Battery Management Systems (BMS) are critical to safe and efficient operation of lithium-ion batteries and accurate prediction of the internal states. Smarter BMS that can estimate and implement optimal charging profiles in real-time are important for advancement of the Li-ion battery technology. Estimating optimal profiles using physics-based models is computationally expensive because of the non-linear and stiff nature of the model equations, involving the need for constrained nonlinear optimization. In this work, we present an alternative approach to control batteries called as Generic Model Control, or Reference System Synthesis. This work enables robust stabilization and control of battery models to set-point as an alternative approach, eliminating the need to perform optimization of nonlinear models. As compared to the generic model control approaches implemented by previous researchers, we implement the same concept using direct DAE numerical solvers. The results are presented for single input single objective problems, and for constrained problems for various battery models. (C) The Author(s) 2017. Published by ECS. All rights reserved.