Energy Optimization of a hybrid car engine

Proposition type:
Post-docs
Latest date:
septembre 30, 2009
Responsability:
COMMANDS
Detail:

Presentation:

The project aims at developing mathematical tools to model and simulate scenarios allowing to improve the performances of electric car engines. Let us recall that the hard point of the electric technology lies on the restricted kilometric autonomy related to a weak density energy of the battery and a weak speed of its refill in energy (8 hours for the slow load). The goal of this project consists in:
  • Maximizing the absolute autonomy (hybrid technology)
  • Minimizing the autonomy variability: Optimal management of the energy by taking into account the available informations of navigation
These problems can be described by stochastic dynamic optimization problems. The objective of our project is twofold:
  • Theoretical and numerical study of related stochastic optimization problems
  • Validation on the model associated with the problem of hybrid car engine

Host institution:

Commands Team (INRIA-Saclay, CMAP, ENSTA) in collaboration with Renault (Technocentre Guillancourt).
Applied Mathematics Department (UMA) at ENSTA-Paris and Center of Applied Mathematics (CMAP) at Ecole Polytechnique offer two excellent environments in fundamental and applied research.

Post doc position (from January 2009):

A one year postdoctoral research position is available, extendable to a period of two years. Candidates should have a PhD in applied mathematics, and have a good knowledge of optimal control theory and/or stochastic optimization. Please apply by email, at one of the contact adresses below, with a full curriculum vitae, a list of publications, and the names and addresses of at least two referees.

Salary:

Approximately 1900 Euro net per month. This post-doc is supported by Renault & Inria-Saclay.

Contact:

Hasnaa Zidani , and Frédéric Bonnans

Master's internship (Mar-Aug 2009) & PhD (Sept 2009 - Aug 2012):

A good background in applied mathematics is required, as well as experience in programming. Knowledge in optimal control theory is welcome. This internship is supported by Renault & Inria.

Contact:

Hasnaa Zidani , Frédéric Bonnans , and Kamal Aouchich