Adaptive model predictive control for hybrid electric vehicles power management

For hybrid electric vehicles (HEVs) that have predictable routes, it is beneficial to use model predictive control (MPC) to derive the optimal control trajectories that can minimize fuel consumption while achieving other objectives. However, for applications such as city buses and delivery trucks, even though the driving routes are pre-determined, the loads of the vehicles are changing from time to time. The trajectories computed by the dynamic programming (DP) or other optimization algorithms based on the pre-defined model might not be optimal during real-time operation. Therefore, an adaptive control design with on-line vehicle parameter estimator is needed to account for those unpredictable changes. In this work, we propose an adaptive model predictive control (AMPC) design that can estimate and update the vehicle mass in real-time. A comparative case study is conducted to analyze the effectiveness of adaptation by comparing the AMPC and non-adaptive MPC in terms of fuel economy. An MPC algorithm based on DP is integrated with a parameter estimation algorithm based on the least squares, simulation results based on a comprehensive vehicle model is presented in this paper.

[1]  Richard Bellman,et al.  Dynamic Programming and the Smoothing Problem , 1956 .

[2]  Keith Wipke,et al.  HEV Control Strategy for Real-Time Optimization of Fuel Economy and Emissions , 2000 .

[3]  Lino Guzzella,et al.  Optimal control of parallel hybrid electric vehicles , 2004, IEEE Transactions on Control Systems Technology.

[4]  Ilya V. Kolmanovsky,et al.  A stable block model predictive control with variable implementation horizon , 2005, Proceedings of the 2005, American Control Conference, 2005..

[5]  Ilya V. Kolmanovsky,et al.  Control, Computing and Communications: Technologies for the Twenty-First Century Model T , 2007, Proceedings of the IEEE.

[6]  Huei Peng,et al.  A stochastic control strategy for hybrid electric vehicles , 2004, Proceedings of the 2004 American Control Conference.

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

[8]  Petros A. Ioannou,et al.  Robust Adaptive Control , 2012 .

[9]  Yong Zhang,et al.  Optimal energy management for a series–parallel hybrid electric bus , 2009 .

[10]  Alberto Bemporad,et al.  Model predictive control of magnetically actuated mass spring dampers for automotive applications , 2007, Int. J. Control.

[11]  L. del Re,et al.  Optimal control of dual power sources , 2001, Proceedings of the 2001 IEEE International Conference on Control Applications (CCA'01) (Cat. No.01CH37204).

[12]  Thierry-Marie Guerra,et al.  Control of a parallel hybrid powertrain: optimal control , 2004, IEEE Transactions on Vehicular Technology.

[13]  Thierry-Marie Guerra,et al.  Equivalent consumption minimization strategy for parallel hybrid powertrains , 2002, Vehicular Technology Conference. IEEE 55th Vehicular Technology Conference. VTC Spring 2002 (Cat. No.02CH37367).

[14]  L. Guzzella,et al.  Control of hybrid electric vehicles , 2007, IEEE Control Systems.

[15]  Ilya V. Kolmanovsky,et al.  Predictive energy management of a power-split hybrid electric vehicle , 2009, 2009 American Control Conference.

[16]  Jianqiu Li,et al.  Optimal vehicle control strategy of a fuel cell/battery hybrid city bus , 2009 .

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

[18]  Anna G. Stefanopoulou,et al.  Recursive least squares with forgetting for online estimation of vehicle mass and road grade: theory and experiments , 2005 .

[19]  Jing Sun,et al.  Optimal control of hybrid electric vehicles with power split and torque split strategies: A comparative case study , 2011, Proceedings of the 2011 American Control Conference.

[20]  Erik Hellström,et al.  Look-ahead Control of Heavy Trucks utilizing Road Topography , 2007 .

[21]  Huei Peng,et al.  Power management strategy for a parallel hybrid electric truck , 2003, IEEE Trans. Control. Syst. Technol..

[22]  Lino Guzzella,et al.  Optimal Hybridization in Two Parallel Hybrid Electric Vehicles using Dynamic Programming , 2008 .