Electro-aging model development of nickel-manganese-cobalt lithium-ion technology validated with light and heavy-duty real-life profiles

Hosen, Sazzad; Karimi, Danial; Kalogiannis, Theodoros; Pirooz, Ashkan; Jaguemont, Joris; Berecibar, Maitane; Mierlo, Joeri Van

doi:10.1016/j.est.2020.101265

Cited by 49 publications

(28 citation statements)

References 76 publications

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“…A wide range of operating condition results are manifested with mathematical equations simplifying different degradation aspects. Authors have developed such a parameterized model for NMC batteries in their previous research, which has been validated for different dynamic applications (Hosen et al, 2020). The baseline of the model is adapted for the investigated cell in this work, and the outline framework is depicted in Figure 3.…”

Section: Semi-empirical Modelmentioning

confidence: 99%

“…The coefficients and the surface fit orders are for the X and Y axes, respectively. This cycling degradation equation is formulated from in-house NMC battery datasets generated in Batteries2020 (Batteries2020, 2013 and BATTLE (BATTLE, 2013) projects and adapted for the investigated NMC cell, whereas the calendar life capacity fade fitting equations are inherited from the author's previous work (Hosen et al, 2020). The polynomials are represented by Arrhenius equation and the fitting equations relating the calendar life capacity fade to the function of the temperature, SoC, and time.…”

Section: Semi-empirical Modelmentioning

confidence: 99%

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Battery lifetime prediction and performance assessment of different modeling approaches

et al. 2021

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Lithium-ion battery technologies have conquered the current energy storage market as the most preferred choice thanks to their development in a longer lifetime. However, choosing the most suitable battery aging modeling methodology based on investigated lifetime characterization is still a challenge. In this work, a comprehensive aging dataset of nickel-manganese-cobalt oxide (NMC) cell is used to develop and/or train different capacity fade models to compare output responses. The assessment is conducted for semi-empirical modeling (SeM) approach against a machine learning model and an artificial neural network model. Among all, the nonlinear autoregressive network (NARXnet) can predict the capacity degradation most precisely minimizing the computational effort as well. This research work signifies the importance of lifetime methodological choice and model performance in understanding the complex and nonlinear Liion battery aging behavior.

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Section: Semi-empirical Modelmentioning

confidence: 99%

Section: Semi-empirical Modelmentioning

confidence: 99%

Battery lifetime prediction and performance assessment of different modeling approaches

et al. 2021

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“…18,24 An optimistic outlook for battery costs (including mark-up) at 100 USD kWh À1 is, therefore, conceivable. For specific energy, current commercial NMC batteries for stationary storage with lower specific energy but higher cycle lives have order of 3,000 cycles with 30% degradation in simulated cycle life in heavy-duty truck real life drive cycles, using deep 5-95 SoC cycling and operating temperatures of 45 C. 29 For the conservative parameter set, we use performance below this level, assuming 30% battery degradation after 1,500 cycles and 125 Wh kg À1 specific energy, which is in line with older values in the recent literature on electric trucks. For optimistic values, we first consider recent developments indicating that considerably more long lived Li-ion cells with high specific energy are about to be commercialized.…”

Section: Battery Pack Specificationsmentioning

confidence: 99%

The feasibility of heavy battery electric trucks

Nykvist

Olsson

2021

Joule

125

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“…Figure 8 shows the relation between the 1D-3D models and the modeling methodology. The second-order electro-thermal model would not be explained in this work because it has already been published in our previous work ( Hosen et al., 2020 ). Figure 9 exhibits the heat generation of the LiC cell during the cycling regime.…”

Section: Numerical Analysismentioning

confidence: 99%

A hybrid thermal management system for high power lithium-ion capacitors combining heat pipe with phase change materials

Karimi

Hosen

Behi

et al. 2021

Heliyon

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Lithium-ion capacitor (LiC) technology is an energy storage system (ESS) that combines the working mechanism of electric double-layer capacitors (EDLC) and lithium-ion batteries (LiB). When LiC is supposed to work under high power applications, the inevitable heat loss threatens the cell's performance and lifetime. Therefore, a proper thermal management system (TMS) can remove the generated heat of the LiC during high cycling conditions. In this paper, a hybrid TMS (HTMS) using phase change materials (PCM) and six flat heat pipes is proposed to maintain the temperature profile below 40 °C under a high current rate of 150 A for 1400 s profile without any pause. Two K-type thermocouples (T1 & T2) are responsible for monitoring the experiments' temperature evolution in the experiments. Numerical analysis is also performed and verified with experimental results to analyze the temperature profile numerically. The experimental and numerical simulation comprises three case studies, including the cell's temperature under natural convection, temperature distribution when using the heat pipe TMS, and temperature distribution when using HTMS. The results reveal that the HTMS is an exceptionally robust cooling system since it reduces the T 1 temperature by 35% compared to the natural convection case study, while the heat pipe TMS can reduce the T 1 temperature by 15% compared to the same case study.

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Electro-aging model development of nickel-manganese-cobalt lithium-ion technology validated with light and heavy-duty real-life profiles

Cited by 49 publications

References 76 publications

Battery lifetime prediction and performance assessment of different modeling approaches

Battery lifetime prediction and performance assessment of different modeling approaches

The feasibility of heavy battery electric trucks

A hybrid thermal management system for high power lithium-ion capacitors combining heat pipe with phase change materials

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