Dynamic Model of Li-Ion Batteries Incorporating Electrothermal and Ageing Aspects for Electric Vehicle Applications

Mesbahi, Tedjani; Rizoug, Nassim; Bartholoméüs, P.; Sadoun, R.; Khenfri, Fouad; Moigne, Philippe Le

doi:10.1109/tie.2017.2714118

Cited by 67 publications

(38 citation statements)

References 32 publications

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Section: Second-order Thevenin Modelmentioning

confidence: 99%

“…Thevenin models can be used in combination with others to create a multidisciplinary model. The study performed in [48] develops a model considering three aspects: (i) Electrical model, (ii) thermal model, and (iii) degradation model for Li-Ion batteries installed in EVs. Authors apply a modified particle swarm optimization (PSO) for parameter defining and results are validated experimentally.…”

Section: Second-order Thevenin Modelmentioning

confidence: 99%

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Analysis of the Current Electric Battery Models for Electric Vehicle Simulation

et al. 2019

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Electric vehicles (EVs) are a promising technology to reduce emissions, but its development enormously depends on the technology used in batteries. Nowadays, batteries based on lithium-ion (Li-Ion) seems to be the most suitable for traction, especially nickel-manganese-cobalt (NMC) and nickel-cobalt-aluminum (NCA). An appropriate model of these batteries is fundamental for the simulation of several processes inside an EV, such as the state of charge (SoC) estimation, capacity and power fade analysis, lifetime calculus, or for developing control and optimization strategies. There are different models in the current literature, among which the electric equivalent circuits stand out, being the most appropriate model when performing real-time simulations. However, impedance models for battery diagnosis are considered very attractive. In this context, this paper compares and contrasts the different electrical equivalent circuit models, impedance models, and runtime models for battery-based EV applications, addressing their characteristics, advantages, disadvantages, and usual applications in the field of electromobility. In this sense, this paper serves as a reference for the scientific community focused on the development of control and optimization strategies in the field of electric vehicles, since it facilitates the choice of the model that best suits the needs required.

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Section: Second-order Thevenin Modelmentioning

confidence: 99%

Section: Second-order Thevenin Modelmentioning

confidence: 99%

Analysis of the Current Electric Battery Models for Electric Vehicle Simulation

et al. 2019

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“…45 It was also investigated by using the dual exponential function 46 and the impact on the Open Circuit Voltage (OCV) tests were conducted. 51 A rapid screening and regrouping approach was proposed to manage the large-scale retired lithium-ion battery cells in second-use applications by using the neural network algorithm. 48 The co-estimation method was studied for the SOC determination, in which the mixed strategist dynamics was proposed along with the maximum entropy principles.…”

Section: Introductionmentioning

confidence: 99%

“…49 The electrochemical model was conducted by using the charging optimization 50 and the dynamic model was investigated incorporating electro-thermal and aging aspects. 51 A rapid screening and regrouping approach was proposed to manage the large-scale retired lithium-ion battery cells in second-use applications by using the neural network algorithm. 52 Therefore, it is necessary to construct the adaptive model based on the internal mechanism theory, which can achieve the optimum life for f lithium-ion battery packs, protecting the instantaneous power supply capacity and improving its energy utilization.…”

Section: Introductionmentioning

confidence: 99%

An improved packing equivalent circuit modeling method with the cell‐to‐cell consistency state evaluation of the internal connected lithium‐ion batteries

Wang

Shi

Fernandez

et al. 2019

Energy Science & Engineering

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The existing equivalent modeling methods reported in literature focuses mainly on the battery cells and do not take the packing consistency state into consideration, which exists on the internal connected cells of the lithium‐ion battery pack. An improved equivalent circuit model is constructed and reported in this manuscript for the first time, which can be used to characterize the working characteristics of the packing lithium‐ion batteries. A new equilibrium concept named as state of balance is proposed as well as the calculation process, which is realized by considering the real‐time detected internal battery cell voltages. In addition, this new equilibrium concept aims to obtain more information on the real‐time consistency characterization of the battery pack. The improved adaptive equivalent circuit model is investigated by using the improved splice modeling method, in which the statistical noise properties are corrected and the additional parallel resistance‐capacitance circuit is introduced. The parameter correction treatment is carried out by comparing the estimated and experimental detected closed circuit voltages. Furthermore, the tracking error is found to be 0.005 V and accounts for 0.119% of the nominal battery voltage. By taking the packing consistency state and temperature correction into consideration, the accurate working characteristic expression is realized in the improved equivalent circuit modeling process. Finally, the model proposed in this manuscript presents a great number of advantages compared to other methods reported so far, like has the high accuracy, and the ability to protect the security of the lithium‐ion battery pack in the power supply application.

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“…The electrochemical impedance was tracked for the batteries (Piret, Granjon, Guillet, & Cattin, 2016). The dynamic model study was also initiated for lithium-ion batteries (Mesbahi et al, 2018). Existing studies have achieved remarkable results in the construction of equivalent models of lithium-ion batteries.…”

Section: Introductionmentioning

confidence: 99%