Integrated Adaptive Cruise Control for Parallel Hybrid Vehicle Energy Management

The possibility to distribute the traction power in a hybrid electric vehicle powertrain over different prime movers and energy recoverability via recuperative braking as well as buffering the energy on rechargeable batteries, lead to the question of how electrical, mechanical or chemical energy should flow among various hybrid components of the powertrain. It is already known that any information about the future driving condition over either a short or long distance horizon is critically valuable to optimize the hybrid strategy. ACC (Adaptive Cruise Control) is a well-known driving assistant system that allows maintaining a safe longitudinal inter-vehicle speed and distance with other traffic objects. Model Predictive Control (MPC) based ACC system inherently predicts the vehicle velocity and acceleration profile. This information together with sensor data can be used to generate the optimal hybrid control especially while approaching a slower vehicle, which means a recuperation potential for the battery and hybrid energy management system. To achieve this, second order curve fitting is applied to the cost function of Equivalent Consumption Minimization Strategy (ECMS) behaviour. The approximated variant is then used to estimate the look-ahead battery energy and if necessary apply pre-discharge strategies to fully benefit the recuperation energy during deceleration manoeuvres.