Understanding the magnitude and profile of forces and torques (F/T) to properly execute the plugging and unplugging for electric vehicles (EVs) charging is crucial for designing reliable robots in automated charging stations (ACS). Previous research focuses on F/T measurement for controlling force during robotic tasks. In contrast, this study aims to refine automation workflows for smoother operation. By utilizing the comprehensive F/T measurements, it becomes possible to extract precise information during the plugging and unplugging process. This data provides insight into interaction dynamics, improving the robot’s ability to perform tasks more accurately and efficiently. Through experiments involving 40 participants, anthropometric and F/T data were analysed using statistics, uncovering key relationships between height, weight, and forces. The F/T profiles were predicted using polynomial, Fourier series, and Gaussian models, with the Gaussian proving the most accurate. Peak force and impulse are significantly higher during plugging (74.15 Ns) than unplugging(57.92Ns).