The safety of electric vehicles (EVs) has become increasingly important as the number of EVs has grown rapidly in recent years. This work presents a system solution to model the full EV structural crash analysis together with its active battery cells using a thermal-mechanical-electrical coupled analysis. This multi-physics analysis predicts the sequence of events that could lead to thermal runaway and battery fire. In previous work, a representative battery cell model was first developed based on matching the cell dimensions and the total amount of material in a realistic cell. Each battery component was modeled separately with realistic mechanical, electrical, and thermal material models.
Nowadays, lithium-ion batteries are considered as most efficient source of power for electric vehicles (EVs). With the increasing utilization of EVs, the requirements for higher performance, lower weight and improved safety also growing. These demands can be fulfilled by an improved traction battery design, which consists of decreased battery frame mass or higher number of battery cells. However, with these improvements come several negative aspects, such as higher risk of battery frame intrusion or reduction of space between the cells. Due to these factors, the risk of battery damage is rising and it is crucial to predict and better understand the behaviour of the battery cells during critical situations, such as vehicle crash.
Safety is an important functional requirement in the development of large-format, energy-dense, lithium-ion (Li-ion) batteries used in electrified vehicles. Many automakers have dealt with this issue by enclosing the batteries into robust protective cases to prevent any penetration and deformation during car crashes. While this worked well for first-generation vehicles, consumers are increasingly interested in higher range, which makes overengineered heavy protective cases detrimental for range. A more detailed understanding of battery cell behavior under abuse becomes is therefore necessary to properly make design trade-offs.
The adoption of electric vehicles (EVs) has brought renewed attention to battery safety, particularly in scenarios where batteries are subjected to mechanical abuse, such as car crashes. The potential for battery cells to catch fire or exhibit thermal runaway under such conditions necessitates a comprehensive understanding of the underlying physics. The complex interplay of structural, thermal, electrical, and electrochemical phenomena presents a formidable challenge for accurate simulation and prediction of battery behavior. In this context, the integration of multiphysics coupling within Ansys LS-DYNA® has emerged as a crucial tool for studying battery abuse and enhancing safety measures.
Ensuring battery safety is one of the key issues in the design of electric vehicles. In many cases, batteries are designed to be placed in strong cases or with sufficient clearance to prevent serious damage. On the other hand, to develop a vehicle which is lighter and can run longer, it is necessary to reduce the weight of battery cases and the clearance between cells. To meet the above requirements, it is important to fully understand the mechanisms leading up to the occurrence of short circuits that cause thermal runaway, and to feed such information back into the design.
In numerous mechanical engineering applications, the use of multiscale computational modeling and simulations is imperative. Nevertheless, the computational challenge persists in addressing complex multiscale systems due to the vast dimensionality of the solution space. The field of machine learning (ML) has experienced ongoing development as a feasible option that might potentially expedite, substitute, or complement traditional numerical techniques.
Full Electric Vehicle Crash Simulation Using Coupled Thermal-Electrical-Mechanical Analysis