A Comparative Analysis of Techniques for Electric Vehicle Battery Prognostics and Health Management (PHM)
Batteries are widely used as storage devices and they have recently gained popularity due to their increasing smaller sizes, lighter weights and greater energy densities. These characteristics also render them suitable for powering electric vehicles. However, a key gap exists in that batteries are solely used as storage devices with a lack of information flow. Next-generation battery technologies will constitute the enabling tools that would lead to information-rich batteries, thus allowing the transparent assessment of a battery's health as well as the prediction of a battery's remaining-useful-life (RUL) and its subsequent impact on vehicle mobility. Various methods and techniques have been employed to predict battery RUL in order to improve the accuracy of the State of Charge (SoC) estimation.