Study relating cycle operating variables and design variables of a lithium-ion cell through multi-objective optimization

AIMO C.E.; SCHMIDHALTER I.; AGUIRRE P.A.

Buenos Aires

Congreso; WCCE11 - 11th WORLD CONGRESS OF CHEMICAL ENGINEERING; 2023

Asociación Argentina de Ingenieros Químicos

The influence of lithium-ion cell design variables and their relationship to cyclic operating conditions are analyzed through multi-objective optimization. Design and operating variables are simultaneously optimized. The Pareto optimal solutions obtained for different cycle operating conditions are analyzed, specifically, the simple charge-discharge cycle at a constant current (CC) is compared with the simple charge-discharge cycle at constant power (CP) and constant resistance (CR), respectively. The considered design variables are electrode thicknesses, solid volume fractions and cell mass per unit cross-sectional area. Optimal cell designs are obtained for two types of cell chemistries: lithium manganese oxide (LMO) and lithium cobalt oxide (LCO). Regarding the operational variables, the current and the initial state of charge of the charging and discharging processes are optimized. The initial state of charge of the cell corresponds to a set of variables that will be determined in each optimization problem (OP) as solutions, since, no initial state of charge is defined as it is usual in the literature for optimization problems related to simple charging or discharging processes. Instead, in the cyclic process optimization problems solved in this work, it corresponds to a set of constraints that define the equality between the initial and the final state of charge. Maximization of capacity, maximization of specific energy in the discharge and maximization of cycle energy efficiency are the objective functions involved.A phenomenological mathematical model developed in GAMS (General Algebraic Modeling System) environment is applied to achieve the stated goals and the multi-objective problems are solved using an epsilon constraint method-based, which is effective for finding solutions in non-convex feasible regions.A Pareto surface of 529 solutions is obtained corresponding to optimal LMO cell designs operating on a simple cycle of CR discharge and CP charge cycle. These designs have on average 9% more capacity when compared to those optimal designs obtained in [1], which correspond to cells (of same chemistry) operating in a constant current cycle. While the differences in specific energy and cycle energy efficiency are negligible. A smaller number of solutions is obtained for LCO cell chemistry, specifically 26 optimal designs that are Pareto efficient solutions and exhibit negligible differences in the objective functions when compared to solutions operating in a CC cycle.On one hand, results show that material type-dependent variables such as active solids have a strong influence on the specific energy and cycle energy efficiency. While the electrode thicknesses show a general trend regardless of the type of chemistry, presenting a strong influence on cell capacity values. On the other hand, this trend of the design variables is the same, regardless of the operating condition imposed.