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Electrochemical physics-based simulations of Li-ion batteries using a mesoscale 3D structure of porous electrodes are one of the most effective approaches for evaluating the local Li concentration in active materials and the Li-ion concentration in electrolytes. However, this approach requires considerable computational resources compared with a simple 2D or 1D homogeneous simulation. In this work, we developed an advanced electrochemical physics-based simulation method for Li-ion batteries that enabled a quasi-3D simulation of charge/discharge using only a single 2D slice image. The governing equations were based on typical theories of electrochemical reactions and ion transport. From referencing the 2D plane, the model was able to simulate both the Li concentration in the active material and the Li-ion concentration in the electrolyte for their subsequent consideration in a virtual 3D structure. To confirm the validity of our proposed model, a full 3D discharge simulation with randomly packed active material particles was performed and compared with the results of the quasi-3D model and a simple-2D model. Results indicated that the quasi-3D model properly reproduced the sliced Li and Li-ion concentrations simulated by the full 3D model in the charge/discharge process, whereas the simple-2D simulation partially overestimated or underestimated these concentrations. In addition, the quasi-3D model made it possible to dramatically decrease the computation time compared to the full-3D model. Finally, we applied the model to an actual scanning electron microscopy equipped with a focused ion beam (FIB-SEM) image of a positive electrode. Graphic abstract
Yoichi Takagishi; Takumi Yamanaka; Tatsuya Yamaue. Quasi-3D modeling of Li-ion batteries based on single 2D image. SN Applied Sciences 2021, 3, 1 -17.
AMA StyleYoichi Takagishi, Takumi Yamanaka, Tatsuya Yamaue. Quasi-3D modeling of Li-ion batteries based on single 2D image. SN Applied Sciences. 2021; 3 (6):1-17.
Chicago/Turabian StyleYoichi Takagishi; Takumi Yamanaka; Tatsuya Yamaue. 2021. "Quasi-3D modeling of Li-ion batteries based on single 2D image." SN Applied Sciences 3, no. 6: 1-17.
In this work, we developed an advanced electrochemical physics-based simulation method for Li-ion batteries that enabled a quasi-3D simulation of charge/discharge using only a single 2D slice image. The governing equations are based on typical theories of electrochemical reactions and ion transport. From referencing the 2D plane, the model was able to simulate both the Li concentration in the active material and the Li-ion concentration in the electrolyte for their subsequent consideration in a virtual 3D structure. To confirm the validity of our proposed model, a full 3D discharge simulation with randomly packed active material particles was performed and compared with the results of the quasi-3D model and a simple-2D model. Results indicated that the quasi-3D model properly reproduced the sliced Li and Li-ion concentrations simulated by the full 3D model in the charge/discharge process, whereas the simple-2D simulation partially overestimated or underestimated these concentrations. Finally, we applied the model to an actual Scanning Electron Microscopy equipped with a Focused Ion Beam (FIB-SEM) image of a positive electrode.
Yoichi Takagishi; Tatsuya Yamaue; Takumi Yamanaka. Quasi-3D Modeling of Li-ion Batteries Based on Single 2D Image. 2021, 1 .
AMA StyleYoichi Takagishi, Tatsuya Yamaue, Takumi Yamanaka. Quasi-3D Modeling of Li-ion Batteries Based on Single 2D Image. . 2021; ():1.
Chicago/Turabian StyleYoichi Takagishi; Tatsuya Yamaue; Takumi Yamanaka. 2021. "Quasi-3D Modeling of Li-ion Batteries Based on Single 2D Image." , no. : 1.
In this work, we developed an advanced electrochemical physics-based simulation method for Li-ion batteries that enabled a quasi-3D simulation of charge/discharge using only a single 2D slice image. The governing equations are based on typical theories of electrochemical reactions and ion transport. From referencing the 2D plane, the model was able to simulate both the Li concentration in the active material and the Li-ion concentration in the electrolyte for their subsequent consideration in a virtual 3D structure. To confirm the validity of our proposed model, a full 3D discharge simulation with randomly packed active material particles was performed and compared with the results of the quasi-3D model and a simple-2D model. Results indicated that the quasi-3D model properly reproduced the sliced Li and Li-ion concentrations simulated by the full 3D model in the charge/discharge process, whereas the simple-2D simulation partially overestimated or underestimated these concentrations. Finally, we applied the model to an actual Scanning Electron Microscopy equipped with a Focused Ion Beam (FIB-SEM) image of a positive electrode.
