Global optimisation of energy management laws in hybrid vehicles using dynamic programming. (22nd December 2005) - Scordia, J.; Desbois-Renaudin, M.; Trigui, R.; Jeanneret, B.; Badin, F.; Plasse, C.
This paper presents an optimisation method based on dynamic programming, concerning the elaboration of energy management laws for hybrid electric vehicles (HEV). The objective is to minimise fuel consumption on a-known-in-advance driving schedule based on normalised or actual conditions (offline process). An optimisation tool implementing this method has been developed, called KOALA. It allows short computation times, and is flexible as it allows us to code new architectures easily. The main outcome of KOALA is the comparison of different HEVs with regard to fuel consumption, that allows us to estimate the potential consumption gain for different HEV architectures, and to forecast the best component sizing for a given vehicle architecture. Another outcome is the possibility of deriving online management laws from the optimal offline ones given by KOALA. In this paper we focus on the operating mode and validity of the optimisation process.