The curb weight of electric trucks is more than 10% higher than that of conventional internal combustion engine trucks due to the motor and battery. For this reason, cargo box developed for small electric trucks is required weight reduction, and cargo door that can reduce weight and maintain strength are being developed. In this paper, we designed the lightweight cargo door, confirmed the stability of the door through structural analysis, and developed a cargo box door that was more than 25% lighter by applying composite materials such as Sheet Molding Compound(SMC) and Fiber Reinforced Plastic(FRP).

Electric doors have been applied in urban trains since 2007 and operated for a long time. Recently, the failure of mechanical devices in electric doors have been increasing. The door is a device that is directly related to the safety of passengers. The rivet breakage of a ball/nut assembly may occur to an accident during train operation. In this study, the operating voltage and acceleration data of the door were collected for rivet condition monitoring, and 4 features were extracted in the frequency domain using the acceleration data. The classification performance of the rivet condition according to the axial direction of the acceleration data and 4 kernel functions was evaluated using SVM algorithm. When the X-axis data and Gaussian kernel function were used, the highest classification performance was shown for the electric door’s rivet with 90% accuracy.