FPGA-synthesizable Electrical Battery Cell Model for High Performance Real-time Algorithms

Abstract

Modern battery management systems (BMS) for advanced battery energy storages are expected to provide sufficient and reliable State-of-Charge (SoC) and State-of-Health (SoH) information. Focusing also on mid- and long-term maintenance purposes, health monitoring can be realized only by using high performance real-time estimation algorithms involving online electrical battery cell model. Due to the nonlinear I-V characteristics of cells and multivariable nonlinear functions describing the model parameters, a real-time model synthesized to FPGA seems to be the best solution to fulfill also the strongest requirements of energy management and e-mobility applications in respect of scalability, modularity, accuracy and effectiveness. In this paper, an FPGA-synthesizable battery cell model is presented and proposed. The design approach is discussed from offline to online model design including the model considerations using MATLAB/Simulink^®. The performance analysis and evaluation referenced to the offline model are presented and discussed.