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A Method to Extend Inverse Dynamic Simulation of Powertrains with Additional Dyanmics

Inverse dynamic powertrain simulation, like in Advisor or the QSS-toolbox, has proven to be an efficient and successful approach to simulate vehicles during drive cycles. The approach is based on back-calculation of accelerations and torques from the prescribed velocities in the drive cycle, and the differentiation requirements in this simulation process limits the possibility to include additional states in the powertrain models. The main objective here is to extend the simulation with additional dynamics like e.g. mean value models of the engine. This is achieved using stable inversion of nonlinear systems that can handle such additional dynamics. Computer algebra can be used to perform the necessary model transformations. A key step in obtaining sufficient differentiation properties is to smooth the drive cycle using a kernel with interpretation as an implicit driver model. The proposed method is demonstrated using Mathematica for model transformation and Matlab for simulation.

Anders Fröberg and Lars Nielsen


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Last updated: 2019-08-05