Optimized Powermanagement for Human Driver-HEV Using Online Identification of Velocity Patterns

Inspite of the advances in hybrid electric vehicles (HEVs), most powermanagement and optimization techniques are developed for predefined driving cycles. In this contribution, an optimal solution for the future is provided, which encompasses multiple aspects of HEV control. A new embedded-online optimization approach is considered. Instead of carrying out online powermangement optimization with computationally extensive algorithms, the entire task is divided into two parts: an offline part where optimal parameters for different velocity values of a human driver are recorded, an online part where these parameters along with identification and prediction algorithms are used to display the optimal information to the driver online. The online display of results where a real human influences the HEV by driving via a real-time interface show the applicability of this approach.