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Subramanian, Venkat

Publications and source records attributed to Subramanian, Venkat.

6 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Techniques for controlling charging and/or discharging of batteries using a tanks-in-series model

In some embodiments, a battery management system is provided. The battery management system comprises a connector for electrically coupling a battery to the battery management system, at least one sensor configured to detect a battery state, a programmable chip configured to control at least one of charging and discharging of the battery, and a controller device. The controller device is configured to receive at least one battery state from the at least one sensor; provide the at least one battery state as input to a tanks-in-series model that represents the battery; and provide at least one output of the tanks-in-series model to the programmable chip for controlling at least one of charging and discharging of the battery.

25 ENERGY STORAGE↗
DOE OSTI2023

Improving Volatile Fatty Acid Productivity of Anaerobic Digestion

Typical anaerobic digestion (AD) focusses on complete conversion of waste to biogas (primarily carbon dioxide and methane). However, the intermediate metabolites of the AD process, which includes short- and long-chain volatile fatty acids (VFAs), that could serve as the precursors for useful industrial applications are typically ignored. The goal of this project is to eliminate production of biogas while enhancing the production of the intermediate VFAs. Using a mixed microbial consortium (from rumen sources and waste-water sludge), we have determined the optimal carbon loading (chemical oxygen demand, "COD") and optimal pH, that results in high VFA concentrations from food waste. The best VFA yields were obtained using 15 g COD/L and a pH of 9.0 for this substrate. pH 9 produced over 200% higher VFA titers than the controlled conditions (i.e., ph 7.0) after 35 d of digestion, in comparison to pH 5 that showed - 88% higher titers than the control digestion. As expected, the cumulative biogas production was highest in the pH 7.0 condition, in comparison to pH 5.0 or pH 9.0. We further observed that removal of VFAs using solid-liquid separation technique reduce the inhibitory effects of VFAs, thereby leading to overall improvement in conversion efficiency. 16s rRNA analysis is being carried out to explain and identify the biocatalysts that enable VFA production in these AD cultures. Additional efforts to improve VFA yields via increasing the total solid content, temperature optimizations, VFA removal via electrodialysis, and improving hydrolysis via microaeration will be presented.

anaerobic digestion↗
DOE OSTI2022

Systems and methods for direct estimation of battery parameters using only charge/discharge curves

Electrochemical models for the lithium-ion battery are useful in predicting and controlling its performance. The values of the parameters in these models are vital to their accuracy. However, not all parameters can be measured precisely, especially when destructive methods are prohibited. In some embodiments of the present disclosure, a parameter estimation approach is used to estimate the open circuit potential of the positive electrode (Up) using piecewise linear approximation together with all the other parameters of a single particle model. Up and 10 more parameters may be estimated from a single discharge curve without knowledge of the electrode chemistry using a technique such as a genetic algorithm. Different case studies were presented for estimating Up with different types of parameters of the battery model. The estimated parameters were then validated by comparing simulations at different discharge rates with experimental data.

Qi, Yanbo↗
DOE OSTI2021

Lithium-ion battery physics and statistics-based state of health model

A pseudo-2d model using COMSOL Multiphysics® software is developed to simulate performance and performance degradation of Li-ion batteries consisting of layered and olivine cathodes with graphite anode when subjected to peak shaving grid service. Multiple degradation pathways are considered, including solid electrolyte interphase (SEI) formation and breakdown at the anode, cathode dissolution and its synergistic effect on SEI formation at the anode. The model is validated by simulating commercial cylindrical cell performance. A global model is developed to simulate performance across all chemistries, along with individual chemistry models using global model parameters as initial values. There is good agreement between these models for various optimization parameters such as SEI equilibrium potential, cathode dissolution exchange current density, solvent diffusivity in the SEI and SEI ionic conductivity. To circumvent time constraints related to the COMSOL model, a 0d global model is developed which fits data well and provides more clarity on differences in cathode dissolution exchange current density. Again, good agreement for various optimization parameters is obtained among the COMSOL global & individual chemistry models and the 0-d model. The lessons learned from the physics-based model is used to develop a top down statistics-based model using current, voltage and anode volumetric change per mole lithium intercalated, along with their interactions as degradation predictors. This model predicts out of sample degradation for multiple grid services and electric vehicle drive cycle with high accuracy and provides the pathway to develop an efficient battery management system combining machine learning and findings from physics-based computationally intensive algorithms.

Crawford, Aladsair J.↗
DOE OSTI2020

Battery models, systems, and methods using robust fail-safe iteration free approach for solving differential algebraic equations

Battery models using robust fail-safe iteration free approach for solving Differential Algebraic Equations, and associated systems and methods are disclosed. In one embodiment, a method includes generating a model of the rechargeable battery; determining one or more initial conditions for one or more algebraic variables of the model using a solver; holding differential variables of the model static by a switch function while determining the one or more initial conditions; applying the initial conditions to the model by the switch function; and determining one or more parameters for the rechargeable battery by solving the algebraic and differential equations.

25 ENERGY STORAGE↗