Lithium-ion Battery State of Health Estimation Using Support Vector Regression(SVR)

Thanks to recent advancements in lithium-ion (Li-ion) storage technology, the automotive industry is transforming. Fully electric vehicles (EVs) function under the widest range of driving and environmental circumstances and range of autonomy. To put it another way, an equal State of Charge (SOC) on two identical model EVs does not necessarily translate to the same distance traveled, as factors such as the battery's State of Health (SOH), the type of driver and even the route will affect how well the EVs operate. State of health (SOH) is the proportion of the battery's rated capacity to its maximal capacity as of the moment. It is a crucial index for describing the state of degradation in a battery for a pure electric vehicle and serves as a crucial benchmark for determining the retired battery's state of health and calculating the driving range. Estimating the state of health (SOH) of lithium-ion batteries is crucial for their safe and lifetime-optimized functioning, hence this is done using support vector regression. This paper presents Python code to implement this project.