Real-Time Estimation of Lithium-Ion Concentration in Both Electrodes of a Lithium-Ion Battery Cell Utilizing Electrochemical–Thermal Coupling

2017 ◽  
Vol 139 (3) ◽  
Author(s):  
Satadru Dey ◽  
Beshah Ayalew
Keyword(s):  
Real Time ◽  
Unscented Kalman Filter ◽  
Lithium Ion ◽  
Time Estimation ◽  
Li Ion Battery ◽  
Battery Cell ◽  
Thermal Dynamics ◽  
Estimation Scheme ◽  
Real Time Estimation ◽  
Li Ion

This paper proposes and demonstrates an estimation scheme for Li-ion concentrations in both electrodes of a Li-ion battery cell. The well-known observability deficiencies in the two-electrode electrochemical models of Li-ion battery cells are first overcome by extending them with a thermal evolution model. Essentially, coupling of electrochemical–thermal dynamics emerging from the fact that the lithium concentrations contribute to the entropic heat generation is utilized to overcome the observability issue. Then, an estimation scheme comprised of a cascade of a sliding-mode observer and an unscented Kalman filter (UKF) is constructed that exploits the resulting structure of the coupled model. The approach gives new real-time estimation capabilities for two often-sought pieces of information about a battery cell: (1) estimation of cell-capacity and (2) tracking the capacity loss due to degradation mechanisms such as lithium plating. These capabilities are possible since the two-electrode model needs not be reduced further to a single-electrode model by adding Li conservation assumptions, which do not hold with long-term operation. Simulation studies are included for the validation of the proposed scheme. Effect of measurement noise and parametric uncertainties is also included in the simulation results to evaluate the performance of the proposed scheme.

scholarly journals Lithium-ion battery models: a comparative study and a model-based powerline communication

2017 ◽  
Vol 15 ◽  
pp. 83-91 ◽  
Author(s):  
Fida Saidani ◽  
Franz X. Hutter ◽  
Rares-George Scurtu ◽  
Wolfgang Braunwarth ◽  
Joachim N. Burghartz
Keyword(s):  
Real Time ◽  
Equivalent Circuit ◽  
Lithium Ion ◽  
Complex Model ◽  
Physical Models ◽  
Chemical System ◽  
Li Ion Battery ◽  
Battery Cell ◽  
Powerline Communication ◽  
Li Ion

Abstract. In this work, various Lithium-ion (Li-ion) battery models are evaluated according to their accuracy, complexity and physical interpretability. An initial classification into physical, empirical and abstract models is introduced. Also known as white, black and grey boxes, respectively, the nature and characteristics of these model types are compared. Since the Li-ion battery cell is a thermo-electro-chemical system, the models are either in the thermal or in the electrochemical state-space. Physical models attempt to capture key features of the physical process inside the cell. Empirical models describe the system with empirical parameters offering poor analytical, whereas abstract models provide an alternative representation. In addition, a model selection guideline is proposed based on applications and design requirements. A complex model with a detailed analytical insight is of use for battery designers but impractical for real-time applications and in situ diagnosis. In automotive applications, an abstract model reproducing the battery behavior in an equivalent but more practical form, mainly as an equivalent circuit diagram, is recommended for the purpose of battery management. As a general rule, a trade-off should be reached between the high fidelity and the computational feasibility. Especially if the model is embedded in a real-time monitoring unit such as a microprocessor or a FPGA, the calculation time and memory requirements rise dramatically with a higher number of parameters. Moreover, examples of equivalent circuit models of Lithium-ion batteries are covered. Equivalent circuit topologies are introduced and compared according to the previously introduced criteria. An experimental sequence to model a 20 Ah cell is presented and the results are used for the purposes of powerline communication.

scholarly journals A Review of State of Health Estimation of Energy Storage Systems: Challenges and Possible Solutions for Futuristic Applications of Li-Ion Battery Packs in Electric Vehicles

2019 ◽  
Vol 16 (4) ◽  
Author(s):  
Sudipta Bijoy Sarmah ◽  
Pankaj Kalita ◽  
Akhil Garg ◽  
Xiao-dong Niu ◽  
Xing-Wei Zhang ◽  
...  
Keyword(s):  
Real Time ◽  
Electric Vehicles ◽  
Lithium Ion ◽  
Time Estimation ◽  
State Of Health ◽  
Li Ion Battery ◽  
Super Capacitor ◽  
Advantages And Disadvantages ◽  
Battery Packs ◽  
Li Ion

Lithium-ion (Li-ion) battery pack is vital for storage of energy produced from different sources and has been extensively used for various applications such as electric vehicles (EVs), watches, cookers, etc. For an efficient real-time monitoring and fault diagnosis of battery operated systems, it is important to have a quantified information on the state-of-health (SoH) of batteries. This paper conducts comprehensive literature studies on advancement, challenges, concerns, and futuristic aspects of models and methods for SoH estimation of batteries. Based on the studies, the methods and models for SoH estimation have been summarized systematically with their advantages and disadvantages in tabular format. The prime emphasis of this review was attributed toward the development of a hybridized method which computes SoH of batteries accurately in real-time and takes self-discharge into its account. At the end, the summary of research findings and the future directions of research such as nondestructive tests (NDT) for real-time estimation of battery SoH, finding residual SoH for the recycled batteries from battery packs, integration of mechanical aspects of battery with temperature, easy assembling–dissembling of battery packs, and hybridization of battery packs with photovoltaic and super capacitor are discussed.

