"Full factorial design of experiments dataset for parallel-connected lithium-ion cells imbalanced performance investigation".

This paper shares an experimental dataset of lithium-ion battery parallel-connected modules. The campaign, conducted at the Stanford Energy Control Laboratory, employs a comprehensive full factorial Design of Experiment methodology on ladder-configured parallel strings. A total of 54 test conditions were investigated under various operating temperatures, cell-to-cell interconnection resistance, cell chemistry, and aging levels. The module-level testing procedure involved Constant Current Constant Voltage (CC-CV) charging and Constant Current (CC) discharge. Beyond monitoring total module current and voltage, Hall sensors and thermocouples were employed to measure the signals from each individual cell to quantify both current and temperature distribution within each tested module configuration. Additionally, the dataset contains cell characterization data for every cell (i.e. NCA Samsung INR21700-50E and NMC LG-Chem INR21700-M50T) used in the module-level experiments. This dataset provides valuable resources for developing battery physics-based, empirical, and data-driven models at single cell and module level. Ultimately, it contributes to advance our understanding of how cell-to-cell heterogeneity propagates within the module and how that affects the overall system performance.

Data of physical and electrochemical characteristics of calendered NMC622 electrodes and lithium-ion cells at pilot-plant battery manufacturing.

The data reported here was prepared to study the effects of calendering process on NMC622 cathodes using a 3-3-2 full factorial design of experiments. The data set consists of 18 unique combinations of calender roll temperature (85 °C, 120 °C, or 145 °C), electrode porosity (30%, 35%, or 40%), and electrode mass loading (120 g/m² or 180 g/m²). The reported physical characteristics of the electrodes include thickness, coating weight, maximum tensile strength, and density. The electrochemical performances of the electrodes were obtained by testing coin cells. In this context, 54 half-cells were produced, 3 per each calendering experiment to ensure repeatability and reliability of the results. The responses of interest included, charge energy capacity at C/2, C/5, discharge energy capacity at C/20, C/5, C/2, C, 2C, 5C, 10C, gravimetric capacity (charge at C/2, C/5, discharge at C/20, C/5, C/2, C, 2C, 5C, 10C), volumetric capacity (charge at C/2, C/5, discharge at C/20, C/5, C/2, C, 2C, 5C, 10C), rate performance (5C:0.2C), area specific impedance (at 10% to 90% state of charge (SoC) in 10 breakpoints), long-term cycling capacity (charge at C/5 for 50 cycles, discharge at C/2 for 50 cycles), long-term cycling degradation (at C/2 during 50 cycles of charge and discharge), and cycling columbic efficiency (50 cycles of C/2 charge and discharge). The details of the experimental design that has led to this data as well as comprehensive statistical analysis, and machine learning-based models can be found in the recently published manuscripts by Hidalgo et al. and Faraji-Niri et al. [1,2].

Dataset for rapid state of health estimation of lithium batteries using EIS and machine learning: Training and validation.

This article addresses the objective, experimental design and methodology of the tests conducted for battery State of Health (SOH) estimation using an accelerated test method. For this purpose, 25 unused cylindrical cells were aged, by continual electrical cycling using a 0.5C charge and 1C discharge to 5 different SOH breakpoints (80, 85, 90, 95 and 100%). Ageing of the cells to the different SOH values was undertaken at a temperature of 25 °C. A reference performance test (RPT) of C/3 charge-discharge at 25 °C was performed when the cells were new and at each stage of cycling to define the energy capacity reduction due to increased charge-throughput. An electrochemical impedance spectroscopy (EIS) test was performed at 5, 20, 50, 70 and 95% states of charge (SOC) for each cell at temperatures of 15, 25 and 35 °C. The shared data includes the raw data files for the reference test and the measured energy capacity and the measured SOH for each cell. It contains the 360 EIS data files and a file which tabulates the key features of the EIS plot for each test case. The reported data has been used to train a machine-learning model for the rapid estimation of battery SOH discussed in the manuscript co-submitted (MF Niri et al., 2022). The reported data can be used for the creation and validation of battery performance and ageing models to underpin different application studies and the design of control algorithms to be employed in battery management systems (BMS).

Experimental data of cathodes manufactured in a convective dryer at the pilot-plant scale, and charge and discharge capacities of half-coin lithium-ion cells.

Megtec Systems pilot-plant scale continuous convective coater. The data was generated as part of an experimental design involving the following coating-drying process variables and ranges: comma bar gap, 80-140 µm; web speed, 0.5-1.5 m/min; coating ratio, 110-150%; drying temperature, 85-110 °C and drying air speed, 5-15 m/s. The manufacturing data include pre-calendered coating thickness, mass loading dry and wet, pre-calendered porosity, spatial autocorrelation and join counting (SAJC) Z-score for carbon and for fluorine, cell thickness, coating weight and porosity of 15 different electrode coatings and 45 half-coin cells. The electrochemical data was obtained at 25 °C in a Maccor 4000 series battery cycler and consists of charge and discharge capacities at C/20, C/5, C/2, 1C, 2C, 5C and 10C C-rates. Discharge gravimetric and volumetric capacities, rate performance (at 5C:0.2C) and first cycle loss data is also reported. Details of the experimental design and a comprehensive analysis of the data can be found in the co-submitted manuscript (Román-Ramírez et al., 2021). Additional collected data not used in Román-Ramírez et al. (2021) is reported in the present manuscript and include visual observations of coating defects, rheological properties of the electrode slurries (solid content, viscosity, coating shear rate and viscosity at coating shear rate), room temperature and room humidity during the coatings and first cycle loss of the coin cells. Raw and analyzed data is made available. The reported data can be used to extend the analysis reported in Román-Ramírez et al. (2021), and for the comparison of relevant data obtained at different manufacturing scales.

Stochastic stability and stabilization of Markov jump linear systems with instantly time-varying transition rates: A unified framework.

This paper investigates the stochastic stability and stabilization problems of non-homogeneous Markov jump linear systems (NHMJLSs) characterized by instantly unconditionally time-varying transition rates (TRs). The novelty of the study lies in proposing a systematic method for achieving finite dimensional conditions with an acceptable degree of conservativeness for the stability and the stabilization problems of the system. In this framework, by first processing the time-varying TRs, a finite number of uncertain but time-constant TR matrices are obtained. Then, a high-level switching signal is constructed for the system, which models the contribution of each possible time-constant TR matrix. Based on the results, the NHMJLS is reformed into an uncertain switching structure referred to as the associated switched Markov jump linear system (AS-MJLS). Finally, by taking advantage of the new representation, sufficient conditions are obtained to ensure the stability and stabilizability of the system, also the controller gains are designed. The proposed framework provides a realistic representation as well as practically solvable analysis and synthesis conditions for the NHMJLS. It also leads to less conservative results compared with the existing well-known techniques. Comparative simulation studies for a single-machine infinite-bus (SMIB) power system subject to stochastically varying load demonstrate the efficiency and superiority of the method.