Ravi N. Methekar

Optimal Porosity Distribution for Minimized Ohmic Drop across a Porous Electrode

This paper considers the design of spatially varying porosity profiles in next-generation electrodes based on simultaneous optimization of a porous-electrode model. Model-based optimal design not including the solid-phase intercalation mechanism is applied to a porous positive electrode made of lithium cobalt oxide, which is commonly used in lithium-ion batteries for various applications. For a fixed amount of active material, optimal grading of the porosity across the electrode was found to decrease the ohmic resistance by 15%‐33%, which in turn increases the electrode capacity to hold and deliver energy. The optimal porosity grading was predicted to have 40% lower variation in the ohmic resistance to variations in model parameters due to manufacturing imprecision or capacity fade. The results suggest that the potential for the simultaneous model-based design of electrode material properties that employ more detailed physics-based first-principles electrochemical engineering models to determine optimal design values for manufacture and experimental evaluation.

Optimum Charging Profile for Lithium-Ion Batteries to Maximize Energy Storage and Utilization

The optimal profile of charging current for a lithium-ion battery is estimated using dynamic optimization implemented via control vector parameterization (CVP). An efficient reformulated model is used for simulating the system behavior of the Li-ion battery. Dynamic optimization is made possible due to the computationally inexpensive reformulated model. It is found that, if the battery is charged using the optimum profile estimated by dynamic optimization, more energy can be stored as compared with conventional charging of the battery. An attempt has been made to understand the dynamics of Li-ion batteries with competing transport and reaction phenomena at various scales and location inside the battery.

A perturbation approach for consistent initialization of index-1 explicit differential–algebraic equations arising from battery model simulations

a b s t r a c t Estimation of consistent initial conditions is very crucial for the successful solution of differential–algebraic equation (DAE) systems that arise in many fields of science and engineering. In this paper, an efficient perturbation approach for initialization of DAE systems of index-1 is proposed and implemented for DAE models governing batteries. In addition, different existing solvers are compared for consistent initialization of DAE systems. The proposed approach does not necessarily require a nonlinear solver for initialization and builds on the applicability and usability of robust and efficient explicit, linearly implicit and semi-implicit integrators in time. Three different problems are presented wherein the proposed approach is observed to work for a wider range of inconsistent initial conditions compared to other existing generally used routines. It is also observed that the present approach is computationally efficient compared to the other existing approaches in a given environment.

Optimal spatial distribution of microstructure in porous electrodes for Li-ion batteries

This paper applies simultaneous optimization to the design of spatially-varying porosity profiles in next-generation electrodes to maximize the capacity of Li-ion batteries, based on porous electrode theory. This paper designs a porous positive electrode made of lithium cobalt oxide, which is commonly used in lithium-ion batteries for various applications. For a fixed amount of active material, optimal grading of the porosity across the electrode decreases the Ohmic resistance by 25%, which in turn increases the electrode capacity to hold and deliver energy. Over 40% enhancement was observed in the robustness of the optimal electrode designs to variations in model parameters due to manufacturing imprecision. The results are sufficiently promising to justify investment in the development of experimental procedures to fabricate batteries that have a graded porosity across the electrode.

Kinetic Monte Carlo simulation of surface heterogeneity in graphite anodes for lithium-ion batteries: Passive layer formation

The properties and chemical composition of the solid-electrolyte-interface (SEI) layer have been a subject of intense research due to their importance in the safety, capacity fade, and cycle life of Li-ion secondary batteries. Kinetic Monte Carlo (KMC) simulation is applied to explore the formation of the passive SEI layer in the tangential direction of the lithium- ion intercalation in a graphite anode. The simulations are found to consistent with observations in the literature that the active surface coverage decreases with time slowly in the initial stages of the battery operation, and then decreases rapidly. The effects of operating parameters such as the exchange current density and temperature on the formation of the passive SEI layer are investigated. The active surface coverage at the end of each charging cycle was initially lower at higher temperature, but remained constant for more cycles. The temperature that optimizes the active surface in a lithium-ion battery at Cycle 1 can result in less active surface area for most of the battery life.

Estimation of Optimum Operating Profile for PEMFC

In this paper, we present a methodology to estimate the optimum operating condition for increasing the available power density from the Proton Exchange Membrane Fuel cell (PEMFC). This is achieved by implementing an optimization procedure on a mathematical model of the PEMFC. As a first step, the input condition in steady state is optimized and dynamic optimization is implemented on the transient model. It was observed that the firstprinciples model requires large computational time and hence we propose to reformulate the model to increase the computational efficiency and then use the same for dynamic optimization.