Quasi-optimal Energy Management of Range Extender Buses in Presence of Changing Traffic Conditions

Buses and other vehicles with regular routes and stop patterns are an important application field for hybrid electric drives. Given initial and final desired state of charge (SOC) of the battery, the optimal distribution of power between both sources, battery and engine, can be computed off-line for a known driving cycle. In the case of a range extender (REX) with an engine switched between two operating points, the solution boils down to a sequence of engine state changes. However, applying this profile to the vehicle under general traffic conditions proves very inefficient, as the required traction power over time will change strongly according to the actual traffic and load situation. Instead, this paper suggests to use a spatial-domain SOC trajectory based on off-line optimization results as reference quantity, for which simulations indicate a smaller sensitivity to varying traffic conditions. The paper shows the a posteriori computation of an energy efficient control sequence as well as an on-line implementation that utilizes model predictive control (MPC) and a short-term prediction of the future power demand. Evaluation is performed using a detailed nonlinear simulation model and real traffic data where the limited loss of optimality due to changes of traffic but also due to the driver’s style is confirmed.