Optimal charging strategies in lithium-ion battery

Klein, Reinhardt; Chaturvedi, N.A.; Christensen, Jake; Ahmed, Jasim; Findeisen, Rolf; Kojić, Aleksandar

doi:10.1109/acc.2011.5991497

Cited by 159 publications

(99 citation statements)

References 13 publications

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“…Smith et al utilized a reduced-order, linearized electrochemical model for state estimation and prediction of maximum, safe current draw [7]. Klein et al use a detailed electrochemical model with nonlinear model predictive control to determine optimal charging trajectories subject to state constraints [8]. Hu et al use equivalent circuit battery models to optimize charge time and power loss subject to state of charge, current, voltage, and charge time constraints [9].…”

Section: Introductionmentioning

confidence: 99%

Enhanced Performance of Li-Ion Batteries via Modified Reference Governors and Electrochemical Models

Pérez

Shahmohammadhamedani

Moura

2015

IEEE/ASME Trans. Mechatron.

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Abstract-This paper examines reference governor (RG) methods for satisfying state constraints in Li-ion batteries. Mathematically, these constraints are formulated from a first principles electrochemical model. Consequently, the constraints explicitly model specific degradation mechanisms, such as lithium plating, lithium depletion, and overheating. This contrasts with the present paradigm of limiting measured voltage, current, and/or temperature. The critical challenges, however, are that (i) the electrochemical states evolve according to a system of nonlinear partial differential equations, and (ii) the states are not physically measurable. Assuming available state and parameter estimates, this paper develops RGs for electrochemical battery models. The results demonstrate how electrochemical model state information can be utilized to ensure safe operation, while simultaneously enhancing energy capacity, power, and charge speeds in Li-ion batteries.

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Section: Introductionmentioning

confidence: 99%

Enhanced Performance of Li-Ion Batteries via Modified Reference Governors and Electrochemical Models

Pérez

Shahmohammadhamedani

Moura

2015

IEEE/ASME Trans. Mechatron.

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“…A model for a lithium-ion battery consisting of a PDAE system [2] with boundary conditions [1] and an ODE for the temperature [3] has been considered. The problem of time-optimal charging has been solved with a direct method as well as with the induced optimization problem.…”

Section: Discussionmentioning

confidence: 99%

“…This paper describes a model for the occuring processes in a battery based on different formulations [2] in the literature. We investigate time-optimal battery charging which has been stated by [3] and solved therein by an NMPC scheme. Here, we present two other solution techniques [4,5] and discuss more mathematical aspects of the problem.…”

Section: Introduction and Model Formulationmentioning

confidence: 99%

Optimal control for lithium‐ion batteries

Vossen

Struck

Roos

2015

Proc Appl Math and Mech

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Modelling, simulation and optimal control for a lithium-ion battery cell is discussed. The model involves ionic concentrations, currents and potentials in the electrodes and the separator together with the battery temperature as state variables. The resulting system is a nonlinear PDAE system with 10 partial, 1 ordinary differential and 4 algebraic equations involving the ButlerVolmer kinetics for describing the interaction of ionic currents and potentials. Time-optimal charging of the battery subject to age-preventing leads to a state-constrained optimal control problem which is solved in two ways. A first-discretize-thenoptimize approach leads to a high-dimensional nonlinear optimization problem which is solved by an efficient solver. As an alternative, a feedback control law along an active arc of the state constraint of order 1 is derived to formulate and solve the corresponding so-called induced optimization problem.

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“…[19][20][21][22][23][24] Efforts in optimal control and nonlinear model predictive control, incorporating a SPM and other reduced order models have been published. 6,7 A mathematical reformulation method [25][26][27][28] gives rise to a computationally efficient model that can be solved in milliseconds without compromising on accuracy. These reformulation techniques consist of spectral methods (specifically orthogonal collocation) where, depending on number of collocation points in the anode, separator, and cathode, models can be generated with varying degree of accuracy.…”

Section: Model Descriptionmentioning

confidence: 99%

“…Methekar et al 5 looked at the problem of energy maximization for a set time with constraints on voltage using Control Vector Parametrization (CVP). Klein et al 6 considered the minimum-time charging problem while including constraints on temperature rise and side reactions. Rahimian et al 7 calculated the optimal charging current as a function of cycle number for a lithium-ion battery experiencing capacity fade using a single-particle model (SPM).…”

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confidence: 99%

Optimal Charging Profiles with Minimal Intercalation-Induced Stresses for Lithium-Ion Batteries Using Reformulated Pseudo 2-Dimensional Models

Suthar

Northrop

Braatz

et al. 2014

J. Electrochem. Soc.

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This paper illustrates the application of dynamic optimization in obtaining the optimal current profile for charging a lithium-ion battery by restricting the intercalation-induced stresses to a pre-determined limit estimated using a pseudo 2-dimensional (P2D) model. This paper focuses on the problem of maximizing the charge stored in a given time while restricting capacity fade due to intercalation-induced stresses. Conventional charging profiles for lithium-ion batteries (e.g., constant current followed by constant voltage or CC-CV) are not derived by considering capacity fade mechanisms, which are not only inefficient in terms of life-time usage of the batteries but are also slower by not taking into account the changing dynamics of the system. Lithium-ion chemistries are attractive for many applications due to high cell voltage, high volumetric and gravimetric energy density (100 Wh/kg), high power density (300 W/kg), good temperature range, low memory effect, and relatively long battery life.1-3 Capacity fade, underutilization, and thermal runaway are the main issues that need to be addressed in order to use a lithium-ion battery efficiently and safely over a long life.In order to address the aforementioned issues and increase battery utilization, smarter battery management systems are required which can exploit the dynamics of a battery to derive better operational strategies. Recognizing the potential of reducing the weight and volume of these batteries by 20-25% for vehicular applications, the Department of Energy has recently initiated a $30M program through ARPA-E named Advanced Management and Protection of Energy Storage Devices (AMPED). 4 The use of physically meaningful models in deriving these strategies has received attention. Methekar et al. 5 looked at the problem of energy maximization for a set time with constraints on voltage using Control Vector Parametrization (CVP). Klein et al. 6 considered the minimum-time charging problem while including constraints on temperature rise and side reactions. Rahimian et al. 7 calculated the optimal charging current as a function of cycle number for a lithium-ion battery experiencing capacity fade using a single-particle model (SPM). Hoke et al.9 used a lithium-ion battery life-time model to reduce battery degradation in a variable electricity cost environment using the SPM. Previous efforts included the derivation of optimal charging profiles considering various phenomena that account for capacity fade separately (plating over-potential at the anode, 13 side reaction during charging, 6 thermal degradation, 10 intercalation-induced stress using SPM 11 etc.). Fracture of solid electrode particles due to intercalation induced stresses is one of the dominant capacity fade mechanics which affect the battery capacity in two ways: 12 (1) It leads to loss of solid phase due to isolation from the electronically conducting matrix of electrode. (2) It also increases the surface area, which lead to SEI * Electrochemical Society Student Member.* * Electrochemical Soci...

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Optimal charging strategies in lithium-ion battery

Cited by 159 publications

References 13 publications

Enhanced Performance of Li-Ion Batteries via Modified Reference Governors and Electrochemical Models

Enhanced Performance of Li-Ion Batteries via Modified Reference Governors and Electrochemical Models

Optimal control for lithium‐ion batteries

Optimal Charging Profiles with Minimal Intercalation-Induced Stresses for Lithium-Ion Batteries Using Reformulated Pseudo 2-Dimensional Models

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