Fitting the OCV-SOC relationship of a battery lithium-ion using genetic algorithm method

In response to the need of reducing fossil fuel dependence and environmental impacts for ground transportation, electric vehicles (EVs) powered by lithium-ion batteries (LIBs) are being intensively researched they have placed on forefront as alternative vehicles. The state charge (SOC) is one most important states LIBs that monitored online. However, model-based method estimation requires an accurate Open circuit voltage (OCV), which characteristic parameter batteries, used estimate battery (SOC). Therefore, OCV modeling a great significance management. polynomial model uses function establish relationship between SOC mapping. this paper,8th degree fitting curve considered genetic algorithm optimization proposed estimating parameters. results show root mean square error can be decreased 0.002. best OCV-SOC increase accuracy improve estimation.