The objective of this paper is to study the multiobjective optimization problems for the optimal design of lithium-ion batteries. First, a two-objective problem is constructed with the performance measures of energy per unit separator area for the discharge rate of 0.5C and the mass per unit separator area. The reaction zone model and genetic algorithm are employed to solve this problem qualitatively. The resulted Pareto front comes out to be a concave curve in the 2D plane of the two performance measures. Three case studies are guided to illustrate the advantages and applications of employing the multiobjective optimization in the design process. A more sophisticated simulation model is then employed for a three-objective optimization problem with the objectives of energy performance at both low and high discharge rates and mass performance. The problem is quantitatively resolved with the assistance of the electrochemical model and genetic algorithm. The Pareto front comes out to be a curved surface in the 3D space of the three objectives. The properties of the Pareto front are discussed to offer new perspectives on product designs in the industry.