Time to Torque Optimization by Evolutionary Computation Methods

Paper #:
  • 2017-01-1629

Published:
  • 2017-03-28
DOI:
  • 10.4271/2017-01-1629
Citation:
Wang, J., Michelini, J., Wang, Y., and Shelby, M., "Time to Torque Optimization by Evolutionary Computation Methods," SAE Technical Paper 2017-01-1629, 2017, doi:10.4271/2017-01-1629.
Pages:
8
Abstract:
Time to torque (TTT) is a quantity used to measure the transient torque response of turbocharged engines. It is referred as the time duration from an idle-to-full step torque command to the time when 95% of maximum torque is achieved. In this work, we seek to control multiple engine actuators in a collaborative way such that the TTT is minimized. We pose the TTT minimization problem as an optimization problem by parameterizing each engine actuator’s transient trajectory as Fourier series, followed by minimizing proper cost function with the optimization of those Fourier coefficients. We first investigate the problem in CAE environment by constructing an optimization framework that integrates high-fidelity GT (Gamma Technology) POWER engine model and engine actuators’ Simulink model into ModeFrontier computation platform. We conduct simulation optimization study on two different turbocharged engines under this framework with evolutionary computation algorithms. It is shown that, compared with baseline control, modifying exhaust variable cam timing (VCT) and spark timing transient traces can significantly reduce TTT. Based on this, a new transient control strategy has been proposed and implemented on a dyno engine. Test results show that the newly developed strategy can reduce the TTT by 20% and increase peak torque considerably.
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