Modern battery system engineering operates at the intersection of multiple demanding objectives, with each parameter exerting its own influence on the overall performance and efficiency of the design. Engineers are faced with the formidable challenge of optimizing energy density, quantified as kwh/kg, ensuring longevity in terms of years or operational cycles, maintaining paramount safety standards, and achieving all these within defined cost parameters.
Battery system engineers are presented with the multifaceted task of balancing diverse objectives: energy density (kwh/kg), lifespan (years or cycles), safety, and cost factors. Present toolchains exhibit constraints in addressing these parameters concurrently at multi-scale levels, resulting in fragmented and sequential workflows. CAD tool updates, considering component intricacy, often become time-intensive, thus limiting swift iterative processes. Additionally, design modifications frequently necessitate manual interventions by CAE professionals due to the absence of robust associativity, extending feedback duration.