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UGV (Unmanned Ground Vehicle) is gaining increasing amounts of attention from both industry and academic communities in recent years. Local trajectory planning is one of the most important parts of designing a UGV. However, there has been little research into local trajectory planning and tracking, and current research has not considered the dynamic of the surrounding environment. Therefore, we propose a dynamic local trajectory planning and tracking method for UGV driving on the highway in this paper. The method proposed in this paper can make the UGV travel from the navigation starting point to the navigation end point without collision on both straight and curve road. The key technology for this method is trajectory planning, trajectory tracking and trajectory update signal generation. Trajectory planning algorithm calculates a reference trajectory satisfying the demands of safety, comfort and traffic efficiency.

Significant progress in modeling techniques has greatly enhanced the application of computer simulations in vehicle safety. However, the fine-meshed impact models are usually complex and take lots of computational resources and time to conduct design optimization. Hence, to develop effective methods to simplify the impact models without losing necessary accuracy is of significant meaning in vehicle crashworthiness analysis. Surface deformation is frequently regarded as a critical factor to be measured for validating the accuracy of CAE models. This paper proposes an integrated validation framework to evaluate the inconsistencies between the deformed surfaces of the original model and simplified model. The geometric features and curvature information of the deformed surfaces are firstly obtained from crash simulation. Then, the magnitude and shape discrepancy information are integrated into the validation framework as the surface comparison objects.

The control strategy of switched reluctance motor (SRM) in-wheel motor is investigated in order to reduce the influence of torque ripple of SRM on the ride comfort. The nonlinear model of switched reluctance motor (SRM) is established and the variable angle control strategy with optimal switch angles is applied to control SRM. However, the variable angle control strategy can not reduce the torque ripple of SRM significantly. Therefore, some advanced control strategies are developed to improve the ride comfort in electric vehicle. In this paper, the fuzzy proportional integration differential (PID) is developed to improve the torque ripple of SRM in which the fuzzy control idea is utilized to adjust the parameters of proportional integration differential (PID) control online and ensure the adaptive capabilities of the fuzzy proportional integration differential (PID) control to motor driving system.