An energy and emission conscious adaptive cruise controller for a connected automated diesel truck

Conventional speed planning for connected automated vehicles (CAVs) adopts an energy-centric perspective and improves fuel economy by means of reducing the power loss due to braking and operating the engine at its high efficiency region. This paper considers a simulated connected automated truck with a diesel powertrain and a selective catalytic reduction (SCR) system for the treatment of NOx emissions, and first shows that a 20% fuel economy improvement is followed by up to 50% increase in NOx emissions with conventional speed planning due to its sole focus on energy that neglects emissions. Then, a novel model predictive controller (MPC) is designed for concurrent treatment of energy and emissions within speed planning of the CAV. Details of this energy and emissions conscious (E2C) MPC design are described, including the vehicle, powertrain and emission model development, selection of the appropriate objective function and its parameters for acceptable optimality, and computational performance. Simulation results of the E2C-MPC over multiple drive cycles are presented to demonstrate the robust performance of the controller. The results show 5–15% improvement in the fuel economy with a corresponding 0–25% reduction in NOx emissions for different drive cycles without requiring re-calibration for each test cycle.