A High-Efficiency Bidirectional Active Balance for Electric Vehicle Battery Packs Based on Model Predictive Control

• Published in: Energies (Basel) Vol. 11; no. 11; p. 3220
• Main Authors: Song, Shixin, Xiao, Feng, Peng, Silun, Song, Chuanxue, Shao, Yulong
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.11.2018
• Subjects: active balance; Algorithms; Automobile industry; battery packs; Business administration; Constraint modelling; Cost function; Efficiency; electric vehicle; Electric vehicles; Energy; Energy consumption; Heat; Industrial production; Lithium; model predictive control; Optimal control; Power management; United States > US; China
• ISSN: 1996-1073; 1996-1073
• DOI: 10.3390/en11113220

This study designs an active equilibrium control strategy based on model predictive control (MPC) for series battery packs. To shorten equalisation time and reduce unnecessary energy consumption, bidirectional active equalisation is modelled and analysed, and the model predictive control algorithm is then applied to the established state space equation. The optimisation problem that minimises the equilibrium time is transformed to a linear programming form in each cycle. By solving the linear programming problem online, a group of control optimal solutions is found and the series equalisation problem is decoupled. The equalisation time is shortened by dynamically adjusting the equalisation current. Simulation results show that the MPC algorithm can avoid unnecessary energy transfer and shorten equalisation time. The bench experimental result shows that the equilibrium time is reduced by 31%, verifying the rationality of the MPC strategy.