A Two-Level MPC for Energy Management Including Velocity Control of Hybrid Electric Vehicles
Journal article, 2019

© 1967-2012 IEEE. Todays cruise control systems try to keep a constant speed given by the driver without regarding the energy consumption. There is, however, possibilities to save energy by choosing the optimal velocity is neglected. Solving the underlying control problem for long distances with an algorithm that runs on a vehicle control unit is not straightforward, especially when it comes to hybrid electric vehicles (HEV). In order to overcome the computational burden, this paper presents a two-level model predictive control approach. It uses a sequential quadratic program (SQP) that comprises the total travel distance computing a target set for a lower layer that uses discrete state-space dynamic programming and Pontryagin's maximum principle to compute the optimal control for a short horizon. The computational efficiency is shown by a case study for an HEV passenger car with parallel powertrain, which reveals a cost advantage of up to 39% compared to a benchmark solution that exactly follows the velocity of the SQP while both approaches yield the same travel time.

dynamic programming

model predictive control

sequential quadratic program

Pontryagin's maximum principle

hybrid vehicles

velocity control

energy management

Optimal control


Stephan Uebel

Technische Universität Dresden

Chalmers, Electrical Engineering, Systems and control

Nikolce Murgovski

Chalmers, Electrical Engineering, Systems and control

Bernard Bäker

Technische Universität Dresden

Jonas Sjöberg

Chalmers, Electrical Engineering, Systems and control

IEEE Transactions on Vehicular Technology

0018-9545 (ISSN)

Vol. 68 6 5494-5505 8688431

Subject Categories

Computer Engineering

Vehicle Engineering

Control Engineering



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7/8/2019 2