Deterministic models of Li-ion battery aging: It is a matter of scale

Jafari, Mehdi; Khan, Khalid; Gauchía, Lucía

doi:10.1016/j.est.2018.09.002

Cited by 72 publications

(41 citation statements)

References 86 publications

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“…This question was also stated in Figure 3. The performance of battery packs, mostly Li-Ion batteries, are discussed in terms of aging in [55,57,[90][91][92][93], in terms of temperature impact in [94,95] and also of state of balance/ health [96], in terms of both aging and temperature of operation in [56], in terms of both aging and sizing in [97], and in terms of both aging and energy management/power estimation in [98][99][100]. Also, the experimental settlement has a strong influence on the outcomes reported, and for that reason we can find out contradictory results in many papers.…”

Section: Discussionmentioning

confidence: 99%

Are Personal Electric Vehicles Sustainable? A Hybrid E-Bike Case Study

Machedon-Pisu

Borza

2019

Sustainability

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As the title suggests, the sustainability of personal electric vehicles is in question. In terms of life span, range, comfort, and safety, electric vehicles, such as e-cars and e-buses, are much better than personal electric vehicles, such as e-bikes. However, electric vehicles present greater costs and increased energy consumption. Also, the impact on environment, health, and fitness is more negative than that of personal electric vehicles. Since transportation vehicles can benefit from hybrid electric storage solutions, we address the following question: Is it possible to reach a compromise between sustainability and technology constraints by implementing a low-cost hybrid personal electric vehicle with improved life span and range that is also green? Our methodology consists of life cycle assessment and performance analyses tackling the facets of the sustainability challenges (economy, society, and environment) and limitations of the electric storage solutions (dependent on technology and application) presented herein. The hybrid electric storage system of the proposed hybrid e-bike is made of batteries, supercapacitors, and corresponding power electronics, allowing the optimal control of power flows between the system's components and application's actuators.Our hybrid e-bike costs less than a normal e-bike (half or less), does not depend on battery operation for short periods of time (a few seconds), has better autonomy than most personal electric vehicles (more than 60 km), has a greater life span (a few years more than a normal e-bike), has better energy efficiency (more than 90%), and is much cleaner due to the reduced number of batteries replaced per life time (one instead of two or three).

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Section: Discussionmentioning

confidence: 99%

Are Personal Electric Vehicles Sustainable? A Hybrid E-Bike Case Study

Machedon-Pisu

Borza

2019

Sustainability

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“…Battery degradation costs can be an essential economic variable when designing an installation with battery power storage [2]. Several models in the technical literature can estimate batteries' degradation costs, sometimes including thermal and electrical aspects [3][4][5][6][7]. Depending on the significance of the degradation costs, the best solutions may or may not include extensive use of the batteries.…”

Section: Introductionmentioning

confidence: 99%

“…It is necessary to estimate degradation costs accurately. While selecting the models studied, the fact that the feedback of values in real-time is not available when mathematical models are used for optimization problems were taken into account [6,7].…”

Section: Introductionmentioning

confidence: 99%

“…In other reviews, Thompson [4] studied and identified three main models: NREL, Wang, and MOBICUS; and Lucu et al [5] reviewed adaptive aging models, which are of interest for on-board systems but not for our objective. The review carried out by Jafari et al [6] is useful for optimization problems; this review presented deterministic models that are easy to apply, as they provide functions fitted to real data. Finally, a review by Ahmadian et al [7] is of interest, in which several classifications of mathematical model studies related to battery degradation were presented.…”

Section: Introductionmentioning

confidence: 99%

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Estimating Degradation Costs for Non-Cyclic Usage of Lithium-Ion Batteries

2020

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Estimating the degradation costs of lithium-ion batteries is essential to the designs of many systems because batteries are increasingly used in diverse applications. In this study, cyclic and calendar degradation models of lithium batteries were considered in optimization problems with randomized non-cyclic batteries use. Such models offer realistic results. Electrical, thermal, and degradation models were applied for lithium nickel cobalt manganese oxide (NMC) and lithium iron phosphate (LFP) technologies. Three possible strategies were identified to estimate degradation costs based on cell models. All three strategies were evaluated via simulations and validated by comparing the results with those obtained by other authors. One strategy was discarded because it overestimates costs, while the other two strategies give good results, and are suitable for estimating battery degradation costs in optimization problems that require deterministic models.

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“…However, they are less computationally intensive and are easy to implement in online applications. The model-based approach, on the other hand, is based on the historical data of the battery performance and relies on the mathematical expression for the battery capacity fade evaluation [5]. Electrochemical models, equivalent circuit models (ECMs), and empirical aging models are different groups of this approach.…”

Section: Introductionmentioning

confidence: 99%

Hierarchical Bayesian Model for Probabilistic Analysis of Electric Vehicle Battery Degradation

Jafari

Brown

Gauchía

2019

IEEE Trans. Transp. Electrific.

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This paper proposes a hierarchical Bayesian model for probabilistic estimation of the electric vehicle battery capacity fade. Since the battery aging factors such as temperature, current, and state of charge are not fixed, and they change in different times, locations and by the different users, deterministic models with constant parameters cannot accurately evaluate the battery capacity fade. Therefore, a probabilistic presentation of the capacity fade including uncertainties of the measurements/ observations of the variables can be a proper solution. We have developed a hierarchical Bayesian Network model for the electric vehicle battery capacity fade considering multiple external variables. The mathematical expression of the model is extracted based on Bayes' theorem, the probability distributions for all variables and their dependencies are carefully chosen where the Metropolis-Hastings Markov Chain Monte Carlo sampling method is applied to generate the posterior distributions. The model is trained with a subset of experimental data (85%) to obtain its unseen parameters and tested with other 15% of data to prove its accuracy. Also, three case studies for different drivers, different grid services' frequencies, and different climates are explored to show model's flexibility with different input data. The developed model needs training data for parameter tuning in different conditions. However, after training, it has more than 95% precision in estimating the battery capacity fade percentage. Index Terms-Bayesian Networks, Electric Vehicle Battery, Markov

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Deterministic models of Li-ion battery aging: It is a matter of scale

Cited by 72 publications

References 86 publications

Are Personal Electric Vehicles Sustainable? A Hybrid E-Bike Case Study

Are Personal Electric Vehicles Sustainable? A Hybrid E-Bike Case Study

Estimating Degradation Costs for Non-Cyclic Usage of Lithium-Ion Batteries

Hierarchical Bayesian Model for Probabilistic Analysis of Electric Vehicle Battery Degradation

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