Estimation of Lithium-Ion Concentrations in Both Electrodes of a Lithium-Ion Battery Cell

2015 ◽  
Author(s):  
Satadru Dey ◽  
Beshah Ayalew ◽  
Pierluigi Pisu
Keyword(s):  
Unscented Kalman Filter ◽  
Sliding Mode ◽  
Lithium Ion ◽  
Ion Concentration ◽  
Spherical Particles ◽  
Particle Model ◽  
Thermal Dynamics ◽  
Ion Concentrations ◽  
Estimation Scheme ◽  
Li Ion

For control and estimation tasks in battery management systems, the benchmark Li-ion cell electrochemical pseudo-two-dimensional (P2D) model is often reduced to the Single Particle Model (SPM). The original SPM consists of two electrodes approximated as spherical particles with spatially distributed Li-ion concentration. However, the Li-ion concentration states in these two-electrode models are known to be weakly observable from the voltage output. This has led to the prevalent use of reduced models in literature that generally approximate Li-ion concentration states in one electrode as an algebraic function of that in the other electrode. In this paper, we remove such approximations and show that the addition of the thermal model to the electrochemical SPM essentially leads to observability of the Li-ion concentration states in both electrodes from voltage and temperature measurements. Then, we propose an estimation scheme based on this SPM coupled with lumped thermal dynamics that estimates the Li-ion concentrations in both electrodes. Moreover, these Li-ion concentration estimates also enable the estimation of the cell capacity. The estimation scheme consists of a sliding mode observer cascaded with an Unscented Kalman filter (UKF). Simulation studies are included to show the effectiveness of the proposed scheme.

scholarly journals A New All-Solid-State Lithium-Ion Battery Working without a Separator in an Electrolyte

2018 ◽  
Author(s):  
Seonggyu Cho ◽  
Shinho Kim ◽  
Wonho Kim ◽  
Seok Kim ◽  
Sungsook Ahn
Keyword(s):  
Solid State ◽  
Ionic Conductivity ◽  
Solid Electrolyte ◽  
System Development ◽  
Lithium Ion ◽  
Internal Resistance ◽  
Li Ion Battery ◽  
Battery Cell ◽  
Metal Anode ◽  
Li Ion

Considering the safety issues of Li ion batteries, all-solid-state polymer electrolyte has been one of the promising solutions. In this point, achieving a Li ion conductivity in the solid state electrolytes comparable to liquid electrolytes (>1 mS/cm) is particularly challenging. Employment of polyethylene oxide (PEO) solid electrolyte has not been not enough in this point due to high crystallinity. In this study, hybrid solid electrolyte (HSE) systems are designed with Li1.3Al0.3Ti0.7(PO4)3(LATP), PEO and Lithium hexafluorophosphate (LiPF6) or Lithium bis(trifluoromethanesulfonyl)imide (LiTFSI). Hybrid solid cathode (HSC) is also designed using LATP, PEO and lithium cobalt oxide (LiCoO2, LCO)—lithium manganese oxide (LiMn2O4, LMO). The designed HSE system displays 3.0 × 10−4 S/cm (55 ℃) and 1.8 × 10−3 S/cm (23 ℃) with an electrochemical stability as of 6.0 V without any separation layer introduction. Li metal (anode)/HSE/HSC cell in this study displays initial charge capacity as of 123.4/102.7 mAh/g (55 ℃) and 73/57 mAh/g (25 °C). To these systems, Succinonitrile (SN) has been incorporated as a plasticizer for practical secondary Li ion battery system development to enhance ionic conductivity. The incorporated SN effectively increases the ionic conductivity without any leakage and short-circuits even under broken cell condition. The developed system also overcomes the typical disadvantages of internal resistance induced by Ti ion reduction. In this study, optimized ionic conductivity and low internal resistance inside the Li ion battery cell have been obtained, which suggests a new possibility in the secondary Li ion battery development.

scholarly journals From Battery Cell to Electrodes: Real-Time Estimation of Charge and Health of Individual Battery Electrodes

2020 ◽  
Vol 67 (3) ◽  
pp. 2167-2175 ◽  
Author(s):  
Satadru Dey ◽  
Ying Shi ◽  
Kandler Smith ◽  
Andrew Colclasure ◽  
Xuemin Li
Keyword(s):  
Real Time ◽  
Time Estimation ◽  
Battery Cell ◽  
Real Time Estimation
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