Title :
Nonlinear model predictive control for cell balancing in Li-ion battery packs
Author :
Samadi, M. Foad ; Saif, Mehrdad
Author_Institution :
Sch. of Eng. Sci., Simon Fraser Univ., Burnaby, BC, Canada
Abstract :
A major issue with Li-ion batteries hindering their widespread application in transportation industry is safety related concerns that should be effectively addressed within the battery management system design. Over-charge/discharge of the cells within a battery pack is one undesirable outcome that can affect the battery´s health. Differences between the cells within a battery pack can lead to cell over-charge/discharge that is not detectable from battery pack´s voltage. Thus, a cell balancing circuit is usually employed in battery packs in order to keep all the cells in balance. The control of cell-balancing circuits is mostly addressed by logical-based algorithms where the dynamical model of the system is not taken into account. This work considers the control problem of a cell-balancing circuit in a model-based framework by proposing a nonlinear model predictive control (NMPC). The NMPC problem is solved using a genetic algorithm and simulation studies show the effectiveness of the proposed algorithm.
Keywords :
battery management systems; genetic algorithms; predictive control; secondary cells; Li; Li-ion battery packs; NMPC; battery health; battery management system; battery pack voltage; cell balancing circuit; dynamical model; genetic algorithm; logical-based algorithms; nonlinear model predictive control; over-charge-discharge; transportation industry; Batteries; Discharges (electric); Genetic algorithms; Integrated circuit modeling; Mathematical model; Optimization; System-on-chip; Control applications; Switched systems;
Conference_Titel :
American Control Conference (ACC), 2014
Conference_Location :
Portland, OR
Print_ISBN :
978-1-4799-3272-6
DOI :
10.1109/ACC.2014.6859109