ROUTE-BASED ADAPTIVE OPTIMIZATION FOR ENERGY MANAGEMENT OF HYBRID ELECTRIC VEHICLES

Compared with real-time control, global optimization has a great advantage to improve the fuel economy due to considering the whole drive condition in advance. However, on-board controller doesn't support the global optimization with a large amount of calculation. Remote data communicating technology provides a platform to make global optimization applied to on-board control at a pre-known driving cycle. In this paper, a route-based optimal control strategy for the real-time energy management of parallel hybrid electric vehicles is developed. The proposed control strategy employs computers to optimize the power-split and engine stop-start control based on the minimum principle at a predicted driving cycle. Guiding controller provides real-time control with CAN bus communication. The experiment results prove the proposed strategy has a 10% fuel economy improvement than rule-based control strategy.