A Regression-Based Technique for Capacity Estimation of Lithium-Ion Batteries

Electric vehicles (EVs) and hybrid (HEVs) are being increasingly utilized for various reasons. The main reasons their implementation that they consume less or do not fossil fuel (no carbon dioxide pollution) cause sound pollution. However, this technology has some challenges, including complex troublesome accurate state of health estimation, which is affected by different factors. According to the increase in electric vehicles’ application, it crucial have a more reliable estimation charge (SOC) (SOH) environmental conditions. This allows improving battery management system operation optimal utilization pack operating article proposes an approach estimate capacity based on two parameters. First, practical straightforward method introduced assess battery’s internal resistance, directly related remaining useful life. Second, least square algorithm explored. Finally, promising, practical, simple, accurate, technique proposed appropriately. root mean percentage error absolute methods were calculated than 0.02%. It was concluded geometry all advantages recursive manner, fading memory, close form solution, applicable embedded systems.