抄録
Advanced traffic systems, for instance automatic platooning control, are required to solve environmental problems and traffic problems. The vehicles under the automatic platooning control can travel automatically with maintaining short distances between vehicles and following preceding vehicles. However, precise control is necessary to ensure driving safety because vehicles controlled by automatic platooning maintain short distances between vehicles. Accurate parameters are important to conduct high performance of automatic control because control system is affected by a change of vehicle parameters. Especially parameters of trucks are changed widely according to the loaded condition. Performance of the automatic platooning control is affected by changing of vehicle parameters. Therefore the accurate parameters is required in real-time. Among the vehicle parameters, the yaw moment of inertia is an important parameter for the vehicle steering control, cornering or lane change. A method is proposed using Dual Kalman filter algorithm, which estimates state of vehicle and parameters of vehicle simultaneously, to identify the yaw moment of inertia of vehicle on travelling. Performance to estimate the yaw moment of inertia was evaluated through the experiment using the GPS sensor. The yaw moment of inertia was estimated by the proposed method. The results of the experiment show the proposed method is effective for the identification of the yaw moment of inertia. Validity of the proposed method is confirmed through the examination.
