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Due to the multi-gear configuration and high integration of electric drive systems in electric vehicles, it is necessary to investigate the influence of drive motor torque fluctuation on the dynamic characteristics and load sharing performance of planetary gear transmission systems. Considering both motor torque fluctuation and internal excitations of the transmission system, a dynamic model of the electromechanical coupled system is established by combining the Maxwell motor electromagnetic model with the planetary gear dynamics model. Based on the proposed model, the dynamic characteristics, dynamic load performance and load sharing performance of the system considering motor torque fluctuation are analyzed, and the improvement of system load sharing performance due to sun gear floating is discussed. The results show that motor torque fluctuation leads to more complex dynamic response and causes the vibration displacement amplitude to more than doubled.

A flat neural network is designed for the on-line state prediction of engine. To reduce the computational cost of weight matrix, a fast recursive algorithm is derived according to the pseudoinverse formula of a partition matrix. Furthermore, the forgetting factor approach is introduced to improve predictive accuracy and robustness of the model. The experiment results indicate that the improved neural network is of good accuracy and strong robustness in prediction, and can apply for the on-line prediction of nonlinear multi input multi output systems like vehicle engines.

In this paper, an investigation is made to the friction clutch engagement control of automotive AMT systems based on a nonlinear dynamic model with double inputs. According to friction torque transmission characteristics during clutch engagement, an equivalent, fully controllable and linearized model and the feedback linearization control are derived from the original system with nonlinearities via homomorphic transforms. By the resulting mathematical modeling, computer simulations are made both for the original nonlinear and feedback linearized systems with incorporation of ordinary PID controllers to follow ideal vehicle dynamic responses. It has been shown by comparison between the two sets of numerical results that the feedback linearization control designed for the nonlinear system is of fine accuracy and robustness in model tracking behaviors of clutch engagements.