Lithium-ion batteries are the most common cells used to power electric vehicles. Short circuiting in these cells is a major field of research and development as it can be triggered and rapidly spread under certain abusive conditions. Many real-life experiments have been conducted at cell-level to study the loads vs deformation and voltage. This paper predicts the forces involved in a medium-speed full-frontal crash of an electric vehicle with a rigid barrier and the kinematics of the battery pack (BP) during the impact. A heterogeneous finite-element model of the front-end of the electric vehicle was developed using the numerical tool LS-DYNA. Two types of frontal-frames were simulated and tested. The design of the battery pack of the model was inspired by Tesla’s Model-S battery pack. The modules of the battery pack are of lumped masses with 444 elements matching the number of the battery cells contained in each module of Tesla Model-S battery pack. Every element preserves the mechanical properties of the 18650 cylindrical lithium-ion battery cells. Primary crash dynamics are compared with the results of frontal crash tests obtained experimentally. The kinematics of the battery pack can be predicted in the event of full-frontal crashes using the presented finite-element model. Simulation models can be used for load analysis to understand the severity of failures to the battery cells in the event of frontal crashes. The results of the simulation will be used to test a proposed damped biomimetic layered honeycomb structure which will be added in the front end of the battery pack housing. The multi-layer biomimetic structure will have a bearing layer that contains Magnetorheological fluid and equipped with an electro-magnet circuit to change the viscosity of the fluid increasing the damping ratio of the smart structure. This mechanism will be modelled and tested to analyse the level of protection the biomimetic layered honeycomb structure will provide to the safety of the battery pack when the EV is involved in a frontal crash.
Mr. Mohammad Al Hariri, Tutor Assistant and PhD student, The School of Engineering, David Goldman Informatics Centre