Accurate measurement of the state of charge (SOC) in lithium-ion batteries is crucial for battery management systems in electric vehicles and fair transactions at battery swapping stations. However, battery aging leads to nonlinear variations in capacity and internal resistance, posing challenges for precise SOC estimation. To address this issue, this paper proposes a high-precision measurement method based on aging trajectory transfer and hardware-in-the-loop (HIL) simulation. Firstly, a two-stage aging trajectory transfer prediction model is established, utilizing aging data from standard batteries to predict the capacity degradation trajectory of the target battery. Factors such as temperature and current are incorporated to enhance prediction accuracy. Subsequently, the predicted aging trajectory is introduced into a PHIL simulation platform to update battery model parameters in real-time, simulating the charging and discharging characteristics of the battery under different aging states. Experimental results demonstrate that this method can effectively predict battery aging trajectories and achieve high-precision SOC measurement. The model accurately quantifies the capacity degradation from 734.63 mAh to 558.24 mAh, a decrease of 24.01%, along with the decline rate of open-circuit voltage and charging time, contributing to high-precision measurement and fair transactions for lithium-ion batteries.