Yoichi Takagishi; Tatsuya Yamaue; Takumi Yamanaka. Quasi-3D Modeling of Li-ion Batteries Based on Single 2D Image. 2021, 1 .
AMA StyleYoichi Takagishi, Tatsuya Yamaue, Takumi Yamanaka. Quasi-3D Modeling of Li-ion Batteries Based on Single 2D Image. . 2021; ():1.
Chicago/Turabian StyleYoichi Takagishi; Tatsuya Yamaue; Takumi Yamanaka. 2021. "Quasi-3D Modeling of Li-ion Batteries Based on Single 2D Image." , no. : 1.
Lithium (Li)-ion battery thermal management systems play an important role in electric vehicles because the performance and lifespan of the batteries are affected by the battery temperature. This study proposes a framework to establish equivalent circuit models (ECMs) that can reproduce the multi-physics phenomenon of Li-ion battery packs, which includes liquid cooling systems with a unified method. We also demonstrate its utility by establishing an ECM of the thermal management systems of the actual battery packs. Experiments simulating the liquid cooling of a battery pack are performed, and a three-dimensional (3D) model is established. The 3D model reproduces the heat generated by the battery and the heat transfer to the coolant. The results of the 3D model agree well with the experimental data. Further, the relationship between the flow rate and pressure drop or between the flow rate and heat transfer coefficients is predicted with the 3D model, and the data are used for the ECM, which is established using MATLAB Simulink. This investigation confirmed that the ECM’s accuracy is as high as the 3D model even though its computational costs are 96% lower than the 3D model.
Takumi Yamanaka; Daiki Kihara; Yoichi Takagishi; Tatsuya Yamaue. Multi-Physics Equivalent Circuit Models for a Cooling System of a Lithium Ion Battery Pack. Batteries 2020, 6, 44 .
AMA StyleTakumi Yamanaka, Daiki Kihara, Yoichi Takagishi, Tatsuya Yamaue. Multi-Physics Equivalent Circuit Models for a Cooling System of a Lithium Ion Battery Pack. Batteries. 2020; 6 (3):44.
Chicago/Turabian StyleTakumi Yamanaka; Daiki Kihara; Yoichi Takagishi; Tatsuya Yamaue. 2020. "Multi-Physics Equivalent Circuit Models for a Cooling System of a Lithium Ion Battery Pack." Batteries 6, no. 3: 44.
The fracture toughness temperature dependence of ferritic steels in the ductile-to-brittle transition temperature region, predicted using the ASTM E1921 master curve (MC) and stress distribution T-scaling (CDS) methods, is presented in this paper. A total of 34 cases (i.e., combination of material heats and specimen types) including 661 fracture toughness test data were considered. First, the direct correlation between fracture toughness and yield stress—as suggested by the CDS method—was validated using machine learning techniques. Subsequently, the accuracy of the predictions obtained by each method was quantitatively evaluated using a coefficient of determination. In 25 out of the 34 cases, the CDS method showed better prediction ability than the MC method. In the other 9 cases, the difference between the two methods was small, if considered from an engineering perspective.
Toshiyuki Meshii; Goh Yakushi; Yoichi Takagishi; Yohei Fujimoto; Kenichi Ishihara. Quantitative comparison of the predictions of fracture toughness temperature dependence using ASTM E1921 master curve and stress distribution T-scaling methods. Engineering Failure Analysis 2020, 111, 104458 .
AMA StyleToshiyuki Meshii, Goh Yakushi, Yoichi Takagishi, Yohei Fujimoto, Kenichi Ishihara. Quantitative comparison of the predictions of fracture toughness temperature dependence using ASTM E1921 master curve and stress distribution T-scaling methods. Engineering Failure Analysis. 2020; 111 ():104458.
