TY - GEN
T1 - A Predictive Control Design with Speed Previewing Information for Vehicle Fuel Efficiency Improvement
AU - Ozkan, Mehmet Fatih
AU - Ma, Yao
N1 - Publisher Copyright:
© 2020 AACC.
PY - 2020/7
Y1 - 2020/7
N2 - The growing vehicle connectivity and autonomy in the ground transportation system are not only able to improve traffic safety but also fuel efficiency. This paper proposes a computational friendly receding-horizon optimization-based nonlinear model predictive control (NMPC) algorithm to achieve fuel-saving speed planning for connected vehicles. The NMPC method solves for the fuel-optimal speed profile of connected vehicles considering a short speed preview of the preceding vehicle. By utilizing such previewing information through vehicle connectivity, the fuel consumption of the connected vehicles is reduced by avoiding unnecessary braking and acceleration, particularly in transient operating conditions. In order to analyze the effectiveness of NMPC design, dynamic programming (DP) method is adopted as a benchmark algorithm where the full speed preview of the preceding vehicle is known. The performances of NMPC and DP designs in driving behavior and fuel economy are quantitatively explored and compared under several standard driving cycles. Results show a promising improvement of the performance by adopting the proposed design and reveal the potential fuel benefits brought by vehicle connectivity and autonomy.
AB - The growing vehicle connectivity and autonomy in the ground transportation system are not only able to improve traffic safety but also fuel efficiency. This paper proposes a computational friendly receding-horizon optimization-based nonlinear model predictive control (NMPC) algorithm to achieve fuel-saving speed planning for connected vehicles. The NMPC method solves for the fuel-optimal speed profile of connected vehicles considering a short speed preview of the preceding vehicle. By utilizing such previewing information through vehicle connectivity, the fuel consumption of the connected vehicles is reduced by avoiding unnecessary braking and acceleration, particularly in transient operating conditions. In order to analyze the effectiveness of NMPC design, dynamic programming (DP) method is adopted as a benchmark algorithm where the full speed preview of the preceding vehicle is known. The performances of NMPC and DP designs in driving behavior and fuel economy are quantitatively explored and compared under several standard driving cycles. Results show a promising improvement of the performance by adopting the proposed design and reveal the potential fuel benefits brought by vehicle connectivity and autonomy.
UR - http://www.scopus.com/inward/record.url?scp=85089590255&partnerID=8YFLogxK
U2 - 10.23919/ACC45564.2020.9147826
DO - 10.23919/ACC45564.2020.9147826
M3 - Conference contribution
AN - SCOPUS:85089590255
T3 - Proceedings of the American Control Conference
SP - 2312
EP - 2317
BT - 2020 American Control Conference, ACC 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 American Control Conference, ACC 2020
Y2 - 1 July 2020 through 3 July 2020
ER -