Title :
Energy management strategy for a parallel hybrid electric truck
Author :
Lin, Chan-Chiao ; Kang, Jun-Mo ; Grizzle, J.W. ; Peng, Huei
Author_Institution :
Dept. of Mech. Eng., Michigan Univ., Ann Arbor, MI, USA
Abstract :
Due to the complex nature of hybrid electric vehicles, control strategies based on engineering intuition frequently fail to achieve satisfactory overall system efficiency. This paper presents a procedure for improving the energy management strategy for a parallel hybrid electric truck on the basis of dynamic optimization over a given drive cycle. Dynamic programming techniques are utilized to determine the optimal control actions for a hybrid powertrain in order to minimize fuel consumption. By carefully analyzing the resulting optimal policy, new rules can be ascertained to improve the basic control strategy. The resulting new control strategy is shown to achieve better fuel economy through simulations on a detailed vehicle model
Keywords :
dynamic programming; electric vehicles; energy measurement; intelligent control; optimal control; road vehicles; dynamic programming; energy management; fuel consumption; hybrid electric vehicle; optimal control; rule based control; Automotive engineering; Control systems; Dynamic programming; Energy management; Fuels; Hybrid electric vehicles; Mechanical power transmission; Optimal control; Power engineering and energy; Vehicle dynamics;
Conference_Titel :
American Control Conference, 2001. Proceedings of the 2001
Conference_Location :
Arlington, VA
Print_ISBN :
0-7803-6495-3
DOI :
10.1109/ACC.2001.946337