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: 2019-12-17