Predictive energy management of hybrid electric vehicles via multi-layer control
Journal article, 2021

This paper presents predictive energy management of hybrid electric vehicles (HEVs) via computationally efficient multi-layer control. First, we formulate an optimization problem by considering driveability and a penalty for using service brakes in the objective function to optimize gear, engine on/off, engine clutch state, and power-split decisions subject to constraints on the battery state of charge (SOC) and charge sustenance. Then, we split it into two control layers, including a supervisory control in a higher layer and a local power-split control in a lower layer. In the supervisory layer, a gear and powertrain mode manager (PM) is designed, and optimal gear, engine on/off and clutch states are obtained by using a combination of dynamic programming (DP) and Pontryagin's minimum principle (PMP). Moreover, a real-time iteration Secant method is proposed to calculate optimal battery costate such that the constraint on charge sustenance is satisfied. In the local controller layer, a linear quadratic tracking method (LQT) is used to optimally split power between the engine and the electric machine and keep battery SOC within its bounds.

real-time iteration Secant method


multi-layer control



model predictive control (MPC)

State of charge

Hybrid electric vehicles

Energy management


Hybrid electric vehicle (HEV)


Maryam Razi

Chalmers, Electrical Engineering, Systems and control

Nikolce Murgovski

Chalmers, Electrical Engineering, Systems and control

Tomas McKelvey

Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering

Torsten Wik

Chalmers, Electrical Engineering, Systems and control

IEEE Transactions on Vehicular Technology

0018-9545 (ISSN) 1939-9359 (eISSN)

Vol. 70 7 6485-6499 9435008

Driving Forces

Sustainable development

Areas of Advance



Subject Categories

Aerospace Engineering

Control Engineering

Other Electrical Engineering, Electronic Engineering, Information Engineering



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4/5/2022 6