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A comparison of stochastic optimal control laws for a parallel hybrid vehicle

Lars Johannesson (Institutionen för signaler och system, Reglerteknik) ; Bo Egardt (Institutionen för signaler och system, Reglerteknik)
Proceedings of the 8th International Symposium on Advanced Vehicle Control, Taipei, Taiwan (2006)
[Konferensbidrag, refereegranskat]

This paper studies the properties of stochastic optimal control laws for hybrid vehicles, derived using stochastic dynamic programming with a Markov Chain as a drive behavior model. The focus of the study is on establishing how complex the Markov Chain model needs to be in order to achieve good performance. Moreover, a simple robustness analysis is done in order to examine how a control law, optimized with data from one city, performs when evaluated in a city with a considerably different drive behavior. The results indicate that it is sufficient to use a Markov Chain model with only power demand as the sole variable in the Markov state. Furthermore the simulation results show a remarkable robustness for the fuel consumption of the derived controllers when evaluated on a new drive behavior.

Nyckelord: Powertrain and Drivetrain Control, Fuel Cell and Hybrid Vehicles

Denna post skapades 2007-01-08. Senast ändrad 2015-05-08.
CPL Pubid: 24988


Institutioner (Chalmers)

Institutionen för signaler och system, Reglerteknik (2005-2017)



Chalmers infrastruktur