by 380 publications

(177 citation statements)

References 80 publications

Supporting

Mentioning

159

Contrasting

Unclassified

Order By: Relevance

“…The Coulomb counting SoC estimation technique has been used extensively in the literature [50,56,[58][59][60] and can be used to determine and update the battery cells SoC during simulations. It counts the charge transferred from or to the battery in order to calculate the remaining available capacity, expressed as the SoC [54].…”

Section: State Of Charge Estimationmentioning

confidence: 99%

Lithium Ion Batteries—Development of Advanced Electrical Equivalent Circuit Models for Nickel Manganese Cobalt Lithium-Ion

et al. 2016

View full text Add to dashboard Cite

Abstract:In this paper, advanced equivalent circuit models (ECMs) were developed to model large format and high energy nickel manganese cobalt (NMC) lithium-ion 20 Ah battery cells. Different temperatures conditions, cell characterization test (Normal and Advanced Tests), ECM topologies (1st and 2nd Order Thévenin model), state of charge (SoC) estimation techniques (Coulomb counting and extended Kalman filtering) and validation profiles (dynamic discharge pulse test (DDPT) and world harmonized light vehicle profiles) have been incorporated in the analysis. A concise state-of-the-art of different lithium-ion battery models existing in the academia and industry is presented providing information about model classification and information about electrical models. Moreover, an overview of the different steps and information needed to be able to create an ECM model is provided. A comparison between begin of life (BoL) and aged (95%, 90% state of health) ECM parameters (internal resistance (R o ), polarization resistance (R p ), activation resistance (R p2 ) and time constants (τ) is presented. By comparing the BoL to the aged parameters an overview of the behavior of the parameters is introduced and provides the appropriate platform for future research in electrical modeling of battery cells covering the ageing aspect. Based on the BoL parameters 1st and 2nd order models were developed for a range of temperatures (15˝C, 25˝C, 35˝C, 45˝C). The highest impact to the accuracy of the model (validation results) is the temperature condition that the model was developed. The 1st and 2nd order Thévenin models and the change from normal to advanced characterization datasets, while they affect the accuracy of the model they mostly help in dealing with high and low SoC linearity problems. The 2nd order Thévenin model with advanced characterization parameters and extended Kalman filtering SoC estimation technique is the most efficient and dynamically correct ECM model developed.

show abstract

Section: State Of Charge Estimationmentioning

confidence: 99%

Lithium Ion Batteries—Development of Advanced Electrical Equivalent Circuit Models for Nickel Manganese Cobalt Lithium-Ion

et al. 2016

View full text Add to dashboard Cite

show abstract

“…Different types of physics-based battery modeling, from electrochemicalto circuit-based modeling schemes, have been studied in a comprehensive survey by Seaman et al [5]. However, circuit-based models are not accurate enough in some control-oriented problems, which are essential in electric vehicles design.…”

Section: Introductionmentioning

confidence: 99%

Parameter estimation of an electrochemistry-based lithium-ion battery model

Masoudi

Uchida

McPhee

2015

Journal of Power Sources

Self Cite

View full text Add to dashboard Cite

Parameters for an electrochemistry-based Lithium-ion battery model are estimated using the homotopy optimization approach. A high-fidelity model of the battery is presented based on chemical and electrical phenomena. Equations expressing the conservation of species and charge for the solid and electrolyte phases are combined with the kinetics of the electrodes to obtain a system of differential-algebraic equations (DAEs) governing the dynamic behavior of the battery. The presence of algebraic constraints in the governing dynamic equations makes the optimization problem challenging: a simulation is performed in each iteration of the optimization procedure to evaluate the objective function, and the initial conditions must be updated to satisfy the constraints as the parameter values change. The ε-embedding method is employed to convert the original DAEs into a singularly perturbed system of ordinary differential equations, which are then used to simulate the system efficiently. The proposed numerical procedure demonstrates excellent perfor- * Corresponding author. The final publication is available at Elsevier via http://doi.org/10.1016/j.jpowsour.2015.04.154 © 2015 mance in the estimation of parameters for the Lithium-ion battery model, compared to direct methods that are either unstable or incapable of converging. The obtained results and estimated parameters demonstrate the efficacy of the proposed simulation approach and homotopy optimization procedure.

show abstract

“…As mentioned in Introduction, neither first-principles (or "white boxes") nor data-driven (or "black boxes") methods are valid. On the one hand, although the electrochemical, thermodynamic, and transport phenomena that define the behaviour of a Li-Ion battery are well known [16], white models are not valid because these models depend on a large number of parameters that are not provided by the manufacturer [17]. On the other hand, black boxes are unreliable when predicting unforeseen states and cannot incorporate prior knowledge about the mentioned phenomena [18].…”

Section: State Of the Art In The State Of Health Monitoringmentioning

confidence: 99%

A Model-Based Virtual Sensor for Condition Monitoring of Li-Ion Batteries in Cyber-Physical Vehicle Systems

et al. 2017

View full text Add to dashboard Cite

A model-based virtual sensor for assessing the health of rechargeable batteries for cyber-physical vehicle systems (CPVSs) is presented that can exploit coarse data streamed from on-vehicle sensors of current, voltage, and temperature. First-principle-based models are combined with knowledge acquired from data in a semiphysical arrangement. The dynamic behaviour of the battery is embodied in the parametric definition of a set of differential equations, and fuzzy knowledge bases are embedded as nonlinear blocks in these equations, providing a human understandable reading of the State of Health of the CPVS that can be easily integrated in the fleet through-life management.

show abstract

A survey of mathematics-based equivalent-circuit and electrochemical battery models for hybrid and electric vehicle simulation

Cited by 380 publications

References 80 publications

Lithium Ion Batteries—Development of Advanced Electrical Equivalent Circuit Models for Nickel Manganese Cobalt Lithium-Ion

Lithium Ion Batteries—Development of Advanced Electrical Equivalent Circuit Models for Nickel Manganese Cobalt Lithium-Ion

Parameter estimation of an electrochemistry-based lithium-ion battery model

A Model-Based Virtual Sensor for Condition Monitoring of Li-Ion Batteries in Cyber-Physical Vehicle Systems

Contact Info

Product

Resources

About