Emergency Battery Discharge under Safety Constraints using Optimization-based Controllers

This paper presents an algorithm that defines the maximum discharge rate that could be allowed safely, while addressing the enforcement of temperature, state of charge (SoC), and pressure constraints. The algorithm leverages polynomial approximations of battery models to formulate two types of safety controllers. The first utilizes a model predictive control (MPC) framework to systematically enforce multiple constraints while optimizing performance. The second is based on control barrier functions (CBFs), which transform safety requirements into low-dimensional optimization problems. Simulation analysis demonstrates the effectiveness of both approaches. Compared to MPC, the CBF approach achieves 28-70% reduction in average computational time, while providing similar safety guarantees.