Theory of battery ageing in a lithium-ion battery: Capacity fade, nonlinear ageing and lifetime prediction

Atalay, S.; Sheikh, Muhammad Aman; Mariani, Alessandro; Merla, Yu; Bower, Ed; Widanage, Widanalage Dhammika

doi:10.1016/j.jpowsour.2020.229026

Cited by 141 publications

(51 citation statements)

References 31 publications

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“…The slow timescale is degradation, which occurs on the scale of months and is characterized by the State of Health (SOH). State of Health can be assumed to be approximately constant over a single cycle, and vary linearly over a few cycles -although there are exceptions at the start and end of life, especially after the 'knee point' [28,38].…”

Section: Inter-cycle Extrapolationmentioning

confidence: 99%

Accelerated battery lifetime simulations using adaptive inter-cycle extrapolation algorithm

Sulzer¹,

Mohtat²,

Pannala³

et al. 2021

Preprint

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We propose algorithms to speed up physics-based battery lifetime simulations by one to two orders of magnitude compared to the state-of-the-art. First, we propose a reformulation of the Single Particle Model with side reactions to remove algebraic equations and hence reduce stiffness, with 3x speed-up in simulation time (intra-cycle reformulation). Second, we introduce an algorithm that makes use of the difference between the `fast' timescale of battery cycling and the `slow' timescale of battery degradation by adaptively selecting and simulating representative cycles, skipping other cycles, and hence requires fewer cycle simulations to simulate the entire lifetime (adaptive inter-cycle extrapolation). This algorithm is demonstrated with a specific degradation mechanism but can be applied to various models of aging phenomena. In the particular case study considered, simulations of the entire lifetime are performed in under 5 seconds. This opens the possibility for much faster and more accurate model development, testing, and comparison with experimental data.

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Section: Inter-cycle Extrapolationmentioning

confidence: 99%

Accelerated battery lifetime simulations using adaptive inter-cycle extrapolation algorithm

Sulzer¹,

Mohtat²,

Pannala³

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…The authors do not make the claim that the battery model used was an as accurate as possible model of a battery of this sort. Additionally, there are many different aspects to the ageing of Li-ion batteries [39,40], not just the cycling based on usage which was used here. However, as the aim in this study was to find out whether the ETS or ERS characteristics affect battery ageing, it was deemed that valuable information could still be gathered by estimating the ageing this way.…”

Section: Battery Modelmentioning

confidence: 99%

“…The ageing of the battery is evaluated after each drive cycle simulation in order 280 to assess how much of the lifetime of the battery that is consumed. The simulation 281 produces a time series of the SOC which is then analyzed by a rainflow algorithm [38] in 282 order to count the number of cycles at a specific depth of discharge (DoD) [39]. Cycles…”

Section: Battery Modelmentioning

confidence: 99%

Energy Supply to Buses on a Conductive Electric Road: An Evaluation of Charger Topologies and Electric Road Characteristics

Karlsson

Alaküla

2021

WEVJ

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An electric road system (ERS) enables transfer of electric energy to a moving vehicle, making it possible to reduce the capacity—and cost—of the battery and the need for static chargers. A conductive electric road allows for relatively low complexity whilst being able to provide high levels of power. When utilising a conductive electric road, safety precautions must be considered with regard to isolation between the charging supply (the electric road) and the vehicle’s traction voltage system (TVS), since no protective Earth connection can be guaranteed. Isolation can be achieved by separating the two systems galvanically or by double isolating the entire TVS and all equipment connected to it on-board the vehicle. This study used the experimental results from a previous paper to model and evaluate three different electric powertrains/charger topologies, including a novel integrated design fulfilling the required safety features. The models were used in a full vehicle model and further investigated in a city bus scenario in terms of how charging performance, energy consumption and battery ageing are affected by the aforementioned charging topologies and electric road characteristic. We discovered that charging topology has a strong influence on energy consumption, and that electric road characteristics have a strong influence on battery ageing.

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“…The aging process of a battery is very complex and is subject of intense research [28]. In general, various complex techniques to prevent aging have been proposed for the case of small residential storage devices [29], electric vehicles [13], and large-scale BESS for power systems [21,30].…”

Section: Bess Aging-preventing Operation and Strategy For Sfcmentioning

confidence: 99%

The Impact of Aging-Preventive Algorithms on BESS Sizing under AGC Performance Standards

et al. 2021

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It is normally accepted that Battery Energy Storage Systems improve frequency regulation by providing fast response to the Automatic Generation Control. However, currently available control strategies may lead to early Energy Storage Systems aging given that Automatic Generation Control requirements are increasing due to zero carbon power generation integration. In this sense, it is important to analyze the aging phenomena in order to assess the technical–economical usefulness of Battery Energy Storage Systems towards zero carbon power systems. In order to avoid early aging, various proposals on aging-reducing algorithms can be found; however, it is unclear if those aging-reducing algorithms affect the performance of Battery Energy Storage Systems. It is also unclear whether those effects must be internalized to properly dimension the capacity of Battery Energy Storage Systems to both comply with performance standards and to prevent early aging. Thus, this paper estimates the storage capacity of a Battery Energy Storage Systems to comply with Automatic Generation Control performance standard under aging-reducing operating algorithms by dynamics simulations of a reduced-order, empirically-validated model of the Electric Reliability Council of Texas. The results show the relationship between the required performance of Automatic Generation Control and Battery Energy Storage System capacity, considering a 1-year simulation of Automatic Generation Control dynamics. It can be concluded that the compliance with performance standards is strongly related to the storage capacity, regardless of how fast the device can inject or withdraw power from the grid. Previous results in the state-of-the-art overlook the quantification of this relationship between compliance with performance standards and storage capacity.

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Theory of battery ageing in a lithium-ion battery: Capacity fade, nonlinear ageing and lifetime prediction

Cited by 141 publications

References 31 publications

Accelerated battery lifetime simulations using adaptive inter-cycle extrapolation algorithm

Accelerated battery lifetime simulations using adaptive inter-cycle extrapolation algorithm

Energy Supply to Buses on a Conductive Electric Road: An Evaluation of Charger Topologies and Electric Road Characteristics

The Impact of Aging-Preventive Algorithms on BESS Sizing under AGC Performance Standards

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