Batteries are one of the important energy storage sources for a changing world. Applications of battery use as an energy supply and storage device have been extended from small portable electronic devices to big transportation vehicles. Modeling and simulation of lithium ion batteries have been carried out across various disciplines to investigate different aspects of such batteries, from electrochemical performance to design optimization simulations. Electrochemical based energy storage devices, such as Li-ion battery, are one of the physical systems which are representing multiscale phenomena. In order to get a more realistic model, the effect of microscale phenomena of a battery system should be accounted for in the total response of the system. Multiscale modeling methods have been proposed for the analysis of systems representing multiscale phenomena. The missing part in the simulation of battery systems is to correlate ongoing phenomena across their different spatial scales, which is necessary to be accounted for the goal of having a more realistic model. Several methods of multiscale modeling have been proposed and employed previously. Examples include homogenization, multiscale residential segregation, variational multiscale modeling (VMM) and recently, variational multiscale enrichment. This study intends to employ VMM for the analysis of a Li-ion battery. The main advantage of VMM is that this method is computationally less expensive compared with the conventional methods. The main idea of implementing VMM is to decompose the response fields linearly into macro- and microscale components. VMM evaluates the microscale response semi-analytically through variational projection. With the determined microscale response, the VMM resolves the heterogeneity of the microstructure of the battery and obtains more accurate results. Validation of the model will be obtained against experimental and numerical results of Li-ion battery studies that are ongoing in our group.