Chicago/Turabian StyleToshiyuki Meshii; Goh Yakushi; Yoichi Takagishi; Yohei Fujimoto; Kenichi Ishihara. 2020. "Quantitative comparison of the predictions of fracture toughness temperature dependence using ASTM E1921 master curve and stress distribution T-scaling methods." Engineering Failure Analysis 111, no. : 104458.
We have proposed a data-driven approach for designing the mesoscale porous structures of Li-ion battery electrodes, using three-dimensional virtual structures and machine learning techniques. Over 2000 artificial 3D structures, assuming a positive electrode composed of randomly packed spheres as the active material particles, are generated, and the charge/discharge specific resistance has been evaluated using a simplified physico-chemical model. The specific resistance from Li diffusion in the active material particles (diffusion resistance), the transfer specific resistance of Li+ in the electrolyte (electrolyte resistance), and the reaction resistance on the interface between the active material and electrolyte are simulated, based on the mass balance of Li, Ohm’s law, and the linearized Butler–Volmer equation, respectively. Using these simulation results, regression models, using an artificial neural network (ANN), have been created in order to predict the charge/discharge specific resistance from porous structure features. In this study, porosity, active material particle size and volume fraction, pressure in the compaction process, electrolyte conductivity, and binder/additives volume fraction are adopted, as features associated with controllable process parameters for manufacturing the battery electrode. As a result, the predicted electrode specific resistance by the ANN regression model is in good agreement with the simulated values. Furthermore, sensitivity analyses and an optimization of the process parameters have been carried out. Although the proposed approach is based only on the simulation results, it could serve as a reference for the determination of process parameters in battery electrode manufacturing.
Yoichi Takagishi; Takumi Yamanaka; Tatsuya Yamaue. Machine Learning Approaches for Designing Mesoscale Structure of Li-Ion Battery Electrodes. Batteries 2019, 5, 54 .
AMA StyleYoichi Takagishi, Takumi Yamanaka, Tatsuya Yamaue. Machine Learning Approaches for Designing Mesoscale Structure of Li-Ion Battery Electrodes. Batteries. 2019; 5 (3):54.
Chicago/Turabian StyleYoichi Takagishi; Takumi Yamanaka; Tatsuya Yamaue. 2019. "Machine Learning Approaches for Designing Mesoscale Structure of Li-Ion Battery Electrodes." Batteries 5, no. 3: 54.
A numerical model denoted the “Tri-bred model” is developed to accurately reproduce Li-ion battery nail penetration tests. The model considers the movement of the nail as well as the thermal decomposition reaction. Moreover, the “combustion volume” was defined to quantitatively evaluate the degree of combustion risk in a unique manner. The validity of the model was verified by comparison with experimental results. The model suitably described the experimental phenomena; the behavior of the “combustion volume” indicated a similar tendency to the gas emission degree during the experiment. To investigate the relationship between the experimental conditions and the degree of risk, a parametric study was performed and the results of “combustion degree” were compared. As a result, it was found that the nail speed was more strongly correlated with combustion risk than penetration position.
Takumi Yamanaka; Yoichi Takagishi; Yasufumi Tozuka; Tatsuya Yamaue. Modeling lithium ion battery nail penetration tests and quantitative evaluation of the degree of combustion risk. Journal of Power Sources 2019, 416, 132 -140.
AMA StyleTakumi Yamanaka, Yoichi Takagishi, Yasufumi Tozuka, Tatsuya Yamaue. Modeling lithium ion battery nail penetration tests and quantitative evaluation of the degree of combustion risk. Journal of Power Sources. 2019; 416 ():132-140.
Chicago/Turabian StyleTakumi Yamanaka; Yoichi Takagishi; Yasufumi Tozuka; Tatsuya Yamaue. 2019. "Modeling lithium ion battery nail penetration tests and quantitative evaluation of the degree of combustion risk." Journal of Power Sources 416, no. : 132-140.