Fundamental Techniques for Optimal Control of Reconfigurable Battery Systems: System Modeling and Feasible Search Space Construction

TL;DR

This paper introduces a unified modeling framework and feasible search space construction techniques for optimal control of reconfigurable battery systems, addressing nonlinearities and high dimensionality to improve efficiency and safety.

Contribution

It presents a novel unified modeling approach and a method to narrow the search space for feasible solutions in RBS optimal control problems.

Findings

Demonstrated effectiveness through simulation tests

Validated techniques with experimental tests

Reduced search efforts while ensuring safe configurations

Abstract

Reconfigurable battery systems (RBSs) are emerging as a promising solution to improving fault tolerance, charge and thermal balance, energy delivery, etc. To optimize these performance metrics of RBSs, high-dimensional nonlinear integer programming problems need to be formulated and solved. To accomplish this, it is necessary to address several critical challenges stemming from nonlinear battery characteristics, discrete switch states, dynamic system configurations, as well as the curse of dimensionality inherent in large-scale RBSs. Thus, we propose a unified modeling framework to accommodate various possible configurations of an RBS and even to cover different RBS designs and their hybrid combinations, enabling the problem formulation for the RBS optimal control and facilitating the RBS topology design.Further, to solve the formulated RBS optimal control problems, the search space is narrowed to encompass only the feasible solutions, thereby ensuring safe battery connections while substantially curtailing search efforts. These proposed techniques, focusing on unifying the system modeling and narrowing the search space, lay a solid foundation for effectively formulating and efficiently solving RBS optimal control problems. The accuracy and effectiveness of the proposed techniques are demonstrated by both simulation and experimental tests.