A charge equalisation controller (CEC) was developed for continuously monitoring individual battery cells and equalising the charge or voltage levels of all cells in a series pack. A charge equalisation control algorithm was developed to equalise undercharged, overcharged, and unprotected cells through the use of a bidirectional fly-back converter. The equalisation involves charging and discharging by employing constant current–constant voltage and discontinuous current mode proportional–integral (PI) control techniques. Particle swarm optimisation is applied to optimising the PI controller parameters that generate the regulated pulse width modulation switching signal for the converter. A CEC model was applied to 90 lithium-ion battery cells (nominally 15.5 Ah and 3.7 V each) connected in series. The results showed that the developed CEC model performed well at equalising both undercharged and overcharged cells with ∼92% efficiency and equalised every cell within the safe operation range of 3.73–3.87 V. The developed system realises excellent equalisation speed, a simple design and efficiency with low power loss. Thus, the CEC model has great potential for implementation in real-world electric vehicle energy storage systems.
Optimal algorithms for the charge equalisation controller of series connected lithium-ion battery cells in electric vehicle applications
IET Electrical Systems in Transportation ; 7 , 4 ; 267-277
2017-09-06
11 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
secondary cells , proportional-integral control technique , real-world electric vehicle energy storage system , PI controller parameter optimisation , electric vehicle charging , charge equalisation controller , battery powered vehicles , optimal control , battery discharging , voltage 3.7 V to 3.87 V , CEC model , pulse width modulation switching signal , PI control , discontinuous current mode PI control techniques , lithium compounds , optimal algorithm , battery charging , series connected lithium-ion battery cells , bidirectional fly-back converter , electric vehicle applications , particle swarm optimisation
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