A Switching Nonlinear MPC Approach for Ecodriving

In recent years many works focusing on improved vehicle fuel efficiency through advanced control have been carried out, reflecting the high interest in ecodriving of vehicles. Although many studies have shown the potential that optimal control based ecodriving can offer, these solution are often difficult to be translated into online control strategies, one of the reasons being the complexity of the optimal control problem and therefore the computational burden. To cope with this a novel online approach, based on switching Nonlinear Model Predictive Control (NMPC), is proposed. The NMPC strategy is developed for the case of conventional vehicles, where gear shifting and longitudinal dynamics are controlled. It is shown that our proposal can operate in real time, while recovering most of the performance achievable by an offline optimal solution. The development of the method is described in detail and its performance is analyzed. The results show that the proposed NMPC can successfully solve the ecodriving task and seems a good compromise between computational burden and performance suitable for field implementation.

[1]  Jan M. Maciejowski,et al.  Predictive control : with constraints , 2002 .

[2]  Karl Henrik Johansson,et al.  Road grade estimation for look-ahead vehicle control using multiple measurement runs , 2010 .

[3]  Péter Gáspár,et al.  Design of predictive optimization method for energy-efficient operation of trains , 2014, 2014 European Control Conference (ECC).

[4]  Alessandro Astolfi,et al.  Stabilization of continuous-time switched nonlinear systems , 2008, Syst. Control. Lett..

[5]  Erik Hellström,et al.  Design of an efficient algorithm for fuel-optimal look-ahead control , 2010 .

[6]  Xiaohai Lin,et al.  Energy-optimal adaptive cruise control combining model predictive control and dynamic programming , 2018 .

[7]  Luigi del Re,et al.  Emission constrained fuel optimal vehicle control with route lookahead , 2018, 2018 Annual American Control Conference (ACC).

[8]  Panagiotis D. Christofides,et al.  Predictive control of switched nonlinear systems with scheduled mode transitions , 2005, IEEE Transactions on Automatic Control.

[9]  Gian Paolo Incremona,et al.  Collaborative Eco-Drive of Railway Vehicles via Switched Nonlinear Model Predictive Control , 2018 .

[10]  Luigi del Re,et al.  Two layer optimal vehicle control for known routes , 2018 .

[11]  Dimitri P. Bertsekas,et al.  Dynamic Programming and Optimal Control, Two Volume Set , 1995 .

[12]  F. Allgöwer,et al.  Model predictive control of switched nonlinear systems under average dwell-time , 2011, ACC.

[13]  A P Stoicescu On fuel-optimal velocity control of a motor vehicle , 1995 .

[14]  Frank Allgöwer,et al.  Improving performance in model predictive control: Switching cost functionals under average dwell-time , 2012, Autom..

[15]  J. Geromel,et al.  Stability and stabilization of discrete time switched systems , 2006 .

[16]  Antonio Sciarretta,et al.  Optimal Ecodriving Control: Energy-Efficient Driving of Road Vehicles as an Optimal Control Problem , 2015, IEEE Control Systems.

[17]  Patrizio Colaneri,et al.  Robust model predictive control of discrete-time switched systems , 2007, PSYCO.

[18]  James B. Rawlings,et al.  Postface to “ Model Predictive Control : Theory and Design ” , 2012 .

[19]  Richard D. Braatz,et al.  Switched model predictive control of switched linear systems: Feasibility, stability and robustness , 2016, Autom..

[20]  R. Goddard A Method of Reaching Extreme Altitudes. , 1920, Nature.