Energy storage is one of humanity’s greatest technological challenges. As society’s size and energy appetite grow, we must seek solutions that facilitate penetration of renewable energy and enhance efficiency, particularly in the transportation and power system infrastructures. This seminar focuses on modeling, estimation, and control challenges in two emerging energy applications: batteries and demand response. Today, existing battery technologies are expensive, overdesigned, and conservatively operated. We seek to combine electrochemical models and novel control theories to expand the performance limits of existing battery technologies. In the second half, we discuss demand responsive flexible loads in the smart grid. Aggregations of large-scale distributions of flexible loads can be elegantly modeled by coupled partial differential equations (PDEs). This modeling framework enables one to perform analysis, estimation, and control design using recently developed techniques for PDE systems. The talk concludes with an overview of open questions and future research plans in the Energy, Controls and Applications Laboratory (eCAL).