Method and system for identifying electrolyte composition for optimal battery performance

A system comprising:

• a memory storing instructions;
• one or more Input/Output (I/O) interfaces;
• and
• one or more hardware processors coupled to the memory via the one or more communication interfaces, wherein the one or more hardware processors are configured by the instructions to:
• receiving (i) one or more initial material parameters, (ii) one or more physics-based model parameters, (iii) one or more optimization parameters, and (iv) one or more lower length scale model parameters;
• estimating a plurality of transport properties based on the one or more initial material parameters;
• determining a mapping between a plurality of electrolyte compositions in a material database and associated plurality of transport properties using a lower length scale model based on the one or more lower length scale model parameters;
• computing a deviation index (DI) for each of the plurality of electrolyte compositions based on the associated plurality of transport properties and the estimated plurality of transport properties;
• selecting an electrolyte composition with minimum DI among the plurality of electrolyte compositions;
• evaluating internal heat generation (Q) and capacity fade (C) of the selected electrolyte composition using a physics-based model based on the estimated plurality of transport properties and the one or more physics-based model parameters;
• and
• optimizing an objective function based on the one or more optimization parameters to obtain revised material parameters, wherein the objective function comprises weighted sum of Q, C, and minimum DI.

One or more non-transitory machine-readable information storage mediums comprising one or more instructions which when executed by one or more hardware processors cause:

• receiving (i) one or more initial material parameters, (ii) one or more physics-based model parameters, (iii) one or more optimization parameters, and (iv) one or more lower length scale model parameters;
• estimating a plurality of transport properties based on the one or more initial material parameters;
• determining a mapping between a plurality of electrolyte compositions in a material database and associated plurality of transport properties using a lower length scale model based on the one or more lower length scale model parameters;
• computing a deviation index (DI) for each of the plurality of electrolyte compositions based on the associated plurality of transport properties and the estimated plurality of transport properties;
• selecting an electrolyte composition with minimum DI among the plurality of electrolyte compositions;
• evaluating internal heat generation (Q) and capacity fade (C) of the selected electrolyte composition using a physics-based model based on the estimated plurality of transport properties and the one or more physics-based model parameters;
• and
• optimizing an objective function based on the one or more optimization parameters to obtain revised material parameters, wherein the objective function comprises a weighted sum of Q, C, and minimum DI.