The global automotive industry has experienced rapid development, leading to the widespread popularity and application of electric vehicles. The power battery is a crucial component of electric vehicles, and its cycle life has a direct impact on its performance. As the battery undergoes more life cycles, its health, as measured by the State of Health (SOH), will inevitably deteriorate to some extent. Therefore, accurately estimating the SOH of power batteries has become increasingly important. The SOH of power batteries has a direct impact on their energy storage capacity, operating stability, and service life. Hence, precise evaluation of the SOH of power batteries is crucial for extending battery life, optimizing battery system management, and enabling intelligent maintenance. This paper aims to explore the concept, methodology, and practical implementation of evaluating and estimating the SOH of power batteries. The study is grounded on actual operational data obtained from pure electric vehicles. The charging capacity data of small fragments are extracted using the ampere-hour integral method, and the least squares method is utilized to estimate the SOH of power batteries. The developed estimation model enables prompt identification of the SOH of power batteries.