The future of modelling real-world fuel economy
CAE simulation tools have long been an asset for engineers to evaluate technology alternatives and predict performance. Over the last decade, CAE tool capability has made substantial strides towards simulating real-world fuel economy. The gap in CAE tool capability resides in how we instruct tools to mimic the real world, and today's standard modelling approach is insufficient. To take analysis beyond scripted scenarios and standard drive cycles, a promising modelling approach known as Agent-Based Modelling (ABM) is being explored to capture the dynamic interactions between a vehicle and its operating environment.
In this webinar we cover CAE advancements that are enabling ABM to make significant strides in predicting real world behavior as well as present a recently completed application using the ABM methodology.