The collision of a vehicle is often a process of strong nonlinearity and large deformation, and the finite element method is time-consuming. For this reason, a method of collision inversion research is proposed. Through the definition of the forward and inverse problems, the forward problem is inversely solved from the perspective of the inverse problem, and the collision process can be predicted quickly while the accuracy is ensured. In this paper, the idea of inversion is introduced into the collision test of the front bumper of the vehicle. First, a finite element model is established based on the geometric model of the bumper. The accuracy of the finite element model is verified by comparing the results of the drop weight test with the simulation results of the finite element model. Then, using the built simulation model, spring mass model and drop weight test, the inversion research of vehicle collision and the front bumper of a vehicle is carried out. The inversion research of the bumper first inverts the collision course in the inversion algorithm derived from the vehicle collision, and then compares the collision course derived from the inversion algorithm formula with the simulation test results. The research results show that the change trends of the time-velocity curve and the time-deformation curve obtained by the collision inversion algorithm are basically consistent with the simulation test results, indicating that the collision inversion algorithm can realize the rapid prediction of the collision course and improve derivation efficiency significantly, and it provides a new idea. Finally, under the constant energy condition of the drop weight test E = mgh, through the relationship between energy and deformation, it is concluded that the depth deformation of low-speed collision of the front bumper is greater than that of high-speed collision.
Citation: Miao Luo, Yousong Chen, Dawei Gao, Lijun Wang. Inversion study of vehicle frontal collision and front bumper collision[J]. Electronic Research Archive, 2023, 31(2): 776-792. doi: 10.3934/era.2023039
The collision of a vehicle is often a process of strong nonlinearity and large deformation, and the finite element method is time-consuming. For this reason, a method of collision inversion research is proposed. Through the definition of the forward and inverse problems, the forward problem is inversely solved from the perspective of the inverse problem, and the collision process can be predicted quickly while the accuracy is ensured. In this paper, the idea of inversion is introduced into the collision test of the front bumper of the vehicle. First, a finite element model is established based on the geometric model of the bumper. The accuracy of the finite element model is verified by comparing the results of the drop weight test with the simulation results of the finite element model. Then, using the built simulation model, spring mass model and drop weight test, the inversion research of vehicle collision and the front bumper of a vehicle is carried out. The inversion research of the bumper first inverts the collision course in the inversion algorithm derived from the vehicle collision, and then compares the collision course derived from the inversion algorithm formula with the simulation test results. The research results show that the change trends of the time-velocity curve and the time-deformation curve obtained by the collision inversion algorithm are basically consistent with the simulation test results, indicating that the collision inversion algorithm can realize the rapid prediction of the collision course and improve derivation efficiency significantly, and it provides a new idea. Finally, under the constant energy condition of the drop weight test E = mgh, through the relationship between energy and deformation, it is concluded that the depth deformation of low-speed collision of the front bumper is greater than that of high-speed collision.
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Miao Luo, Yousong Chen, Dawei Gao, Lijun Wang. Inversion study of vehicle frontal collision and front bumper collision[J]. Electronic Research Archive, 2023, 31(2): 776-792. doi: 10.3934/era.2023039
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