Ecological Adaptive Cruise Controller for a Parallel Hybrid Electric Vehicle

This paper focuses on developing an Ecological Adaptive Cruise Controller (eco-ACC) for a parallel Hybrid Electric Vehicle (HEV) in a two-vehicle platoon in order to improve its fuel economy. This goal is achieved by globally optimizing a) its speed profile in relation to the leading vehicle in order to avoid unwanted driving behaviours (eco-driving), b) the management of the two energy sources of its powertrain, the Internal Combustion Engine (ICE) and the Electric Motor (EM), and c) the gear ratio of its Continuously Variable Transmission (CVT). The Nonlinear Model Predictive Control (NMPC) framework is adopted to develop the optimal controller, which is then tested on a control-oriented parallel HEV model developed for this purpose. Simulations are conducted for various standard driving cycles as the speed profile of the leading vehicle and different values of the prediction horizon. Results based on the suburban WLTP-M cycle are presented. To evaluate the effectiveness of the controller, its performances are compared with the full horizon optimal solution found using Sequential Quadratic Programming (SQP).