Research In Simulation Of Electric Vehicle’s Front Collision Based On LS-DYNA

With the country’s support of industry of electric vehicle, the number of theelectric vehicle is gradually increasing. With the development of industry ofelectric vehicle, electric vehicles’ safety shows the importance. Because electricvehicles in the composition of power are different from the traditional fuel vehicle,passive safety problem of electric vehicle has its particularity, in addition to theneed to meet the safety standards of the traditional vehicle, electric vehicles’passive safety need to consider the safety of the battery.The article uses explicit dynamic analysis software LS-DYNA to simulateelectric vehicle front crash. The electric vehicle crashes into a rigid wall in thespeed of48km/h. Use the powerful finite element pre-processing softwareHYPERMESH to mesh geometry model. Spot-weld function and node coupledmethod can separately simulate the body welding and bolted connections betweenbattery and chassis in finite element modal. Set the appropriate time step size factorand local hourglass coefficient to control CPU time and hourglass deformation.Use post processor in ANSYS to view the deformation and displacement curve,velocity curve and acceleration curve. According to energy curve, observe thetransition between kinetic energy and inner energy as well as the control of thehourglass energy. Select the appropriate nodes to observe the deformation of thefront battery and door in order to determine whether the battery is safe and the doordeformation is within acceptable range. Improve the chassis structure according tosimulation results. Make frontal crash simulation to improved body, simulationresults show that the improved chassis structure can effectively improve thestiffness of the chassis in the cab, reduce the beam bending and control thedeformation of the door within an acceptable range. Finally, the topologyoptimization method on the chassis has been applied. Simulation results show thatthe crashworthiness of new modal is stronger than that of the original model andthe previous improved modal.