Algorithms that eliminate the forward/backward restriction in vehicle performance and energy use analysis.

摘要

The goal of this research was to develop algorithms that allow generalized flexibility in vehicle system design analysis. Unique features of the algorithms include freely selecting known and unknown variables, improved convergence speed, and solving combined systems of algebraic equations and differential equations without restriction on the unknown variable. These algorithms were combined and their effectiveness demonstrated in a vehicle design application, SmartDesigned Vehicles (SDV). SDV was verified using industry standard simulation models and vehicle test data. The results show that SDV accurately predicts vehicle performance and energy use over a range of performance parameters and vehicle characteristics. Using the new algorithms in SDV removes the restriction of defining a forward or backward facing solution strategy and allows the user to focus on specifying performance goals to drive vehicle design.