Predictive energy management of hybrid long-haul trucks
Journal article, 2015

This paper presents a novel predictive control scheme for energy management in hybrid trucks that drive autonomously on the highway. The proposed scheme uses information from GPS together with information about the speed limits along the planned route to schedule the charging and discharging of the battery, the vehicle speed, the gear, and when to turn off the engine and drive electrically. The proposed control scheme divides the predictive control problem into three layers that operate with different update frequencies and prediction horizons. The top layer plans the kinetic and electric energy in a convex optimization problem. In order to avoid a mixed-integer problem, the gear and the switching decision between hybrid and pure electric mode are optimized in a lower layer in a dynamic program whereas the lowest control layer only reacts on the current state and available references. The benefits of the proposed predictive control scheme are shown by simulations between Frankfurt and Koblenz. The simulations show that the predictive control scheme is able to significantly reduce the mechanical braking, resulting in fuel reductions of 4% when allowing an over and under speed of 5 km/h.

Long haulage truck

Predictive control

Dynamic programming

HEV energy management

Automotive control

Intelligent cruise control


Lars Johannesson

Chalmers, Signals and Systems, Systems and control

Nikolce Murgovski

Chalmers, Signals and Systems, Systems and control

Erik Jonasson

Volvo Group

Jonas Hellgren

Volvo Group

Bo Egardt

Chalmers, Signals and Systems, Systems and control

Control Engineering Practice

0967-0661 (ISSN)

Vol. 41 83-97

Driving Forces

Sustainable development

Areas of Advance



Subject Categories

Computational Mathematics

Vehicle Engineering

Control Engineering



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